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“Quite simply, if you are designing e-learning, you should be following Michael’s earned, respected, and apt advice. In this updated version of his classic, he points out the dearth of and need for, good e-learning, and then tells us succinctly how to get there.”

—CLARK QUINN

Executive Director at Quinnovation

“Michael Allen’s books have been the fundamental reasons for me to establish an e-learning development firm in Singapore.”

—SHAMINI MANIKAM

Founder, TinkTank Talent Associates

“Our industry is littered with rapidly produced content and it’s time we look back to one of our pioneers to learn where we went wrong. Dr. Allen speaks to the heart of the issues today with solutions designed to realign training to its business goals.

With an unwavering focus on the science behind learning design, Dr. Allen’s latest k

book is essential for anyone passionate about designing training to deliver tangible k

results.”

—GLENN BULL

Founder & CEO, Skilitics

“Michael Allen’s Guide to e-Learning is one of the books I consider to be essential reading for any e-learning designer. It’s full of useful design frameworks and vivid examples.”

—JULIE DIRKSEN

Author of Design for How People Learn

“Michael’s use of stories and missteps to add context elevates the experience of the learners. Learning becomes memorable. In this book Michael elegantly weaves boring fact-based content with realism, emotions and motivation. Read this book and breathe new life into your courses.”

—RAY JIMENEZ, PH.D.

Chief Learning Architect,

Vignettes Learning Training Magazine Network

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“I still remember the day I picked and started reading the first edition of Michael Allen’s Guide to e-Learning. It completely changed my perspective and gave me practical ideas on creating engaging, interactive, and fun eLearning courses. Feeling the same joy reading the second edition today.”

—POOJA JAISINGH

Senior eLearning Evangelist, Adobe Systems

“There are experts, and then there are the people the experts talk to when they really want to know the truth. Michael Allen is one of those people. He was there at the start of the eLearning industry and has devoted his entire career to nurturing, shaping, growing and, sometimes, disciplining entire generations of learning professionals who seized on an approach to development that Michael helped to create. Michael Allen’s Guide to e-Learning is a must read for anyone (ANYONE) who aspires to create meaningful, measurable and impactful e-learning.”

—LARRY ISRAELITE

“Being in the industry for many years, seeing the constant flux of change, it is refreshing to see professionals that remain adamant on certain qualities and still recognize the difference communicating ideas and concepts effectively can make k

in all these forces pulling the industry in every direction. As Michael recognizes, k

“learning begins by drawing the learner’s attention. A meaningful task challenge takes the place of traditional learning objectives”. Indeed, creativity and the ability to write content that is meaningful, motivational, and memorable at the same time, however essential skills, are not to be taken for granted. I am re-assured that we do enter the next age still with a few great professionals to hold as beacons of quality and true essence in this constant changing.”

—CHRISTOPHER PAPPAS, MBA, MED

Founder & Owner of the eLearning Industry Network

“Michael Allen, one of the ‘e-learning elite,’ has crafted a second edition that is more relevant and practical than ever. His ‘Seven Magic Keys to Motivational eLearning’ are worth the price of the book alone! This book is sure to be your go-to guide for everything ‘e.’”

—ELAINE BIECH

Author Training and Development for Dummies and 101 Ways to Make Learning Active Beyond the Classroom Editor ATD

Handbook

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“This is an excellent example-filled update for the novice practitioner or the experienced one wanting to catch up – and brush up.”

—DR. JANE BOZARTH

Author of Better than Bullet Points and From Analysis to Evaluation eLearning Coordinator for the state of NC.

“Michael Allen nails it. This rework of classic is itself, an instant classic. He reminds us that creating meaningful, memorable, and motivational learning experiences is hard but critically important work. He presents tangible, accessible and highly impactful guidance for anyone designing instruction and crafts a stunning defense against those who want to create instruction by ‘taking the easy way out.’ His recommendations, examples and stories are based on rich intellectual knowledge of instructional design and vast experience in the field. If you want a book that will make you a better designer of instruction there is no other book.”

—DR. KARL M. KAPP

Professor of Instructional Technology, Bloomsburg University Author of The Gamification of Learning and Instruction

“Over a decade after the first edition, Michael Allen does it again with his second k

edition—bringing practical, research-inspired wisdom to e-learning design. I can k

dive in anywhere in the book and find nugget after nugget of inspired practical insights.”

—WILL THALHEIMER, PHD

President of Work-Learning Research, Inc

“It would be difficult to find any important topics regarding the e-learning industry that aren’t covered in this amazing volume. It is both a primer for those new to the industry and a reminder of what really matters to anyone who is already working in this field.”

—JOE GANCI

President, eLearningJoe, LLC

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“If you only read one book on eLearning and instructional design, let this be it. Full of updated and practical examples for today’s generation of e-learning designers, you’ll walk away inspired and more knowledgeable than before.”

—CAMMY BEAN

VP of Learning Design at Kineo

Author of The Accidental Instructional Designer: Learning Design for the Digital Age

“When Michael Allen talks, I want to listen! While the book covers many of the basics that a new practitioner would need, Dr. Allen also uses humor to challenge even experienced practitioners so that we don’t slip into bad habits or adopt hot trends just because they’re hot. He helps us stay the course.”

—DIANE ELKINS

Founder, Artisan E-Learning

“I often close my critique of a student’s work with the question “Are you having fun?” I often close my email with the axiom ‘Instructional Design is Fun!’ and Michael Allen provides a way for those assigned to design e-learning to have fun creating learning experiences that will help their learners have fun as they k

acquire the skills being taught. As he notes e-learning has become pervasive but, k

as he also correctly observes, way too much of this flood of online instruction is boring, ineffective, inefficient, and expensive because it wastes the student’s time and does not accomplish the goals of the organization providing the training.

Michael’s Guide to e-Learning is a very pragmatic approach that attempts to provide a simple way to design instruction that is meaningful, motivating and motivational while painlessly implementing the best that research has to say about effective, efficient and engaging instruction. This guide is a must read for everyone who is tasked to design e-learning whether trained instructional designers or designers-by-assignment. You’ll be glad you did. Keep smiling!”

—DAVID MERRILL

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Michael Allen’s Guide to

e-Learning

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Michael Allen’s Guide to

e-Learning

SECOND EDITION

Building Interactive, Fun, and

Effective Learning Programs

for Any Company

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Michael W. Allen

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This book is printed on acid-free paper.

Copyright © 2016 by Michael W. Allen. All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600, or on the web at

www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at www.wiley.com/go/permissions.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with the respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and k

strategies contained herein may not be suitable for your situation. You should consult with a k

professional where appropriate. Neither the publisher nor the author shall be liable for damages arising herefrom.

For general information about our other products and services, please contact our Customer Care Department within the United States at (800) 762-2974, outside the United States at (317) 572-3993 or fax (317) 572-4002.

Wiley publishes in a variety of print and electronic formats and by print-on-demand. Some material included with standard print versions of this book may not be included in e-books or in print-on-demand. If this book refers to media such as a CD or DVD that is not included in the version you purchased, you may download this material at http://booksupport.wiley.com.

For more information about Wiley products, visit www.wiley.com.

Library of Congress Cataloging-in-Publication Data is available:

ISBN 9781119046325 (Paperback)

ISBN 9781119046394 (ePDF)

ISBN 9781119046332 (ePub)

Cover Design: Wiley

Cover Image: Scott Colehour, Solutions Architect at Allen Interactions Printed in the United States of America

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In Memoriam

This book is dedicated to my niece

Rev. Kelly Allen

who was an inspiration to so many through her

exemplary life and

her tireless fight for the poor, discriminated, and defenseless.

Taken from us far too soon, I know Kelly,

an indefatigable scholar,

would encourage all efforts to help people learn and develop their full potential.

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Contents

Foreword by Tony Bingham

xiii

Preface

xv

Acknowledgments

xix

Chapter 1

What’s New?

1

PART I

THE BUSINESS PERSPECTIVE

15

Chapter 2

Plain Talk

17

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Chapter 3

What You Don’t Know Can Kill

(Your e-Learning)

29

Chapter 4

Making Success Possible

41

Chapter 5

Executive’s Guide to Good e-Learning

73

Chapter 6

Where Does e-Learning Fit?

83

PART II

GREAT E-LEARNING DESIGN

95

Chapter 7

Seven Simple Success Strategies

97

Chapter 8

The Serious e-Learning Manifesto

109

Chapter 9

Motivation in Learning

121

Chapter 10

Seven Magic Keys to Motivational

e-Learning

131

Magic Key 1: Build on Anticipated Outcomes

133

Magic Key 2: Put the Learner at Risk

144

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Magic Key 3: Select the Right Content

for Each Learner

156

Magic Key 4: Use an Appealing Context

171

Magic Key 5: Have the Learner Perform

Multistep Tasks

192

Magic Key 6: Provide Intrinsic Feedback

198

Magic Key 7: Delay Judgment

201

Chapter 11

Navigation

211

Chapter 12

CCAF and Interactive Instruction

235

Chapter 13

Interactivity Paradigms That Work

267

Chapter 14

Successive Approximation and SAM

297

PART III SERIOUS LEARNING GAMES

327

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Chapter 15

Serious Learning Games: Where

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Rules Rule

329

Chapter 16

Integrating Instructional Content

and Games

341

Chapter 17

Learning Games, Serious or Not?

357

About the Author

379

References

381

Additional Resources

387

Index

389

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Foreword

Meaningful. Memorable. Motivational. When was the last time you applied those three words to an e-learning course you took?

My guess is you might answer “never” or “rarely.” And that’s a problem.

It’s a problem Michael Allen masterfully tackles in the second edition of Michael Allen’s Guide to e-Learning.

Nearly thirteen years ago, when Michael published the first edition of this work, the case was still being built for the viability of technology-enabled learning. The debates raged about whether e-learning was actually learning, and whether people could learn via computers. Classroom was king and Michael’s work helped open eyes k

and minds to how technology could enable learning on a scale previously k

unimagined. These were the days before tablets and smartphones, before Facebook and Twitter, before MOOCs and the Khan Academy. And Michael’s resounding call about the viability of e-learning rang loud and strong. But he also challenged us to understand that the value of e-learning wasn’t about the technology—it was about designing for the technology and making e-learning something different, something powerful, and something meaningful.

Today, the conversation is a bit different. Learning via technology is pervasive. Online courses are offered to students in elementary schools, and most young people will tell you their #1 research tool is YouTube.

Organizations continue to increase the use of technology to deliver learning. We know that people can and do learn via technology—and some prefer to learn that way. But e-learning still has not realized its full potential. There’s more of it, yes. But that doesn’t mean that what’s available is making enough of a difference in the lives of learners.

Michael talks about the “3Ms” (meaningful, memorable, motivational) in Chapter 5 (Executive’s Guide to Good e-Learning) and states, “What I value are meaningful, memorable, and motivational learning experiences because they have the best chance of enabling people to do what they want k

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and need to do.” This is a powerful statement that extends well beyond the context of e-learning. In fact, I think it is a lens through which all of us in the talent development profession can evaluate what we do and how we do it.

It’s critically important that we understand that the courses we design and deliver must be relevant to the learner. In organizations, learning’s relevance means aligning to goals and strategies that are meaningful to stakeholders and to employees. Some of this is about the learning experience, certainly, but there’s more to the story.

To be relevant and to create meaningful content, talent development professionals must partner with stakeholders to fully understand their needs, and then design courses and learning initiatives that address knowledge and performance needs, close skill gaps, and prepare pipelines of ready talent. This requires intentionality, preparation, and an investment of time—things that are often lacking because they are not valued as critical parts of the process.

We need to change how we think about what we do, why it’s important, and what it can achieve. The power of learning should not be undervalued or underestimated. Learners must do their own learning, of course, but those in the talent development profession are uniquely positioned to k

make that learning meaningful, memorable, and motivational. When we k

rise to that challenge we have the ability to affect real change and growth.

And that is Michael’s call to us. His passion for the “why” behind e-learning is evident in every page of this book. He’s brought new thinking and new insights to this second edition. He’s not only updated the content, he’s updated the context. He helps us see that just because we’re swimming in technology, doesn’t mean we’re using it well. He makes it very clear we’re not reaching our potential when it comes to e-learning.

And then he offers us a road map. As only Michael Allen can, he’s laid out examples and tactics and resources in a meaningful, memorable, and motivational way.

I encourage everyone with a passion for learning to read this book.

It will inspire your work.

Tony Bingham

ATD President and CEO

June 2016

xiv

Foreword

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Preface

It seems like yesterday when the first edition of Michael Allen’s Guide to e-Learning was published. But it was actually almost 13 years ago when the first copy was delivered to my doorstep on Christmas Day, even finding me vacationing with my family on Grand Cayman Island. Talk about your publisher pulling out all the stops to deliver a present at the best time and place!

When writing the first edition, I thought about how much I learned from very early endeavors in e-learning. Each undertaking was a serious event because expensive equipment was involved, programming took a lot of time and effort, and there were many skeptics ready to point out k

shortcomings. Disrupting sacred traditions of teaching, introducing cold k

insensitive machinery, and suggesting that teachers might better use their time as a resource to students rather than as presenters were bold and radical.

Nevertheless, there were inspiring achievements in that early work, along with many demonstrations of ineffective directions, too. The future promised meaningful, memorable, and motivational learning opportunities for all—if and when the barrier of delivery costs were overcome.

Not only have delivery costs dropped to negligible levels (something we honestly couldn’t have contemplated), but the capabilities of the delivery systems are now also greatly expanded to include video, animation, instantaneous searches of live data, portability, and so much more.

We now have none of the barriers we previously faced to provide excellent learning opportunities to all citizens of planet Earth—and at a very low cost, if any.

But what’s happened?

Well, the situation flip-flopped. In centers where instructional technology was being developed and tested, researchers developed critical know-how regarding how to use technology effectively. But today, we have legions of people who are blithely confident that their abilities to use tools k

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to present content and ask questions are sufficient. Instead of repeated evaluations to make certain instructional software is effective before going live on expensive delivery systems, e-learning courseware is now routinely delivered with no evaluation ever. Today, we’re concerned about every minute of authoring time as opposed to the much more important volumes of hours learners spend, productively or not.

So, the mission of this book has not changed. I continue to look for simplifying methods of courseware design that can both reduce authoring time and, most importantly increase learning impact. I believe much of what I offered in the first edition remains valid, but I’ve gathered and share herein additional concepts and methods that are useful to my colleagues and me.

Examples are always valuable, so I’ve updated examples, retaining a few that seem to make some points as clear as can be and adding new ones for inspiration. Because the nature of interactive instructional designs can best be understood by describing the essential components of context, challenge, activity, and feedback (CCAF), many of the examples are presented through identification of these components.

Second Edition Examples

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Chapter Page Concept

Example Title

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3

36

Experiences vs. presentations

Locating an Earthquake’s

Epicenter

10

138

Building motivation through

Expedia Travel Planning

anticipated outcomes vs.

learning objectives

10

150

Using risk to increase learning

Sunnyside Grill

motivation

10

166

Reversing traditional “tell and

Cooking with Flair: Preparing

test” to measuring abilities first

Fruits, Salads, and

(testing) allows subsequent

Vegetables

instruction to be tailored to

individual needs

10

183

A compelling story and novel

Manhattan Associates:

are combine to make an

Supply Chain Training

engaging context

10

187

Using a novel context to make

Why Does Glue Stick?

learning experiences memorable

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Chapter Page Concept

Example Title

10

193

Authentic multistep tasks

POST LERT First Responder

engage learners more deeply

and help transfer learning to

performance

10

205

Delayed judgment is more

AutoNation: Customer Care

representative of the

performance feedback learners

receive on the job

11

218

Allowing learners to browse and

ZebraZapps “Sneak Peek”

assess courseware as easily as

feature

they would a book

11

227

Multifunction navigation bar

NYI Medical Center: ICIS

provides controls and status

patient records

information

11

228

Reusable model implements all

American Airlines WorldTutor

navigation imperatives

12

238

Primary components of

Supervisor Effectiveness:

instructional interactivity (CCAF)

Employee Security

12

244

Second example of CCAF

Railroad Safety for

Professional Drivers

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12

260

Varying complexity of user

Deciduous and Coniferous

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gestures doesn’t equate to

Trees

more effective learning

experiences

13

268

Models That Work: Increased

Airline Reservations and

incentive to learn when

Ticketing

available help takes more effort

to access

13

271

Models That Work: Task Model

NYU Medical: Integrated

Clinical Information System

13

278

Models That Work: Corrective

Who Wants to Be a Miller?

Feedback Paradigm (CFP)

13

284

Models That Work:

Corning Substance Abuse

Problem-Solving Investigation

13

288

Models That Work: Discovery

POST-LERT—Recognizing

learning

and Reporting

13

293

Models That Work: Storytelling

In Their Virtual Shoes

(Washington State Coalition

Against Domestic Violence)

16

349

Integrating games and learning

Sunnyside Grill

content

17

361

Using extrinsic games for drills

Modified Jeopardy Board

and practice

Preface

xvii

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I hope you’ll agree this edition digs to the roots of excellent learning experiences, identifies and clarifies the critical components, shows how to match instructional strategies to identified types of targeted outcomes, and simplifies instructional design in valid, practical ways.

I’m so grateful for the great flood of feedback from the first edition. It has inspired me in countless ways, and I’ve learned so much from readers and their feedback. Please, do let me hear from you!

Michael Allen

February 2016

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Acknowledgments

I am very much indebted to the many people who have cheerfully assisted in the production of this book and to those who inspired it by so enthusiastically sharing with me their experiences with the first edition—my first published book. What fun it has been to autograph copies and pose in selfies with my readers.

My appreciation goes to those who have educated, hired, and inspired me, those who have set the example of sharing objective evaluations and opinions of alternative approaches to e-learning, my employees who strive daily to design and produce the best learning experiences possible within given constraints, and my friends and family—without whose support k

there would be no second edition.

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As in the first edition, the examples shown offer real, functional e-learning applications. There are no abstract mockups here. I am so proud to be able to share that first collection of work, not only because they are such fine accomplishments, but also because those who commissioned them are proud of them—and proud enough to share them publicly. This time around, I had many more candidate examples than I had space for. It was hard to choose. With our studios producing countless works for the most prestigious and demanding corporations, and achieving more awards than we can possibly display at one time, the library of examples has grown to immense proportions.

Steve Lee was invaluable in his assistance sorting through projects, recommending examples, and annotating their notable characteristics, just as Ethan Edwards was for the prior collection, some of which were retained because they so perfectly illustrate key concepts. Helpful editorial feedback came from Ellen Burns and Michelle Kenoyer.

My assistants, Sarah Bertram and Jose Benitez, worked tirelessly with document management, formatting, communicating, coordinating, and so much more. Try as I would to confuse things, they kept sorting things out and calming my hysterics.

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Linda Rening, a talented writer, experienced editor, and the nicest, warmest person you’ll ever meet, volunteered to edit my ramblings while also giving me helpful feedback on content. Her sharp and creative eye is responsible for whatever appeals to you in this text; the rest of it is my doing.

Chris Palm and Joslyn Schmitt did a fantastic job of providing a more modern aesthetic to the book through a redesign of old graphics and creation of new ones. They have tremendous talent, are spectacularly fast, and are really fun to work with. Thank you to Scott Colehour and Pete Lisowski for their efforts to produce a presentable cover photo.

I couldn’t be more grateful to Tony Bingham for his encouragement of this work and ATD’s promotion of the concepts through workshops, webinars, and bookstore events. Please note Tony’s foreword herein. We’re all so lucky to have his leadership in our industry. Special thanks also to Glenn Bull and editors@thenewid.com for their permission to use their great comic strips. It’s important to keep good humor as we tackle the many diverse opinions on what makes good instruction and how to create it.

Special thanks to Martin Lipshutz, my business partner and a confident and steady rudder who keeps Allen Interactions functioning smoothly and efficiently while I devote so much time to works like this. And my hat goes k

off to all the others who somehow manage to devote the time and effort k

it takes to publish works of guidance on e-learning. I know how much time and energy it takes and the sacrifices involved, but I always learn so much when reading your publications, and I always try to integrate the contemporary thinking, knowledge, and experience of others into my work.

Again, my wife and family do so much to accommodate my mental fugues and sojourns, which happen so unpredictably. I always come back, and without having to ask “What did I miss?” I can count on an empathetic account to catch me up. They are the biggest supporters of my happiness and goals.

Thank you all.

xx

Acknowledgments

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Michael Allen’s Guide to

e-Learning

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Chapter 1

What’s New?

What’s new in our field? What’s new in this second edition of the

Guide?

Useful world knowledge continues to advance by leaps and bounds.

Along with the growth of knowledge comes the need for more effective access, communication, and aids to learning these ever-more-complex understandings.

Similarly, brain research continues to inform conversations across k

multiple disciplines (Blakemore and Frith, 2005) and appears on the k

edge of providing valuable insights for teaching, although we remain short of transferring knowledge instantly and bioelectrically as forecast in the movie The Matrix:

Neo: Can you fly that thing [helicopter]?

Trinity: Not yet. Taps cell phone.

Tank: Operator.

Trinity: I need a pilot program for a B212 helicopter. Hurry. Seconds later: Enlightened facial expression. Let’s go!

As technology transforms in amazing ways, often with unexpected consequences, I’m ready to think we will find effortless ways to transfer knowledge and skills at some point. But as appealing as that is, we need to accept the fact we’re just not there yet. In the meantime, the question should be: while it’s still necessary for learners to do their own learning, how can we best facilitate the process?

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My observation is that we continue to look for unrealistically easy answers. We even hope simple access to information may preclude the need for any instruction or learning at all. It seems we want to avoid the work of creating meaningful, memorable, motivational learning experiences, even though there’s no doubt they provide the best way for people to learn and improve performance. There’s no evidence the fundamentals of human brain function have changed recently and diminished the value of effective instruction. But we seem to keep looking for signs that has occurred as an excuse for not doing the admittedly challenging work of instructional design.

Although there are frequent claims that succeeding generations learn in different ways, most are myths (Bruyckere, Kirschner, and Hulshof, 2015). I’ve seen no foundational changes in what we know about how people learn or in what we know about effective instruction. The critical principles remain valid and, sadly, unheeded. And yet claims abound that, with advances in technology, everything has changed.

This edition of Michael Allen’s Guide to e-Learning was created to respond to the assertions that everything has changed and quality instructional design is no longer critical. Responses are provided through:

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• New perspectives on the hyperbolical claims that everything has changed

• Additional efforts to simplify and clarify foundational principles that haven’t changed (and aren’t likely ever to change)

• A fresh, new, and expanded collection of examples of approaches that work

To get started, let’s take a look at these opposing perspectives—that nothing fundamental has changed versus everything (or at least a whole lot) has changed.

2

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Nothing Has Changed

Let’s first consider the perspective that nothing has changed—at least not the most important aspects of learning and instruction. Take the process of human learning, for instance. The foundations of human learning have not changed, despite concerning attempts to excuse lack of instructional effectiveness by suggesting the human brain works differently now that we’re in the digital age (Bruyckere et al., 2015, p. 142).

We’re still quite certain that much of human learning is centralized in the brain and that information gets to the brain through our nervous system from our senses of sight, hearing, smell, taste, touch, and through kinesthesia (awareness of the position and movement of body parts that is essential in coordinated activity).

We also remain confident that meaningful learning is a function of tying new information to existing, well-rooted knowledge and physical skills. And, we know most well-rooted knowledge and physical skills were established through experience and practiced application. We understand that it takes energy to learn and that learners must spend this energy themselves; we cannot learn for them. We know motivation behaves like a water hose to direct attention and release energy, and we know motivations k

fluctuate up and down in response to situations, such as rising scores in a k

game, an inspiring TED speaker, or boring e-learning.

We have considerable evidence that practice aids learning, and practice spaced over time leads to more enduring memory and behavior patterns.

We also know:

• Examples are more effective when paired with counterexamples

• Worked problems provide clarity often missing from instruction

• Consequences shown in response to specific learner behaviors elevate helpful emotional involvement as well as understanding and do so more effectively than simple, right/wrong feedback For decades now, the Successive Approximations Model (SAM) has been a remarkably effective process and alternative approach to designing and building learner-centered learning experiences. It has been less widely known and applied than it is today, so perhaps there’s been some change here. Its value is now even more certain. Coverage of SAM in the first edition of this book resulted in a flood of appreciative feedback, so it What’s New?

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remains a centerpiece of this edition as well, updated a bit from the work we’ve done to prepare for workshops and webinars on the process and from feedback from countless applications.

In summary, we really know quite a lot about human learning, effective instruction, and instructional design. These long-standing foundational concepts continue to offer valuable guidance. That’s why we can say: nothing critical has changed, including the need for us all to pay greater attention to validated fundamentals. And, in this second edition, foundational concepts remain in the spotlight. They are covered as straightforwardly as I could manage.

Everything Has Changed!

An alternate perspective—perhaps the more commonly held perspective—is that so much has changed in the world of e-learning, we are almost starting from a clean slate. The one correct aspect of that assertion is that today one might not even recognize what’s going on in the field of e-learning as an outgrowth of its origins.

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In its infancy, instructional design for e-learning was taken very seri-k

ously, the paradigms we used were an outgrowth of learning science, and we carefully evaluated courseware before launching it to larger populations of learners. Today, the prevalent notion is, “thank goodness, instructional design isn’t that complicated. It’s not really a profession. Everyone can develop good instruction. You just need to remember the six steps.”

Although I endeavor to help everyone attempting to design instruction to find ways to be effective, and I actually think many people complicate the process unnecessarily, it’s very troublesome to see so many do-it-yourself lists presented as sufficient guidelines to genuine design integrity and excellence.

Let’s look at some of the changes frequently noted—the good, the bad, and the very much unexpected.

Prevalence of e-Learning

One obvious change is that e-learning is no longer new or a novelty for most organizations and institutions. Its use has spread broadly, and there is a plethora of ways technology is used—all unfortunately lumped into the category e-learning. Today, 77 percent of U.S.

companies offer e-learning in their professional development programs 4

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(Roland Berger, 2014). More than 80 percent of higher education institutions offer at least several courses online, and more than half offer a significant number of courses online (EDUCAUSE, 2013).

Low Expectations

In whatever capacity organizations have come to use e-learning, the way they use it defines what e-learning is and, very often, what they think it should and will be for them. In so many cases, initial unguided forays into e-learning reduce delivery costs in the short-term, but achieve little in terms of behavior change or performance improvement. e-Learning has so many more capabilities and advantages than most people ever recognize.

Lost Perspective

At the conception of e-learning, we tried to determine how effective instruction could be delivered via computer technology (Allen, 2008).

Missing some of the capabilities of live instructors, but having its own unique capabilities—such as the ability to accommodate needs of any number of learners individually—we asked, Can e-learning be as effective as typical classroom instruction? Could the e-learning experience be even more effective than that delivered by an instructor? The exciting answers, k

proven now through decades of experiments and applications, are yes k

and yes.

There was another important observation, too—a broadly evidenced fact: There are many forms of e-learning that are not only poor substitutes for live instruction, but also painfully ineffective and wasteful. Not everything called e-learning has the same utility or capability. Just as not all instructors are effective with the techniques they employ, not all e-learning is effective with the instructional techniques implemented in it. And complicating matters, some forms of e-learning are effective in some circumstances for some goals but not in other circumstances for other goals.

What’s changed? The change is that, many years after its conception, people now think of e-learning as an instructional approach, whereas e-learning is actually a delivery platform with an interesting set of capabilities. The instructional design of experiences delivered through e-learning reflects the instructional strategy or pedagogy and determines effectiveness. Because e-learning can provide a wide variety of instructional experiences, it’s inappropriate to speak in terms of whether or not e-learning is effective. A specific design must be evaluated in light of the goals for which the e-learning was deployed. And then the results, good or bad, must be attributed only to the design, not to e-learning as a whole.

What’s New?

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Yet we now deal with the problematic perception that e-learning is a singular and often rather simplistic method of instruction, which is nothing close to its potential.

Lost Expertise

Perhaps the most significant change is the number of people saddled with the responsibility of creating e-learning having so little knowledge of prior work. Whether enthusiastically delving into the field with the confidence— I can do that! —or with the ambition to create better e-learning than they’ve seen—or having been given the task because no one else was available, many people today have to produce e-learning in shorter and shorter time frames. They simply don’t have the time needed to learn fundamentals of good design let alone become proficient at it.

Catering to the demand for instant training, providers of courseware development tools suggest that building courseware is mostly about implementation as opposed to design. Anyone can build great instruction, “just click here.” And people go for it. As a result, much invaluable knowledge about appropriate and effective instructional design is ignored or buried in the past, lost and forgotten.

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New (Mobile) Delivery Options

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Today, we further complicate the landscape by adding into the mix an expanded variety of delivery technologies of which mobile devices are presently receiving prominent attention. Because a delivery device is mobile, do people learn differently? No, of course not. Despite the fact that some developers of mobile applications claim mobility changes everything, it doesn’t. And, excuse me, our reluctance to go along with the new world stance isn’t because we’re not open to new possibilities; it’s because mobility is just one new opportunity technology provides. It’s not a panacea for all instruction.

Mobility does offer new possibilities that have great value for certain goals and situations (for an overview of options and carefully considered viewpoints on m-learning, see Quinn, 2011), but it doesn’t change the most important factor: the instructional design, not the delivery technology, determines effectiveness.

Mobility provides valuable conveniences and the ability to deliver some learning experiences in real-life contexts, which is sometimes desirable and sometimes very dangerous. We recognize the importance of context—the critical importance of context for learning—but we also prize the possibility of placing learners in multiple contexts and adjusting those contexts to 6

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provide a range of examples and challenges that enrich learning. Real-life contexts cannot often be manipulated at practical speeds and costs just for the purpose of instruction, or to meet the needs of each learner.

Questions About Mobile Delivery

With mobility, do we have a different

To a degree, yes.

array of instructional approaches to

choose from?

Are there more options to create

Unfortunately, yes. (Although, we had

ineffective e-learning?

plenty of ways to fall short already.)

Does mobility offer additional ways

Yes.

e-learning can be of value?

Is making the right instructional design

Absolutely. With mobility, there are even

choice more important than ever?

more ways to look clever and smart while

wasting time, money, and opportunity.

Could we ask the same questions of online video, social learning, serious learning games, real-time simulations, and massive open online courses (MOOCS)? For sure, yes.

And the answers? The same as above.

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Mobile Performance Support versus

m-Learning

The value of mobility is not to be understated. It can, in fact, bring great value by making other kinds of learning unnecessary. Used as an on-the-spot source of reference material, such as a checklist or a video demonstration, it can make it unnecessary to memorize the same information through learning. The performer need only remember how to access the guidelines or job aids needed to perform to expectations.

Even in this, the technology can assist by using either or both global positioning data (GPS) and photographic recognition to look up relevant resources.

This is, indeed, a change to the instructional landscape and a welcome opportunity. But when mobile devices are used for various types of reference access and performance support, these uses should not be called m-learning or any kind of learning. Something more like m-help or m-guidance would be more accurate. This is a different domain with its own challenges and opportunities and can be a welcome complement to instructional systems.

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Learning Games

Since the emergence of video games with their avid users and explosive market, we stalwarts in e-learning have witnessed the fact that engaged users will spend long sessions at the keyboard, and learn facts, skills, and strategies for simply the satisfaction of conquest and touting all the fun they’ve had doing it. This flies in the face of what too many pundits claim: Today’s digital learners don’t have patience for anything beyond short snippets of information. In many cases, what’s learned from entertainment games has some general utility, such as problem recognition, problem solving, and quick keyboard/controller skills. The major skills acquired are, however, typically pertinent only to the game at hand. Yet the time and effort is worth it to the millions of people who build and proudly demonstrate superior game skills. If only we witnessed the same behavior, outcome, and fun reported by e-learners.

e-Learning designers haven’t been blind to the coveted attributes of computer games. In the early 1990s, a flood of “edutainment”

products hit the market, boasting fun learning. Unfortunately, the vast majority of these products, delivered via CD-ROMs, were neither instructional nor fun. A few succeeded, but what many designers thought would be fun wasn’t. It was clear they didn’t understand what k

makes games tick.

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Our understanding of games has advanced immeasurably, although groundwork was actually laid for game-based instructional design long ago. The concept of applying the engaging and motivating aspects of games to digital learning experiences, is even older than the work of the 1990s, although you’d think from recent hyperbole the idea has just dawned on us. For a bit of very interesting history, watch the videos at the Computer History Museum covering work done in the 1970s on the PLATO system, much of it looking and feeling like a game, and all of it providing fun immersive and even addictive learning experiences. Here’s the link to one: https://youtu.be/rdDwoUk4ojY.

In a later chapter on Serious Learning Games (SLGs), I’ll lay out my new understanding of how to design instructional games that have high impact and are really, truly fun. The exciting discovery for me in this research is that both successful games and successful e-learning experiences are actually built on the same components: context, challenge, activity, and feedback (CCAF). And, further, that when game rules reflect real life relationships between actions and consequences, we not only get learners to work gleefully at skills development but also to develop skills that have real life applicability and value.

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Social Learning

It’s a difficult challenge in creating instruction to think like a new learner. When you have deep content knowledge and skills, you have synthesized the content and recognize the interrelationships of its components so well that you instantly see and act on patterns—patterns new learners are unable to detect. Recent learners may have an easier time than experts when asked to unravel confusion and answer questions from new learners. This presents an opportunity for social learning.

Social learning builds on the multichannel digital communications at hand today to facilitate access to people with helpful information—people who can communicate at the right level. Peers working under the same constraints and facing similar challenges can share how they deal with issues and how they’ve adapted processes for greatest effectiveness.

Further, technology may embolden us to ask questions we might not ask in face-to-face contexts. Learners can take their time to compose questions (as we can do with e-mail and texting) and converse in a protected and relatively safe environment. In large organizations, and those with a geographically distributed workforce, exchanges may offer the comfort of anonymity, which may encourage others to disagree with answers given or k

to offer alternative suggestions and expanded information.

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Social learning can be very effective and valuable. As is always the case, it has advantages and disadvantages. Not having to prepare courseware, but just making a lot of information accessible sounds attractive. Letting learners guide themselves instead of providing professional instructors seems like a major reduction in training costs. But a risk of social learning is that unmonitored poor practices can be perpetuated resulting in something akin to the blind leading the blind. And, that more experienced and knowledgeable people may not participate when needed. Exchanges can become more social than instructive, absorbing big chunks of time.

Indeed, social learning doesn’t take instructional design off the hook; social learning systems need organization, preparation, leadership, and continuing participation by experts.

What’s Old Is New Again

With so many head-turning paradigms and technologies it could seem like we need to start over again to determine what makes effective instruction.

Mobile delivery has become inexpensive and practical in a short span of time. Published game frameworks make it easy simply to insert content here, and in no time, you’re up and running with a game to present questions What’s New?

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and score results. Learners can easily communicate with one another, access and exchange information, and download files.

People of many backgrounds, skills, and talents find themselves involved in creating instructional applications because interactive technology is more accessible than ever before. Creation tools that emphasize speed and minimal instructional knowledge seduce the unwary into instructional design roles where, although well-meaning, they are not ready or able to make good design decisions.

There’s no doubt we are blessed with more ways than ever to help people and organizations perform better. It’s all very exciting. At the same time, even more expertise is required to choose an effective path—to avoid what’s novel and new but not the best fit.

Unprepared courseware developers, with far too many instructional models, tools, and delivery technologies, are spurred on by eye-catching examples that have great appeal, but actually miss most instructional opportunities. This has created a new environment in our industry. And, it is why my answer to the question What’s new? could well be everything.

And yet, the most important guidelines remain the enduring basics of what we know about learning and performance. Through all these changes, it’s more important than ever to be grounded in, and guided by, the basic k

principles of human learning and performance.

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Can This Book Make Sense

of It All?

For those who have undertaken serious study of human learning and have extensive experience in technology-assisted learning, redirecting the field onto more effective paths has become a pervasive challenge.

As always, I try to be pragmatic. I’ve hoped to help by linking theory, research, and practice for those who need to build effective learning applications. Although I would greatly enjoy a life of research on nuances of instruction and learning, I find it abhorrent that millions of learners are forced into boring, ineffective, time-wasting “lessons” when they could be energetically developing valuable skills that would enhance self-worth, self-confidence, and the ability to contribute meaningfully to pursuits of their choice.

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It Doesn’t Have to Be Like This

Perhaps I’m overwrought about missed learning opportunities and poorly used technology. Perhaps I’m taking this all too personally, and perhaps almost every well-balanced person feels poor instruction and wasted time will always be a part of learning programs. Like it or not, no one should get agitated about it. No big deal. That’s life.

But I just can’t accept this. It doesn’t have to be like this. e-Learning can be so much better. If it were, it could change our world for the better. Seriously. It matters when people have marketable skills and can reduce economic disparity. It matters when people understand the history and values of nations—their own and others. It matters when people can communicate in a common language, understand one another, tackle common problems, and share their insights. And it matters when people give up, thinking they can’t learn.

When technology entered the exclusive domain of live teachers, interacting face to face with their students, many reacted to the intrusion with fear and pushed back in understandable ways. There needed to be proof that the pros outweighed the cons before letting technology take responsibility for teaching their students. So, extensive exploratory work began. It became clear that, with proper design, extraordinary learning k

opportunities were, in fact, feasible. Further, technology made it possible k

to deliver consistently great learning experiences to very large populations of learners. Amortizing costs across larger numbers of learners would afford far more time and expertise in preparation of content and still produce learning experiences that cost very little per learner. In short, the cost per student could be far less than traditional classroom instruction and the learning experience far better.

Lower Costs, Better Learning

Delivery costs are less today—far less than the sum cost of classrooms, teacher salaries, travel, materials, and other components of traditional training and instruction, where costs have risen and will continue to rise.

Organizations have not missed this point, but many have taken a tragic turn. Instead of using a portion of the savings provided by e-learning delivery to produce higher-quality learning experiences that would lead to valuable performance contributions in return, they rejoice at initial overhead cost reductions and continue to squeeze design and development costs. The result is that e-learning is often not much better than a data What’s New?

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sheet or a manual on the screen, perhaps with a 10-item quiz included.

Better than nothing? Perhaps, but not much better.

So, I am agitated. Poorly designed, boring e-learning is not something I endure easily because it’s so unnecessary and hard to justify.

It just makes no sense to me. It’s very hard to sit by when every learning opportunity could lead to a beneficial and enjoyable experience, available worldwide and systematically improving as better ideas were incorporated.

Contrast this vision with today’s common practice of haphazardly thrown together courses that waste learner time, frustrate learners, and cause some to despair of their abilities and lose what small interest they might have had in the topic.

With delivery of instruction via e-learning being so inexpensive, e-learning on a wide range of topics should really be free to all. We should strive for this. But in the present situation, e-learning should be better than it is—more inspiring, more fun, more effective, more meaningful, more memorable, more motivational. It’s hard to accept excuses for it being otherwise.

Bill Norris, CEO of Control Data Corporation

k

nourished the famous PLATO project—a

k

system that was far ahead of its time

in terms of e-learning. He wanted (and

tried) to fund pretty much anyone who

wanted to develop e-learning, because

across the globe there were populations

of people interested in every topic. When

a first version of an e-learning course

became widely accessible, he applauded

the start and expected others would help

Bill Norris

improve it. Through what we now call

crowd-accelerated innovation, he expected

courseware to evolve continuously, reflecting the inspiration and wisdom of the world’s best experts and teachers. Once the idea that freely sharing knowledge and skills became a recognized human value, he expected this somewhat utopian vision to be realized through funding for courseware from many sources, public and private, and through contributions of time and creativity from people who just want to help others. I shared this vision with Mr. Norris in my work on the PLATO system and on Authorware, and continue to believe wholeheartedly that it can be realized.

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No Excuses, Please

My thesis is this: Instructional design is a profession requiring study and mentored practice to achieve excellence. If learners are going to exchange their time for the learning outcomes an instructional event provides, we have an obligation to make that time productive. It doesn’t take many learners for the accumulated usage time to become significant. Employers need to take note here that broadcasting poor instruction quickly becomes a huge expense in both direct costs of employee time (even without factoring in costs of delivery) and indirect costs of missed opportunities because people were in training and unavailable to work. As the number of students rises, the need to make instruction effective becomes paramount; yet, decision makers who insist on frittering money away on hastily produced, time-wasting training somehow overlook this, preferring to ask how much training costs can be reduced further.

But here’s the good news. Simple principles and an effective process can help create much better learning activities than those we typically see. The weak designs so prevalent in the field are really so deplorable that even just the application of a few principles and a slight process change would help a lot. I would personally relish seeing continuous advancement in our most sophisticated approaches. Certainly, there are k

k

important investigations being undertaken at various universities and corporate centers, but the greatest benefits probably will be made by improving the oceans of ineffectual applications at the lower end of the spectrum. Here’s where people are making unnecessary, fundamental errors—the prevention of which costs nearly nothing. Here’s where I think I and this book can help most, although I’ve included much material I believe is of value across the spectrum of design experience, from novice to sophisticated pro.

New Examples

While the first edition of this book had a good and useful collection of examples (many readers told me the examples were invaluable to them), it seemed only fitting to reward readers of this second edition with an updated collection. Admittedly, it was somewhat difficult to improve on the initial collection, but they were built in older technology and were not able to do all the things we can do so easily now. So one last element of change is found in new examples, although I had to hold on to some of my old favorites that illustrate concepts so clearly and seem to have timeless value.

What’s New?

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Ready?

So, the table is set. We’re going to look at ways to design and produce e-learning you can be proud of. We will identify fundamental concepts that will enable you to do an excellent job with whatever resources, time, and money you have. We’ll take advantage of technology, but we won’t let technology mask poor designs. And we’ll produce for our organizations performance improvements that will justify every penny of their support.

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Part I

The Business

Perspective

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Chapter 2

Plain Talk

Success is getting people to do the right thing at the right time!

Did I shout loudly enough? e-Learning is about success, both individual and organizational. It is about behavioral change—again, both individual and organizational. It’s also about inspiration, competency, and even fun with technology. It’s where I’ve lived for well over 45 years, and I invite you to join me in reviewing the state of e-learning from a very personal perspective.

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I’d like to show you the often untapped potential I see in e-learning and share with you some lessons I’ve learned about how to make e-learning a valuable competitive investment for any organization striving to be more successful.

There are many reasons for the prevalence of e-learning, ranging from practical to idealistic. Pundits note that in our information-based economy and society, e-learning may be the component needed most to improve lives dramatically. It will allow us to learn what we want to learn where and when we want to learn it. It will provide choices in how we learn. It will make hard things easy and boring things fun. It will wres-tle our intellectual laziness to the ground while helping each of us use more of our untapped capabilities. And, with knowledge and skills readily acquired when the spirit moves us, we will blissfully pursue alternate careers on a whim. Life will be grand.

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Sure.

But wait. Let’s not dismiss these possibilities just because they seem idealistic and therefore unrealistic. Is it possible e-learning could provide equal access to learning and information? Regardless of socioeconomic status and geographical location, is it possible everyone could have similar if not identical opportunities to build valuable skills, enjoy economic prosperity, become leaders, inventors, artists? Is it possible corporations will take training seriously not just from altruistic motivations but also because there’s no better way to attract and retain a competitive workforce while improving business results?

I think so. But it won’t happen with the type of e-learning that’s dominating the scene today.

The e-Learning Dream

When organizations sit down to study their primary goals and performance needs, they look at the products and services they want to provide; the fidelity of service or manufacturing that will be competitive, marketable, and profitable; and their current abilities to provide them. If k

they are not already performing at a sufficient level, they review staffing, k

process, leadership, and management.

Often, it is necessary to put a strategic program into place, which likely includes training as one of its components. Because they have systematically achieved excellent results, those responsible for creating training take an honored seat at the executive table to help plan the next strategic advancement. (See Figure 2.1.)

Right. Please don’t wake me; I’m enjoying the dream. While this does happen in some organizations, of course, it is the exception rather than the rule despite overwhelming statistics regarding the financial rewards of investing in training and the strategic advantages it brings.

Who’s Kidding Whom?

To this long-term (many would simply say old) proponent, researcher, observer, and developer of technology-based learning applications, it’s hard to reconcile the impressive benefits possible from impactful e-learning with the fact that training budgets are often reduced to the extent those benefits can’t be realized. There seems to be so little concern for impact and return on investment. In many cases, e-learning programs are launched to address business objectives that, 18

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Effective

if met, could improve the bottom line. But

Instruction

those objectives won’t be met just because the

training is now delivered via technology. Ben-

efits have a critical dependency primarily on

the design of the instruction itself and secon-

darily on the technology on which it was deliv-

Strategic

Valued

Planning

Results

ered.

and Support

It doesn’t seem to matter how much

technologies for the delivery of effective

interactive instruction evolve or how much

FIGURE 2.1

Circle 1—

we have learned about effective instructional

the success cycle.

design; training is considered by many to be

an annoying cost rather than a strategic investment. Business leaders ask, How much can we reduce our training costs? You can always reduce them as long as they are greater than zero. The better question to ask is, What’s the smart investment?

At the very low end of investment, there’s no value and the entire expense is wasted (see Figure 2.2). Above this, value returns at an increasing rate for a while and then flattens out. It’s important to note this isn’t an argument to put needless amounts of money into training k

programs. It’s important not to overspend. It doesn’t help anyone to k

have fancy spinning logos and other needless adornments that sap funds and return no benefit. I’ve seen plenty of pretty projects that have little instructional impact but cost a lot.

High Return

+

Best Value/Cost

Compromise

Increasing Return

per Dollar

Value to Company

Directive

Increasing Impact, but

Management

No Value

Less per Dollar

$0

Poor Value

Low Cost

$0

Investment $

+

FIGURE 2.2

Optimal training project budget.

Plain Talk

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Effective versus Boring—Choose One

Boring instruction is not effective instruction. Minds wander, attention wanes, learners muddle through, maybe. When learners push through, they’re through—relieved it is over and ready to escape to something else as quickly as possible. As they distance themselves from a painful experience, they aren’t mentally reviewing helpful information, nor practicing their new skills. Rich associations aren’t being created to help remember key points. They are retaining nothing of what they just saw and heard.

Needed behaviors have not been established. It’s a waste. Little comes from boring instruction. It’s bad.

A lot of boring material is being produced today, even while learner expectations are rising from exposure to the many great interactive apps and games available. User interface continues to become more facile and, at times, amazing. We expect to see the same thing in e-learning: new, inventive capabilities used to make learning more efficient and effective.

In contrast, simplistic, boring instruction

Boring

is being developed for electronic distribution

Instruction

in ever-increasing quantities. It is assault-

ing more and more people every day. The

courseware may have been designed fol-

k

lowing structures validated by research on

k

human learning (although probably not), and

Minimal

Lack of

Funding

Results

it may be totally correct from a content accu- and Support racy point of view. It may be totally proper

in terms of graphic design, typography, and

grammar. But it’s boring. Boring is bad. And

FIGURE 2.3

Circle 2—

it obscures the real opportunities e-learning

failure cycle.

brings.

Stop Boring Me

“Oh,” you’re thinking, “everyone knows boring instruction is bad!”

Do they? Would people deliberately put out bad instruction? No, but they would and do put out boring instruction. It seems that while bad instruction isn’t acceptable, boring is. So either designers don’t realize their products are boring (I think this is often the case), or they’re willing to accept boring as an unavoidable attribute of their “good” work.

When budgets are tight (and when aren’t they?), an unwitting experiment ensues. Training has to get by on less. Learning experiences aren’t likely to become less boring when produced on a reduced budget. So, if any development is done, more boring courseware is produced.

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“Guess what?” one executive says to another. “Training did just fine with their reduced budget and prerecorded webinars. I don’t see any performance differences, really. Of course, the training team is complaining they didn’t have enough resources to do it right, but it seems we’re doing just as well as before. Maybe we can cut training a little more! It doesn’t seem to matter.”

Entertaining Doesn’t Equate to Good

Of course, avoiding boredom doesn’t mean you’re providing good instruction. We know many instructor-led training events get outstanding smile sheet ratings because, perhaps, trainees have a great time. They enjoy laughs, treats, and time away from usual responsibilities. Who knows what smile sheets measure, anyway? As Will Thalheimer (2016) notes while risking outrage from disciples of Kirkpatrick’s four-level model of training evaluation, traditional evaluations are pretty much useless, especially as indicators of learning.

Providing a lively experience is a worthy and important goal, to be sure.

But many entertaining programs are nearly as bad as boring ones in terms of learner outcomes. Learners may take home some previously unknown facts that are great for image enhancement, but when the focus is primarily k

on fun, we easily lose out on improved performance and processes, as well k

as fail to achieve the instructional objectives.

Justifications and excuses for poor instruction abound as do stockpiles of boring e-learning courses. So let’s explore this a little further. How can it be so? I’ll tell you the reasons next.

Rationale for Reduced Quality

Nobody consciously opts for Circle 2, the failure cycle (Figure 2.3), but if sincere efforts at e-learning produce no recognized, meaningful results, it’s easy to conclude there are no good options here—that Circle 1 and that success cycle (Figure 2.1) are hyperbole and just don’t happen. With this perspective, Circle 2 becomes the functional road map and an entrapment that is difficult to break from. All too often I see organizations churning out courseware using the same templates over and over again—templates that continue to fail to provide the essential components of effective learning experiences.

The failure of so many e-learning applications to produce recognized results (beyond the rapture of their developers) has led to some very wrong Plain Talk

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conclusions about e-learning. Some popular but misleading conclusions include:

• e-Learning is boring by nature. The only interesting e-learning is that developed by a few rare and creative people with generous funding and open time lines.

• Effective e-learning can’t be developed quickly enough to meet our needs.

• Effective e-learning can’t be cost justified.

• Just presenting information is just as effective and good enough.

Boring Is Expensive

What’s the most expensive form of training? Regardless of whether training is delivered in a dedicated building by full time trainers to employees who have flown in from remote parts of the globe or through the convenience of e-learning, the most expensive training is training that doesn’t work.

The business cost of ineffective e-learning goes far beyond simply losing all the money spent on it. (See Figure 2.4.) A proper accounting has k

to include the salaries of learners who were not productive during training k

hours. It has to include the residual decline in motivation that boring experiences produce. It has to include the damages poor performance causes.

When all is taken into account, the total cost of boring instruction can be many, many times greater than the direct cost of e-learning development and delivery, and may easily soar to multiples of the combined costs of the poor e-learning when we consider also the hidden costs of providing on-the-job training to fix the damage done by the e-learning. This is a cost which is often overlooked as well. The final bill becomes a sizable sum comprising tangible costs, plus probably the cost of missed opportunities.

Boring instruction is incredibly expensive.

Boring

Instruction

Effective

Instruction

Cost

Cost

FIGURE 2.4

Boring instruction is too expensive.

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This Just In: Effective e-Learning

Is Practical

Even if you haven’t yet witnessed it personally, you need to know that e-learning can provide extraordinary performance enhancements. It can be the least expensive training and the most popular among learners.

“The return-on-investment for e-learning can be 50 to 60 percent greater than for traditional training, which itself can have a 4x ROI, if done properly” (Boggs, 2015).

e-Learning can address some of the innumerable performance problems organizations face, while it can work at an individual level to help us all achieve more of our potential and a better quality of life. It doesn’t do this often enough, of course, but it’s possible.

Some of the things we’ve realized with good e-learning are impressive, including a wide range of benefits, as noted in Table 2.1. But, of course, not all e-learning is alike and too little delivers these desirable attributes.

But look again at the list of attainable e-learning attributes and benefits.

It’s an honest and impressive list.

While there is an undeniable upfront investment, the positive return k

on a sufficient investment can make e-learning one of the least expensive k

means of accomplishing critical organizational performance. With the right people, process, tools, and models, it can even be developed with amazing speed.

TABLE 2.1

Good e-Learning

Attribute

Benefit

Shorter learning time, often

Less time away from productive work.

much shorter

Lower training costs.

Adapts to learner needs

Minimized time away from productive work (people return to (i.e., learning mastery is fixed

work as quickly as individually able).

but individual learning times

No waiting for those needing extra time.

may vary)

Extra attention for those needing more help.

Actively involves learners;

In-depth learning experiences for each learner, not just for frequent activity

selected learners or those volunteering.

Ensures learning

No sliding by. Each learner must achieve and demonstrate competency.

( continued)

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TABLE 2.1

( Continued)

Attribute

Benefit

Generates positive learner

More enthusiastic participation.

attitudes (When done well,

More receptivity.

learners often rate e-learning

Greater likelihood learning will be applied to on-the-job activities as preferable to

performance.

alternatives.)

Provides consistent quality

e-Learning doesn’t have bad hair days, headaches, or late nights out.

Allows instant, worldwide

Through networked services, corrections, improvements, updates

and new information can be made available to all learners instantly.

Is available 24/7/365

Learning can start any day employees are hired or

immediately upon assignment to new responsibilities.

Learning can be worked in and around higher-priority activities.

Learner-managed schedules—learners can work late into the night, in short sessions distributed throughout the day, or in long blocks of time; whatever works best for them.

Is patient and treats all learners

Same options and same performance criteria for all learners.

objectively and fairly

Blind to racial, cultural, and sexual differences.

Offers no more or less learning support to any individual.

k

Is highly amenable to

Easily provides data necessary for the evaluation of each k

systematic improvement

and every component.

Saves money through low-cost

Big savings have resulted from many applications of delivery (no or minimized travel;

e-learning. Even taking full account of development costs, fewer or no instructors;

e-learning has a big advantage in cost savings.

automated administration; no

classrooms, supplies,

whiteboards, etc.)

Allows options for more

Support for learners with special interests or needs to go in-depth study or review

beyond the bounds of classes.

whenever needed

Material used for instruction can be accessed for later use as reference material in a well-designed application.

Want Proof?

Good Training Is Possible

e-Learning can work. e-Learning delivers handsomely for many organizations every day. When well designed, e-learning is extraordinarily effective, efficient with time, and pays for itself over and over again. It can put your organization in a more competitive position by: 24

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• Improving customer service

• Getting new processes up and running faster

• Reducing employee turnover

• Improving morale

• Increasing production

• Decreasing errors

• Improving product quality

• Improving efficiency

Study after study has demonstrated the effectiveness of e-learning when done well. David Boggs has compiled the documented list that appears as Table 2.2. It should, even for the most skeptical, be a compelling argument for building effective web-based training.

TABLE 2.2

Documented Benefits of e-Learning

Strategic Advantages

Creating a global workforce

Web-based training is a powerful instrument for

k

developing a global labor force. Web-based training can k

deliver custom, sophisticated instruction to employees all around the planet. (Driscoll, 2002)

Reacting to abbreviated

Companies that create today’s best-of-breed products product development cycles

and services are now introducing their wares more

quickly into the marketplace. The use of web-based

learning management systems allows your

organization’s training function to keep pace with the market. Web-based training can be used to provide

needed instruction without taking workers away from their daily responsibilities. (Driscoll, 2002)

Managing flat organizations

Down- and right-sized organizations have now become the norm in today’s business landscape. As a result, line managers have multiple responsibilities and are severely time impoverished. e-Learning can help by delivering training to those areas for which line managers are normally responsible, such as desktop application

training and product training. Managers are then freed up to tackle other pressing priorities. (Driscoll, 2002) ( continued)

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TABLE 2.2

( Continued)

Strategic Advantages

Adjusting to employee wants

Economic and demographic shifts have fueled the

and needs

growth of telecommuting, virtual offices, job sharing, and flextime. Delivering training via the Internet overcomes the obstacles imposed by the exigencies of a transient workforce. (Driscoll, 2002)

Facilitating a contingent labor

Contingent workers, such as temporaries, consultants, force

retirees who work part time, and the self-employed, have increased dramatically over the last decade. Companies and organizations have become more reliant on

contingent workforces to deal with peak labor demands.

e-Learning solutions and web-based learning

management systems are invaluable tools to train and manage this unique labor force. (Driscoll, 2002)

Retaining valued workers

Education has become a critical linchpin in a company or organization’s worker benefits portfolio. Workers in today’s new economy are not as afraid to move to a new position if they feel their interests and career welfare are better provided for in a different environment.

Web-based training programs that offer certifications, college and graduate school education, and important k

job skills become powerful incentives for an employee to k

stay. (Driscoll, 2002)

Increasing productivity and

Training of all kinds, including e-Learning programs, profitability

increase employee knowledge and skill levels. As they become better at their jobs, they sell more products, reduce waste, and are more productive and efficient. An educated, well-trained workforce is the main driver to profitability for today’s businesses. (Driscoll, 2002) Tactical Advantages

Flexibility to learn anytime,

Learners can access courses and content from their

anywhere

office, home, or hotel room from any spot around the globe. (Kruse, 2004)

Reduce travel and related

Save on hotels, airfare, meals, and other travel expenses costs

associated with traditional on-site training. (Kitchen & Ryan, 2004)

Tools for tracking, updating,

Web-based learning management systems make it easy

and managing training

to track, to update, and to manage online learners.

Learning management systems facilitate reporting,

succession planning, and workforce development from one centralized, web-based source. (Kruse, 2004)

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TABLE 2.2

Continued

Tactical Advantages

Affordable per-student costs

Almost every computer today has continual wireless

access to the Internet, so setup costs are relatively low. (Kruse, 2004)

Just-in-time learning

Online learners can take training just before they need it rather than enrolling in a course weeks or months before they need the training or a refresher class.

(Driscoll, 2002)

Making updates easy

Web-based training can be updated quickly and easily, so there is no time lag or extra reprinting cost.

(Driscoll, 2002)

Administer competency and

A centralized, web-based learning management system compliance management

aggregates all the data into one location so anyone with appropriate credentials can access the information when they need it. (Kitchen & Ryan, 2004)

Training Delivery Advantages

Consistent delivery

Web-based training is delivered uniformly in a consistent framework, which increases uniformity of knowledge and skills. (Kitchen & Ryan, 2004)

“Learning object” architecture

Web-based training is designed and developed so

k

supports on-demand,

content can be chunked into discrete knowledge objects k

personalized learning

to provide greater flexibility. Students can access these objects through preset learning paths, use skills

assessments to create individualized study plans, or use search engines to locate exact topics. (Kruse, 2004) Interactive content, graphics,

Interactive content, graphics, and animations make

and animations

lessons stand out and help imprint the material on the student’s mind. (Kitchen & Ryan, 2004)

Customized material

Content can be customized to meet the training

objectives of a specific program quickly and

easily. (Kitchen & Ryan, 2004)

Self-paced programs

Students can learn at a pace that works for their

individual learning preferences and life circumstances.

(Kitchen & Ryan, 2004)

Infrastructure Advantages

Leverage existing

Web-based training makes use of already-existing

infrastructure

infrastructure, such as computers, servers, intranets, etc. There is no addition outlay for hardware or capital assets. (Driscoll, 2002)

Controllable and secure

Web-based learning management systems can be easily access

configured to secure and monitor access. (Kurtus, 2004) Source: SyberWorks, Inc., www.syberworks.com. Used with permission.

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Chapter 3

What You Don’t Know

Can Kill (Your

e-Learning)

Of course, e-learning isn’t more effective than other forms of instruction just because it’s delivered via computer. The quality and effectiveness of e-learning are outcomes of its design, just as the quality and value k

of books, television, and film vary with the particular script, actors, k

episode, and movie. e-Learning can be very good, very bad, or anything in between. The way e-learning’s capabilities are used makes all the difference.

One cause of frequent instructional failures is that the actual reasons for undertaking e-learning projects are not defined, are not conveyed, get lost, or become upstaged. Most often, the success-related performance goal of enabling new behaviors is overtaken by the pragmatics of simply putting something in place that could be mistaken for a good training program.

When executives and other reviewers are not attuned to the criteria against which e-learning solutions should be evaluated, the focus of development teams turns to what those reviewers will appreciate: mastering technology, overcoming production hurdles, and just getting something that looks good up and running within budget and on schedule. These latter two criteria, budget and schedule, become the operative goals, stealing focus from the original reason for building an e-learning project. (See Figure 3.1.)

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Initial Goal

What’s Measured

Functional Goal

On Time, Trouble-

Performance

Cost, Development Time,

Free Rollout, Cost

Improvement

Smile Sheets, Complaints

Containment,

Good Looks

FIGURE 3.1

Transformed goals.

Surely performance success is the primary reason most e-learning projects are undertaken. Success comes from more responsive customer service, increased throughput, reduced accidents and errors, better-engineered designs, and consistent sales. It comes from good decision making, careful listening, and skillful performance. Remember: Success for organizations and individuals alike requires doing the right things at the right times.

How do things in e-learning run amok so easily? Two reasons: counterfeit successes (a.k.a., to-do-list projects) and undercover operations k

k

(a.k.a., on-the-job training [OJT]).

To-Do-List Projects

Unfortunately, many e-learning projects are to-do-list projects. The typical scenario: People aren’t doing what they need to be doing. Someone in the organization is given the assignment to get training in place. A budget is set (based on who knows what?), and the clock starts ticking down to the target rollout date. The objective is set: Get something done—and, by all means, get it done on time and within budget. Announce the availability of training, cross the assignment off the to-do list, and move on to something else. Goal accomplished.

For the project manager given the assignment, the driver for implementing e-learning easily transforms from the instigating business need—determining what people need to do and when, and finding the best way of assuring that performance can and will happen—to the pressing challenge of getting a training project done. This is likely because expenditures for training development and delivery are calculated easily, 30

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but training effectiveness is not quantified so easily and is, therefore, rarely measured at all. Any project manager knows how the success of the project will be assessed: timeliness, cost control, and by whether learners like it and report positive things about it. It will be measured by how good it looks, how quickly it performs, and whether it’s easy enough to use. Complaints aren’t good, so safeguards are taken to make sure the training isn’t too challenging and doesn’t generate a lot of extra work for administrative staff or others. The absence of complaints is a win.

Again, the original, driving goal of the project gets swept away and no longer determines priorities. The project transitions into somebody’s assignment to get something done (another project on the to-do list). It will be a success because every effort and sacrifice will be made just to get it done. Success under these criteria, however, will contribute little to the organization or individual learners.

Let’s Not Measure Outcomes

Indeed, many of the e-learning developers I know commiserate that no indicators of behavior change are likely ever to be measured and no assessment of either the business impact or the return on investment (ROI) is likely to be performed. In one study, for example (Bonk, 2002), nearly k

60 percent of more than 200 survey respondents noted their organiza-k

tions did not conduct formal evaluations of their e-learning. It would be very surprising if even 10 percent of organizations using e-learning actually conducted well-structured, valid evaluations. As research-to-practice expert on learning, Will Thalheimer (2016) notes:

We as workplace-learning professionals often work in darkness. We get most of our feedback from smile sheets—also known as happy sheets, postcourse evaluations, student-response forms, training-reaction surveys, and so on. We also get feedback from knowledge tests. Unfortunately, both smile sheets and knowledge tests are often flawed in their execution, providing dangerously misleading information. Yet, without valid feedback, it is impossible for us to know how successful we’ve been in our learning designs. (p. xix)

Many organizations prefer to use available training funds for the development of additional courseware rather than for evaluation of completed programs. This prevents everyone from learning about what works and doesn’t; what’s a smart investment and what isn’t. I guess ignorance truly is bliss.

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What Really Matters

Do people have such confidence their training will attain its goals that no measurement is necessary to confirm it? Or, conversely, could people think it’s so unlikely that any training program is going to be effective, that it doesn’t matter what is done as long as it wraps up on time and budget?

Another possibility: Do people want to avoid the risks in having the impact of their training exposed? If nobody asks or complains, it may be better not to know.

Perhaps the real project goal isn’t to achieve desired learning and performance outcomes. Some sort of formal training, regardless of its effectiveness, will be better than nothing. Perhaps the real reason for implementing the training program might actually be to have the appearance of concern and taking action. Otherwise, employees would complain about the lack of support and clarity of what they’re supposed to do. They’d even have justifiable cause to complain. But by offering a training program—any training program—the burden shifts to the employee. Whew!

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“What do you mean you don’t know how? Didn’t you learn anything in the training we provided? You must not have been paying attention. We go to all the expense of providing you training, and you’re still not getting it? Better get on board fast!”

The likelihood of hearing such a comment is low because an employee would have to be caught not knowing what to do or voluntarily admitting not knowing what to do even after taking training. Most employees are adept at avoiding such exposure. Instead of speaking up, admitting lack of readiness, and enduring the consequences, they duck observation, quietly observe others, and, if all else fails, surreptitiously interrupt coworkers to learn what’s necessary—just enough, at least, to get by and avoid censure.

Poor training is let off the hook.

Informal On-the-Job Training:

A Toxic Elixir for Poor Training

Under the scenario I just presented, formal training is delivered, employ-k

ees appear able to perform, and no one is complaining. Success! Or maybe k

not. Unplanned, possibly even unobserved, informal on-the-job training may be at work here, not just the gratuitous, boring, and, ultimately ineffectual e-learning.

Who’s more eager to learn than people trying to perform a skill, finding they can’t do it, and fearing exposure? The helpful guidance of coworkers is gratefully received in this worrisome situation. It is often effective, at least in terms of assisting with the specific barrier at hand. Unfortunately, providing poor e-learning and then letting haphazard knowledge sharing deal with its ineffectiveness is expensive, slow, and potentially counterproductive—even dangerous. Let’s see why this is so: It’s Expensive

On-the-job (OTJ) training is expensive because you have the costs of two training systems—the e-learning system and the all too often ad hoc, unseen, and unmeasured on-the-job training system. While the costs of e-learning are rather easily identified, including design, development, distribution, and learner time, only distribution costs and learner time are recurring costs. Those costs have become very inexpensive and broadly practical, whether providing access to e-learning is done through local What You Don’t Know Can Kill (Your e-Learning)

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area networks, cloud services; Wi-Fi, hotspots, or wired; on personal computers, laptops, tablets, or even smart phones.

Conversely, unplanned, unstructured on-the-job training doesn’t cost anything for design and development but carries high continuing costs that include coworker disruption and resulting loss of productivity. The learning worker probably receives an incomplete tutorial as well and will have to continue to interrupt others as he or she becomes aware of additional incompetencies. Performance errors and employee frustration are likely and contribute to the high cost of this strategy, which can cause domino effects of unhappy customers, missed business opportunities, disrespect for management, employee attrition, and so on. (See Figure 3.2.) It’s Slow

Surreptitious on-the-job training can be timely but is often inconvenient and slow. It could be that the knowledgeable individual needs to finish a task before providing help on another. Perhaps a

machine has to be shut down and restarted each

time a procedure is demonstrated. The learner

Etc.

stands and waits, perhaps even being distracted

by something to be done elsewhere and then

k

Missed business

opportunities

being detained when learning could resume. The

k

coworker then stands and waits. It’s easy to imag-

Recovery

ine a multitude of realistic, probable causes of

through OJT

scheduling difficulties and inefficiencies. Even

Errors, accidents,

when on-the-job training is planned, many com-

low productivity

panies look for alternatives because of the inher-

e-Learning

ent scheduling difficulties, costs, quality-control development costs

problems, lack of scalability, delays in updat-

ing, and other problems inherent in on-the-job

training.

FIGURE 3.2

Stacked

costs of poor training.

It’s Risky

If all these problems weren’t bad enough, there are dangers that could lead to devastating situations. The learner might not realize he or she needs help or doesn’t want to admit needing it. Keeping incompetency hidden can lead to severe consequences. While caring for you, for example, you don’t want your doctor getting by on hunches, then discovering her errors 34

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and her need for training after the damage has been done. You don’t want an unsupervised first-time Bobcat operator working next to your house or an auto mechanic guessing what’s wrong with your brakes because he doesn’t want to admit his lack of readiness. Trial and error may be a good teacher, but there are costs. If errors are necessary before a worker can get help, errors will have to be made and damages incurred. Even further, if the consulted coworker misunderstands the procedure he or she is helping another with, it’s quite possible misconceptions will be perpetuated, com-pounding error upon error. That’s how bad work habits become part of a corporate culture, and the result is the proverbial blind-leading-the-blind.

Unstructured informal training is a risky remedy for poor training.

Don’t Drink the Kool-Aid

We’ve seen increased interest in learner-constructed content. And I do appreciate instructional strategies that give learners the task of preparing to teach what they’ve learned. But mostly I think this is yet another product of hoping that the hard work of good instructional design can be avoided. Certainly, modern communications capabilities and concurrent authoring tools facilitate collaborative design and development. And as long as a process is provided to validate the subject matter, in some contexts, k

learner-constructed content might indeed be more affordable than engaging k

genuine subject-matter experts and skilled instructional designers (although it seems likely to be more expensive and less impactful in the end).

While recent learners and prospective learners are exceptionally valuable in the process of creating effective learning experiences (something I will detail later with the SAM approach to courseware development), it doesn’t make sense to turn over the reins to those with minimal knowledge of instructional design. We see today the results of too many people working very hard but having no idea how to create performance-changing e-learning. Learner-constructed content shouldn’t take the place of properly executed instructional design.

An Example

Here is a quick example to show that the value of good e-learning instruction can be instantly apparent, while also fun and relatively easy to develop.

The content in this example may be far different from what you need to teach, but consider the instructional strategy for a moment anyway.

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Experience versus Presentation

Suppose you were teaching the fundamentals of finding the epicenter of an earthquake with seismographs. This topic could be taught through some pages of text and graphics—literally a presentation—as shown in Figure 3.3.

But add a question as in Figure 3.4, and it becomes interactive learning, right? Barely.

Locating an Earth Quake’s Epicenter

The three dots show the

location of three

seismograph stations.

Seismographs don't

detect the direction of the

earthquake's center, only

how far away the

earthquake was as

represented by the large

circles.

The epicenter is at the

point where the circles of

all three seismographs

k

intersect.

k

FIGURE 3.3

Page turner.

Locating an Earth Quake’s Epicenter

The three dots show the

location of three

seismograph stations.

Seismographs don't

detect the direction of the

earthquake's center, only

how far away the

earthquake was as

represented by the large

circles.

The epicenter is at the

point where the circles of

all three seismographs

intersect.

How many seismographs are needed to find the

epicenter of an earthquake?

FIGURE 3.4

Page turner with question.

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This interaction invites guessing. There are so many sets of three on the screen that it’s very likely learners would guess correctly without understanding any of the underlying concepts. Truly interactive learning creates an experience that facilitates deeper thinking.

In the design shown in Figures 3.5 to 3.8, learners place seismographic stations on a map, one station at a time, take a reading, and determine from distance data only (with no directionality) how it is necessary to have more than one reading. You can easily see how this would be a better learning experience.

As shown in Figure 3.6, the learner adjusts the radius of circles dynam-ically to match computer-generated readings. This activity reinforces the concept that the seismograph reveals only the distance and not the direction of the epicenter.

In the pedantic approaches we want to avoid, learners would be told outright that three seismographs are usually needed and then asked to remember the number. But in interactive learning, learners can attempt to find the epicenter with just one or two readings and see why another is needed. With that approach, the complete concept is learned and is remembered more easily, as well.

k

k

Locating an Earth Quake’s Epicenter

The three dots show the

location of three

seismograph stations.

Seismographs don't

detect the direction of the

earthquake's center, only

how far away the

earthquake was as

represented by the large

circles.

The epicenter is at the

point where the circles of

all three seismographs

intersect.

The dots represent seismographic stations. Drag one onto the map to place it and check the distance reading. Double click the epicenter of the quake when you know where it was. Otherwise, if you need another seismograph, drag another dot onto the map and repeat.

FIGURE 3.5

Learner activity in an authentic context.

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This seismograph

measured a distance from

of epicenter of:

19 miles

Drag the diamond-

shaped handle to draw a

circle to represent this

radius from the seismic

station.

Double click the epicenter of the quake when you know where it was. Otherwise, if you need another seismograph, drag another dot onto the map and repeat.

FIGURE 3.6

Let the learner play.

Locating an Earth Quake’s Epicenter

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You have readings from

two seismographs now.

Can you tell where the

epicenter is?

I have no idea

It’s at one of two

places I can identify

I know where it is

FIGURE 3.7

Learner experience teaches the principle.

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Locating an Earth Quake’s Epicenter

You have readings from

three seismographs now.

Can you tell where the

epicenter is?

I have no idea

It’s at one of two

places I can identify

I know where it is

Click the map to show

me where it is.

Good. Now, how many seismographs are needed to

find the epicenter of an earthquake?

FIGURE 3.8

Confirming feedback is almost unnecessary.

Once the learner has placed and measured all three seismic stations, it k

is clear how to identify the epicenter.

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It shouldn’t be surprising that the most common learner response to completing this sequence is to try it again. It fosters no end of curiosity: What if I put the stations really close together? What if I put them in a straight line? What if I place one exactly on the distance circle of another station? The interface allows exploration of all these questions, and each answer develops a richer understanding in the learner’s mind.

With capable authoring tools, such as Authorware or ZebraZapps that were used to create this example, active e-learning like this is easy and inexpensive to create; yet, the impact is far greater than just a presentation with or without the ubiquitous follow-up questions.

The Takeaways

It is the intent of this book to share some of the methods, tips, and tricks of accomplishing the primary success goal of all training: getting people to do the right thing at the right time. Just knowing what to do isn’t sufficient and isn’t success unless employees know how and when to do it.

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Because so few organizations measure the impact of their training, regardless of whether it’s delivered by e-learning, they get into a cycle of cutting training costs, not realizing the potentially deleterious effects (unless disaster strikes), and may continue to cut costs when no apparent harm is caused. With so little time and money to work with, training developers feel they can do little but prepare presentation-based instruction that’s admittedly boring and ineffective. The cycle is perpetuated.

Boring instruction is ineffective and ultimately far more expensive than impactful instruction that achieves the success criterion of getting people to do the right thing at the right time. If proper measures aren’t going to be put in place, then courseware at least should be designed with the characteristics that have been proven effective.

There are many proven benefits of good e-learning. They have been measured and are reliably reproducible. While we may try to avoid the work of good instructional design, it is clear that alternatives have major, costly risks, such as being slow, expensive, and inaccurate. Effective instruction is always less expensive than instruction that doesn’t work.

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Chapter 4

Making Success

Possible

It is surprising how many e-learning programs have no chance of success when you look closely. The reason might surprise you. It often has nothing to do with the programs themselves, but rather the failure to scrutinize the training and performance context and take it into account during design. Among the factors that determine training and outcome k

performance success of a program are:

k

• Who participates in the design of the training

• What resources are available for training design and development

• Who is being trained and for what reason

• Instructional delivery media and instructional paradigms used

• Learning support available during training

• Performance support and guidance available after training

• Rewards and penalties for good and poor performance, respectively This chapter considers the importance of learning and performance contexts. It starts by examining the prerequisites for success and then discusses the role of good design as the means to achieving success.

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Unrecognized Contextual Factors

Failed training programs can often be attributed to a number of contextual conditions that prevent their success. The barrier might be an environment that actually inhibits desired performance. It’s not uncommon. It could be training solutions were developed without the essential perspective of employees and their supervisors. And it could easily be the influence of many other contextual factors that can make or break a training initiative.

Even worse, costly instructional failures may go unrecognized for some time. Imagine this scenario: Everyone responsible for launching a training program may have reveled in that achievement and the announcement of the programs’ availability. Likely, they received congratulations from those who recognized that the development and deployment of a new training program was a major undertaking. News that trainees liked the new programs and gave positive feedback validated the cause for celebration. All is well, right? Not necessarily.

Even though trainees may appreciate the excuse to escape the usual work routine and to enjoy doughnuts in the learning center along with the good humor of the instructors and staff, organizations can be surprisingly k

slow to realize their instructional programs are not performing as well as k

they should, could, and need to. So many opportunities may have slipped by unnoticed. So much money might have been saved. So much more might have been earned. It’s unfortunate training simply doesn’t get the attention it needs, and that even training developers underestimate what they could do for their organizations. Listen up, executives!

Change Is Necessary

There are many reasons e-learning or any training solution can fail. We must objectively assess the context for a learning solution to identify the real barriers to success. Having done that, it is very likely e-learning designers and developers can affect some changes that will improve the chances of success.

If we’re talking about employee training, for example, employees may not be doing what management wants because doing something else is easier and seems to be accepted. In this context, training focused on teaching how to do what management wants done may have absolutely no positive effect. Employees may already know full well how to perform tasks in the 42

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manner desired, but they simply choose not to do so. The performance context needs to change. And in this situation, further training won’t make a difference.

Prerequisites to Success

An exhaustive list of e-learning success prerequisites is probably not possible because so many factors can undermine an otherwise thoughtful and well-executed plan. The items in the following list may seem to be rather obvious requirements; yet, inaccurate assumptions are often made about them:

• Performer competency is the problem

• Good performance is possible

• Incentives exist for good performance

• There are no penalties for good performance

• Essential resources for e-learning solutions are available It is not rational to ignore any one of these prerequisites and still hope k

for success, so let’s look closely at each one.

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Is Performer Competency

the Problem?

It is crucial to investigate business problems and define them clearly if any proposed solutions are likely to address and solve them. Underlying causes of performance problems can be hard to identify. Perhaps this is because decision makers are too close to see them or performance problems and suspected causes are too hard to face. Without good analysis, the wrong problems are often targeted because they seem obvious. But, then the real problems persist, ill-defined and unsolved.

Throw Some Training at It

It can be comfortable, even reassuring, to conclude that training is needed in the face of a wide range of problems. If we conclude a problem is really a training issue, no one needs to be culpable for the root cause of Making Success Possible

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that problem. The prospect of a new training effort can paint enthusiastic pictures of future, problem-free performance. With high expectations, but inadequate analysis of the context, training programs are launched that have very little, if any, prospect of solving the real underlying problem.

True Stories—Misguided Training

One client asked us to build a program to teach flight attendants how to perform preflight safety checks. This seemed like a very appropriate use of e-learning.

We began analyzing the performance context and found some unexpected circumstances.

The objective of the training was really not to teach people how to perform safety checks (which is an easy process of following the instructions in the flight manual)—it was to get people actually to do them.

You see, manuals with comprehensive checklists are provided to flight attendants. Even without training, almost anyone could use the manual and perform well. But the manual is thick and heavy to cover many aircraft configurations and provide specific checklists for each attendant’s assigned position.

When experienced flight attendants weren’t seen carrying their manuals, k

less-experienced attendants are eager to shed theirs as well. As a result, the k

checklists were not always readily available, and preflight safety procedures were not properly performed.

Performer competency wasn’t really the problem at all. Everyone could use the manual and perform the safety checks with 100 percent proficiency. Trying to teach these skills again was not the solution.

Together, we worked out what I think was an ingenious solution that demonstrated the consequences of not performing preflight safety checks.

The error, however, is probably not what you’re thinking. It may actually be quite correct that people do need training for ill-defined problems.

Because the preponderance of business challenges involve human performance, a blind guess that training is needed may be correct more often than not.

But the error is likely to be in deciding who needs training on what.

For example, it may well be that supervisors of ineffective performers need training so they can more successfully draw out the desired performance from their already capable teams. Or it may be that ineffective performers 44

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need to learn and use helpful reminders as to when they need to perform specific skills they already possess.

Nonperformance Problems

From starting and running a number of business myself, I know businesses face many problems. It seems there is a new challenge every day: higher costs than expected, slow receipts, telecommunication breakdowns, and so on.

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Training Has Its Limits

A question: With training, you can solve business problems not emanating from employee performance. True or false?

Sorry, you’re wrong. It was a trick question. The correct answer is

“sometimes.”

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Here are the two reasons you can sometimes but not always solve business problems with training even though the problem doesn’t appear to emanate from employee performance:

1. Most nonperformance problems, on closer inspection, do include some performance issues.

2. Not all performance issues can be solved with training.

In most cases, both of these conditions exist simultaneously.

The main point here is that training is a more broadly applicable solution than it may appear, but not a panacea. Of course, training isn’t a good solution when there are no performance issues or when all players are fully capable of the desired performance. But even in these instances, think carefully. Are all players capable of the desired performance? Who are all the players? Training sometimes needs to be offered to suppli-ers, customers, buyers, and others. Think through the whole process and everyone who touches or is touched by the process. Again, it’s very important to assess the situation accurately—the whole situation. (See Table 4.1.) When you do, different answers may emerge.

On the one hand, I often have clients planning a training solution when k

the problem doesn’t appear to be a performance problem at all. They k

aren’t aware of the true source of their problem, and the training solution they seek will be for naught. If the proposed training doesn’t address the source of the performance problem, it will be ineffective, no matter how good the instructional design and implementation are.

On the other hand, nearly all business problems are performance problems, at least in part. We must carefully examine performance problems to determine the root cause, or more likely, the root causes. It is likely that TABLE 4.1

e-Learning Opportunities

Nonperformance Problem

Performer

Performance No Internal

Hidden

Competence Problem

Performance

Performance

Issues (really) Issues

Competent

Consider

Consider process

Consider problem-

performers

supervisor

revision and

solving training

training

related training

Incompetent

Performer

Consider

Consider client or

performers

training

customer, client,

vendor supervisor

or vendor training

training

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part of a good solution will be training. Generally, the questions are whose performance is the problem, and who needs training?

Just Do It—It’s Easy

It is easy to go wrong, especially when not taking the performance problem seriously. Sometimes it seems just making an effort will solve problems. An executive order to put a new training program in place may set expectations that problems will soon vanish. How hard can it be? But these bubbles are destined to burst, probably after some sincere hard work on the part of the training team fighting against restrictive budgets and time lines. Those receiving the blithe order to go forth and train are set up to misunderstand what’s really important for success. Is it to improve performance and bolster the bottom line? Or is it to entertain employees, present fascinating facts, and free them from their daily routines for a moment? Two different things. It can be hard to accept as trainers, but sometimes management really wants the latter. Or maybe they don’t know what they want.

Training development is never easy and success is never a given. But k

when the goal hasn’t been defined, success is a miracle. If you don’t know k

what success looks like, you’re pretty unlikely to achieve it. Flailing about in endless meetings and planning documents doesn’t make it easier; it just spends time and energy.

Disguised Competency Problems

Many business problems not obviously amenable to training solutions can actually be addressed through e-learning, at least in part. When we consider such significant problems as undercapitalized operations, outdated product designs, unreliable manufacturing equipment, noisy work environments, poor morale, bad reputation, and so on, is training really a solution? You may be surprised to hear that training should not be ruled out too quickly.

Although many factors determine the possible success of any enterprise, what people in that enterprise do, and when they do it, is the primary factor. If training can help change what people do and when they do it, then one component of almost every solution might well be training. Consider the following possibilities:

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Undercapitalized operations. Finding more money might not be the only solution nor the best solution. Achieving new levels of efficiency, offering better service, or redefining the business model to match available resources may be better solutions with or without new money, and all of these solutions to some extent require people to change what they’re doing.

If squeaking by without additional funding is the chosen route, it often means having fewer people covering more bases. To be successful in that scenario, the remaining employees need to learn how to handle a greater variety of tasks; just as important, they also must understand why they need to take on so much responsibility and what can be achieved if they manage well.

Successfully squeaking by can be a business triumph if customer service is strong and customer loyalty is maintained. Could effective training separate the competitive winners from the losers in your field when times are tough?

Outdated product designs. How did this happen? Were people not tracking technologies, markets, or competitors? Did they know they were supposed to? Did they know how? Are they able to design better products?

Perhaps some training is needed—the sooner the better.

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Unreliable equipment or tools. Is equipment purchasing ongoing? If so, do buyers know enough about your processes, needs, and cost structures to know the difference between a smart buy and a low price tag? If you’re stuck with the equipment you currently have, are there effective tricks or precautions known only by a few, maybe only by those on the night shift or by a few silent employees, that could be learned by others to make the most of your equipment’s capabilities? This could be a training opportunity.

Poor morale. Poor morale isn’t really a condition, it’s a response. It can stem from a wide variety of problems or perceptions. At the heart is often lack of understanding of the company’s mission and goals, lack of communication, lack of trust, or conflicting agendas. Some good coaching and team-building exercises are probably needed. e-Learning may be helpful in some of these situations, but it’s more likely to be helpful in ongoing measures that energize the workforce and safeguard against chronic morale problems. For example, the corporate mission can be communicated in ways that lead not only to knowledge of the mission but also to energetic participation and voluntary endorsement of the vision. e-Learning can help managers learn more effective ways of encouraging spirited contributions through listening, feedback, and appreciated incentives. Often improperly and narrowly viewed as a vehicle limited to the transfer of k

knowledge and skills, e-learning might overcome a lack of insight and k

nourish a sense of pride that restores or helps maintain the essential health of your entire organization.

Turnover and absenteeism. People don’t feel good about themselves when they aren’t proud of their performance. They may be getting by, perhaps skillfully hiding their mistakes and passing more difficult tasks to others, but it’s hard to feel good about yourself when you can’t do well. As a result, it’s hard to get to work, and one is constantly on the lookout for a more satisfying job. With the ability e-learning has to privately adapt the level of instruction to each learner’s need, it might just be a solution to problems of turnover and absenteeism.

Tarnished reputation. Why does the organization or product have a bad reputation? Are deliveries slow, communications poor, or errors frequent?

In the outstanding book Moments of Truth (1987), Jan Carlzon shows how successful companies focus on the customer, the front line employees, and the interactions among them that define their respective companies through “moments of truth.” In an effective organization, “no one has the authority to interfere during a moment of truth. Seizing these golden opportunities to serve the customer is the responsibility of the front line.

Enabling them to do so is the responsibility of middle managers” (Carlzon 1987, p. 68). But how do those on the front line know how to serve the Making Success Possible

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customer? How do middle managers know how to support and guide the front line? Through e-learning? It’s a possibility.

Until a problem is identified and framed as a competency problem, e-learning is not the solution. The types of problems just listed are not the ubiquitous problems for which training is an obvious solution. They are listed to underscore the widespread, multifaceted nature of performance problems and the often unsuspected value e-learning can bring to corporations and organizations of all kinds.

Few problems are devoid of human performance difficulties, and, generally, few solutions without a high-impact training component will be as effective as those with it. Still, identifying the real problem is a prerequisite. Guessing about the problem is unlikely to lead to effective solutions.

If e-learning is going to work, it’s necessary to determine clearly what the performance factors are and what is preventing optimal performance from happening. The problem may well lie in one of the contextual inhibitors in the previous list.

Good Performance Is Possible

It doesn’t make sense to train people to do things they can’t do. And train-k

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ing is offered with surprising frequency in situations where:

• There’s rarely a case where the new skills would be preferred by customers or supervisors.

• It would take too long to complete a process if it were done by the book.

• Appropriate situations occur so infrequently that it’s unrealistic to expect any trainee to retain skills between opportunities to use them.

I know that it seems too obvious to be included in this list of essential preconditions for successful e-learning, but there have been many times our consultants have looked at one another, shaking their heads in frustration, because they have realized that no matter how good the proposed training may come to be, trainees will not be able to live up to management’s expectations. Without changing the performance context, the desired behavior is not going to happen.

While it seems like common sense, it’s worth mentioning that training does not make the impossible possible or the impractical practical. Good performance needs to be a realistic possibility before e-learning has the potential to help.

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True Stores—Ridiculous Expectations

We once had a client, a major U.S. corporation, wanting us to train the company’s many account reps on the details of more than 100 insurance plans. The problem was that each agent generally stuck to selling only about six different plans—the plans with which they were most familiar.

Although agents could remember the details of a half-dozen plans and could therefore answer questions correctly, place orders quickly, and show at least some flexibility, there was also a good possibility that other plans were a better fit for clients’ needs. To be more competitive and more profitable, the company needed to have its agents consider the full range of products. The solution?

“Train our agents to know all of our products.”

Who could possibly remember the major characteristics of more than 100 different insurance plans, let alone the details of each? Well, nobody could—at least nobody with less than a decade or so of experience. It wasn’t realistic to solve this problem through training alone.

The solution? We developed a performance support system to help agents work with all plans by prompting agents in real time to ask clients selected questions.

This could be done when agents were talking on the phone with clients. When on site, clients and agents could work together to answer questions on laptops.

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After agents narrowed the possible fit to a small number of policies, they could access training on the appropriate class of policies. Agents were eager to learn at this point, content to be learned was minimized, and the tasks taught were possible to perform.

Incentives Exist for Good

Performance

Although the reasons aren’t always obvious, behavior happens for a reason.

People turn up at work for a variety of reasons, but it’s safe to assume that most would not appear if they were not paid.

Many people receive a fixed amount for the hours they work. They will not make more money immediately if they do a better job, and they will not receive less, unless they are fired, for doing a poorer job. So, for these people, pay is an incentive for being present and for doing a minimally acceptable job—and not much more than that.

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Fortunately for employers, other incentives exist:

• Approval and compliments

• Respect and trust

• Access to valued resources (tools, people, a window with a sunny view)

• Awards

• Increased power and authority

• More desirable or interesting assignments

Because these incentives occur in response to desired behavior and are usually offered in a timely, reinforcing manner, they can and do affect behavior in profound ways. If valued incentives exist for desired behavior, training that enables such behavior is likely to be successful as well.

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Incentives Run Amok

A partnership between management and

Management

Training

training is critical for success (see Figure 4.1).

Management’s role is to provide a learn-

ing and performance context that results in

Willing &

Able

a workforce willing to do what needs to be

done, in the way it needs to be done, and

when it needs to be done.

Training is responsible for enabling will-

FIGURE 4.1

Partnership of

ing workers to do the right thing at the right

responsibilities.

time, to see opportunities, and to be

effective and productive. The outcome is a

win for both through a willing and able workforce.

When incentives do not exist or rewards are given regardless of behavior or achievement, personal goals take precedence. For many—certainly and thankfully not all—goals that drive behavior may become:

• Reduced effort (doing nothing or as little as possible)

• Increased free or social time

• Limited responsibility

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• Little accountability

Management may complain that employees are uncooperative, unprofessional, or in some way the cause of operational failures. Seeing this as a performance capability problem, management might jump quickly to ordering up new training. Unfortunately, skill training for employees who lack incentives to perform well makes little, if any, impact.

Use Training to Fix

the Performance Environment

By the way, e-learning can be used to improve the performance environment when positive incentives are absent:

• Consider training managers on how to motivate employees, seek input, build teams, or provide effective reinforcement.

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• Consider providing meaningful and memorable experiences through interactive multimedia to help employees see how the impact of their work determines the success of the group and ultimately affects their employment. (Please refer to Chapter 9 to understand how e-learning design can affect motivation.)

These solutions may be the most cost-effective means of getting the performance you need, and they will dramatically increase the effectiveness of training you subsequently provide performers working in the improved environment. Remember, of course, that you will still need to provide incentives for the people who receive training on providing incentives, or this training will also fail.

Blended Training Solutions

Consider these, also: Blended training solutions that combine e-learning with classroom instruction, field trips, laboratory work, or whatever else can be made available. These kinds of solutions can provide face-to-face interaction and the nurturing environment of co-learners. Many believe the learning process is fundamentally a social process. Observing others, explaining, and questioning can all be very helpful experiences when k

learners are working in close proximity and at similar levels, have time k

scheduled for learning together, and are as concerned with depth of knowledge as developing proficiency as quickly as possible. In general, however, this is more of an educational model than a training model.

Nevertheless, just as it is important to provide incentives and guidance for job performance, it is also important to provide encouragement and support for learning. A well-nurtured learner is going to do much better with e-learning or any other learning experience than an isolated, ignored learner. Learning is work (although with well-designed learning experiences, people don’t mind the work—even if they should happen to notice it). Incentives, rewards, and recognition facilitate better learning just as they do any other performance.

Blending e-learning used to be more necessary than it is today, because computers and other instructional media were expensive and difficult to provide. Good interactivity was difficult to build, and media were often slow and of low fidelity. But these barriers have been overcome.

Blended training solutions are once again in vogue. The reason these many cases is e-learning is poorly designed. Adding more human interaction to the experience is a means to overcome some of the failure. The cost of poor design easily leads to more costs to compensate.

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e-Learning isn’t the best solution for all learning needs. Few would argue that human interaction isn’t highly desirable in support of learning, but it is unfortunate to turn to blended learning as a cover-up for poor e-learning. Many of the advantages of e-learning are lost in blended solutions, including scheduling flexibility, individualization of instruction, and low-cost delivery.

Blended solutions can be great. When done well, they can accomplish what no single form of instructional delivery can achieve by itself. When done poorly, they stack e-learning failures on top of the disadvantages of other forms of instruction—and that’s not a win.

There Are No Penalties for Good

Performance

We haven’t discussed avoidance of penalties as an incentive for good performance, although it is a technique many organizations rely on, even if subconsciously. Penalties are more effective in preventing unwanted behaviors than in promoting desired ones, but, over the long haul, they k

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are weak even in doing this. Further, the burden of penalty avoidance (hiding out) saps energy and creates a negative atmosphere.

Although combined use of penalties (even if just words of disapproval) and positive incentives (even if just words of encouragement) is sometimes considered the most effective means of controlling behavior, employees will be drawn to work environments in which positive rewards are the primary means of defining desired behavior. They will tend to escape environments in which censure is prevalent, whether deserved or not.

The worst case, of course, is one in which there are penalties for desired performance. Although it may seem absurd that any work environment would be contrived to penalize desired performance, it does happen. In fact, I can—and, unfortunately, feel I must—admit to having created just such an environment at least twice myself. I offer an account here as both evidence that this is easier to do than one might think and as a small atone-ment for past errors.

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True Stories—Unwitting Penalties

It’s easy to think there wouldn’t ever be penalties for good performance. But it’s quite easy to penalize just what you want without realizing it.

I was privileged to lead efforts at Control Data Corporation, where major e-learning tool development was undertaken (including the invention of PCD3

and PLATO Learning Management systems) and the research that led to Authorware was conducted. I had some of the most talented and capable researchers and engineers reporting to me. I’m very proud of the achievements of these people. As we worked together, I felt we were truly accomplishing some pioneering efforts that would have worldwide impact.

The feeling that we were doing something very important, if not actually noble, motivated us to work long hours and at the top of our abilities. People contributed fantastic ideas. So many of them led to other ideas, and I was almost euphoric with all of them swimming in my head.

One day, one of my most valued employees made an appointment to talk with me at lunch. While it was customary to conduct business over lunch, the formalism in making the appointment and the unstated topic indicated something was up.

With a nervousness I had never seen in him, he hesitatingly told me that I was penalizing people for their good ideas. Because I saw each idea as a gateway to k

another idea, I immediately wanted to explore all the things we might build on the k

original insight. He needed to help me see how people thought I didn’t appreciate their contributions—that it appeared I wasn’t happy with what they contributed and that the ultimate goal would have to be even beyond what they had envisioned.

I was unwittingly punishing the very performance I felt blessed with. I couldn’t have been happier with what everyone was doing. I appreciated every idea. In truth, I did see many of them as steppingstones and hastily appraised them in that context. As a result, my teams wanted to contribute less, although that was thankfully in conflict with their personal and professional goals, and they didn’t hold back despite their feelings. We needed a better working environment—one that didn’t penalize desired performance.

The people on my team didn’t lack skills, but if they had, training them wouldn’t have fixed the problem. Training me might have. I unfortunately received similar feedback some years later during the development of Authorware. It has taken me a long time to develop better skills at managing teams, and I’m sure many of my employees would suggest I’ve still a long way to go. They’re right. But I hope I’m doing more these days to reward great performance and less to punish it. In any case, if great performance is punished, even when subtle and unintentional, it will counteract the benefits of e-learning. This is an important message to take to heart.

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Essential Resources

for e-Learning Solutions Are

Available

Design and development of good e-learning is a complex undertaking. It requires content knowledge and expertise in a wide range of areas, including text composition, illustration, testing, instruction, interactivity design, user interface design, authoring or programming, and graphic design. It’s rare to find a single person with all these skills, and even when such a person is available, training needs can rarely wait long enough for a single individual to do all the necessary tasks sequentially. Forming design and development teams is the common solution, although teaming introduces its own challenges. (Chapter 11 identifies those and presents some process solutions.) What is essential in teaming approaches, however, is that all necessary skill and knowledge domains be present and available when they are needed.

Not the Usual Suspects

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Making sure all the needed participants are available and involved is not only a coordination problem but also a problem of understanding who needs to be involved. For example, while everyone understands that subject-matter expertise is required, few executives see themselves involved in e-learning projects beyond sanctioning proposed budgets. But executives are presumably owners of the vision from which organizational goals and priorities are derived. e-Learning provides the means for executives to communicate essential messages in a personal way that can also ensure full appreciation of the organization’s vision, direction, and needs.

So it’s a major missed opportunity when executives have no involvement.

e-Learning can truly help all members of any organization understand not only what they need to do, but also why it is important. Check Table 4.2 for suggestions on who needs to be involved when.

The more sophisticated the instructional design, the more likely it is that great amounts of time and money will be wasted if creators lack a full understanding of the following elements:

• Content (facts, concepts, procedures, causes and effects, etc.)

• Characteristics of the learners

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• Behavioral outcomes that are necessary to achieve success

• Specific aspects of the performance environment that will challenge or aid performance

• Organizational values, priorities, and policies

In short, a lot of knowledge and information must guide learning design and development.

“Watson—Come Here—I Want You”

People must be available, not just documents. Other than having a too-shallow understanding of instructional interactivity, perhaps the biggest problem corporate teams have in producing high-impact e-learning applications is the lack of sufficient access to key people.

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TABLE 4.2

Human Resources Needed for e-Learning Design

Executives

Why

When

The vision and business need must guide

At project definition to set goals

development. As projects are designed,

At proposal evaluation to weigh

opportunities arise to question and more fully

suggestions and alternatives

define the vision—always strengthening,

During project design for questions and

sometimes expanding, the contribution of the

selection of alternatives and priorities

training. Executives also need to see that

During specification of criteria and

post-training support is provided.

methods for project evaluation

Performance Supervisors

The people to whom learners will be responsible

At project definition to evaluate and

need to share not only their observations of

propose alternative goals

performance difficulties and needs, but also need

During project design for questions and

to help identify what will motivate learners and

selection of alternatives and priorities

prepare post-training incentives and support.

During the specification of criteria and

methods for project evaluation

Subject-Matter Experts

Unless the instructional designers are also

Throughout the instructional design

subject-matter experts, designers must have

process, beginning with prototypes and

articulate experts to help define what is to be

later for content scope determination

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taught and to ensure its validity.

and reviews

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Experienced Teachers

If the content has been taught previously, those

Throughout the instructional design

who have taught it will have valuable insights to

process to help sequence content and

share. They will know what was difficult for

suggest interactive events

students to learn, what activities or explanations

helped or didn’t help, and what topic sequencing

appears to be best.

Recent Learners

Recent learners are often the most valuable

During rapid prototyping, content

resource to instructional designers. Unlike experts, sequencing, interactive event

recent learners can remember not knowing the

conceptualization, and early evaluation

content, where the hurdles to understanding were,

of design specifications

and what helped them get it.

Untrained Performers

It’s very important to test design ideas before

During evaluation of second- and

e-learning applications have been fully built and

later-round prototypes through to final

the resources to make extensive changes have

delivery

been spent. Because you can only be a first-time

To add fresh perspectives, different

learner once, it’s important to have a number of

performers will need to be added to the

untrained individuals to evaluate alternate

evaluation team as designs evolve.

instructional ideas as they are being considered.

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“Now!”

It is important not only to have the right people available but also to have them available at the right time. A great many interdependent tasks are scheduled during the development of e-learning applications. They are far more complex than you can imagine if you haven’t yet been part of the process. If people are not available for needed input or reviews, it can be very disruptive, expensive, and ultimately damaging to the quality of the final product.

“Never Mind—We Have the Manual”

Repurposing is a term used to put a positive spin on some wishful thinking.

It’s the notion that existing materials, designed for another purpose or medium, can be used in lieu of having more in-depth resources available for e-learning development. It sounds like an efficient if not expedient process to take existing material and turn it into an e-learning application, like turning a toad into a prince. It seems particularly attractive because key human resources, people who are always in high demand, would not be needed very much. The team members can just get the information they need from the documents, videos, instructor notes, and other materials.

Sorry. It’s a fairy tale.

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Noninteractive materials are far too shallow to supply sufficient knowl-k

edge for e-learning design. You’ve heard the adage, “To really learn a topic you should teach it.” Preparation for teaching a subject requires much more in-depth knowledge and understanding than even the best students can gain from just reading documentation. e-Learning approaches vary from timely e-mailed messages to fully interactive experiences incorporating dynamic simulations. But even the simplest form of interactivity tends to reveal lack of depth in the author’s understanding.

Repurposing is essentially a euphemism, because without additional content, in-depth knowledge, and the design work necessary to create appropriate interactivity, repurposed material quickly turns into boring electronic page turning. Any plan, for example, to take a manual and turn it into an effective e-learning application without the involvement of people knowledgeable in the subject, input from those experienced in teaching the subject, and guidance from managers of the target audience is, if not doomed to failure, going to be far less effective than it could be. And, perhaps worse, the faulty applications produced may lead to the erroneous conclusion that effective e-learning solutions don’t exist, are too expensive, or are too difficult to build.

As you can see from Table 4.3, the content to be created for effective instructional interactivity reaches far beyond the information available in noninteractive resources. Much of the design work requires in-depth 60

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TABLE 4.3

Repurposing Content vs. Designing Interactive

Learning

Repurposing

Designing for

Interactivity

Initial analysis

Existing materials

Performance needs

Design focus

Clear content presentation

Meaningful, memorable, &

motivational learning experiences

Additional

Little or none, depending on quality

Extensive, including examples, and

subject matter

of existing materials

likely performance errors and their

resources

consequences

required

Materials to be Content presentations structured Motivational content to prepare

created

for computer screen presentation,

learners to learn, learning events

transmission, and compatibility

carefully structured from CCAF

with delivery devices

components, and logic to select

appropriate events for each learner

Product

Page-turning application, possibly

Highly interactive, e-Iearning adaptive

potential

with shallow interactions or quizzes

to learner abilities, readiness, and

needs

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content knowledge—more than can be gained from careful study of materials designed for declarative instruction.

In listing essential resources, it may indeed sound as though all e-learning applications are tedious and expensive. This isn’t true, but just as any organizational initiative should be guided by people in the know and with experience, it would be an error to attempt e-learning without the expertise needed to direct the effort.

Why Do We Do Things That

We Know Are Wrong?

In outlining the contextual prerequisites for success in the preceding section, I worry that I’ve made an important mistake. I think the reasoning is logical; yet, organizations repeatedly do things to sabotage the success of their investments in e-learning. My mistake may be twofold: (1) assuming that organizations will change their behavior if a better path is identified and (2) assuming that the overall success of the organization k

is the primary goal of individual decision makers.

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The reality may be more like this:

• We like a bargain. “We don’t like the costs we’re hearing for good e-learning applications. If we can get an e-learning project going with minimal investment, at least we won’t be completely behind the times—and who knows, maybe something really good will come out of it. I love getting a real bargain.”

• Our people are smarter than others. “We don’t need to baby our people with all this learning rigmarole. Just get the information out to them, and they’ll do the rest.”

• It’s not really this complex. “I was a student once, and sure, some teachers were better than others. But pretty much anybody with a few smarts can put a course together.”

• Being conservative makes me look good. “I play it conservative. We don’t need Cadillac training, and I sure don’t want to be seen as throwing money around. I save a little, and we get some training. It might be mediocre. But who knows? Everybody argues about 62

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training anyway, no matter how much we spend. So I look interested and keep the costs to a minimum.”

It’s tough to fight such mentalities. The truth remains, however, that astute use of e-learning provides a competitive advantage. Many companies have completely changed their views of training. Whereas they once saw it as an unfortunate burden, they now see it as a strategic opportunity.

They hope their competitors won’t catch on for a long time.

How to Do the Right Thing

It’s easier to point out errors than it is to prescribe fail-safe procedures.

There’s no alternative I know of to strong, insightful leadership. But a short checklist of the right things to do with respect to e-learning would include:

❑ Define performance needs clearly and specifically.

❑ Measure current levels of proficiency.

❑ Determine what is motivating current behaviors.

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❑ Make sure desired behavior is possible and reasonable.

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❑ If appropriate, launch a training development effort to:

• Make needed knowledge resources available.

• Determine what’s most important to achieve and what the benefits will be.

• Look at ROI, not just expense, in determining your budget.

• Use designers and developers who have portfolios of excellent work.

• Define changes to the work environment that will reinforce learning experiences and sustain them.

❑ Develop a supportive environment that recognizes and rewards good performance.

❑ Keep alert for the kind of rationale that supports doing the wrong things.

❑ Stay involved.

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Design—The Means to Success

We’ve seen the importance of the design context for achieving training success and performance goals. Some errors are made by not using e-learning when it really could be of help. In other cases, training could not solve the problem, regardless of the approach taken. Finally, e-learning development, if it could otherwise be successful, is often held back by lack of access to critical resources.

When all the external factors are in place, we’re just getting ready to start. The challenge ahead is that of designing and developing a high-impact e-learning application. This is where the return on the investment of resources will be determined.

In a process something like peeling away the layers of an onion, we will work down to the nitty-gritty details of design. We start first with questions of how good design happens.

e-Learning or Bust

There has been an enthusiastic rush toward e-learning recently. The pio-k

neering efforts in computer-based instruction of the 1960s demonstrated k

the feasibility of outstanding education and training success, whereas e-commerce has fostered today’s expectation that electronic systems will be a primary component of nearly all learning programs in the future.

People no longer wonder whether e-learning is viable but, rather, how to convert to e-learning most expeditiously.

There probably isn’t enough concern or healthy skepticism. It’s good if you are concerned about all this e-learning commotion. I’m there with you. I think it is good to be concerned because much (probably most) e-learning is nearly worthless. Just because training is delivered via computer doesn’t make it good. Just because it has pretty graphics doesn’t make it good. Just because it has animation, sound, or video doesn’t make it good. Just because it has buttons to click doesn’t make it good.

Excellent design is required to integrate the many media and technologies together into an effective learning experience. Excellent design isn’t easy.

Quick and Easy

Multiple approaches to developing e-learning have been advocated over the years, and elaborate systems have been developed. Some have tried 64

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laying out more simplified cookbook approaches providing step-by-step recipes for design and development of learning applications. Although all of them have provided some good ideas, the task continues to prove complex, as evidenced by the plethora of short-lived and little-used applications. Paint-by-number solutions just don’t hack it, although you wouldn’t know that from the number of people who promote them.

There is undying optimism that just around the corner is an easy way to create meaningful and memorable learning experiences that swiftly change human behavior, build skills, and impart knowledge. I emphatically do not share that optimism. We don’t have automated systems producing best-selling novels or hit movies. Developing engaging interactivity is no less of a challenge. In some senses, I see it as a greater challenge.

Clearly, tools will advance, and we will have more flexibility to try out alternatives. Our knowledge will advance, many alternatives will become more successful than they are now. More powerful tools will help us evolve initial ideas into very successful applications more quickly. And perhaps, way down the line, computers will be able to create imaginative learning experiences on command. We’ll just access a database of knowledge, provide information about ourselves (if the computer doesn’t already have it), and indicate whether we want to study alone, with others nearby, or with k

others on the network. The computer will configure a learning experience k

for us, and voilà—there it will be! But not today.

Learning Objects

In the excitement of both e-learning’s popularity and our compelling visions of the future, many have been working to create approaches, if not enterprises, that expeditiously solve today’s problems and meet fore-seeable needs. They hope to develop the primary catalyst that will bring it all together.

One instance of this is the concept of templates or reusable learning objects (RLOs). An RLO (see Table 4.4) is a small “chunk” of training that can be reused in a number of different training settings. RLOs are a speculative technical solution to reduce development costs. They address development and maintenance issues, and when used selectively and judiciously, they can speed up not only development, but design as well.

But because RLOs can have design and implementation details worked out and therefore greatly speed up overall creation of e-learning applications, there’s a temptation to let available RLOs limit, if not dictate, instructional possibilities. Ironically, design choices limited to available Making Success Possible

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TABLE 4.4

Reusable Learning Objects

Characteristic Pros

Cons

Reusability

RLOs can be reused in

Difficult to design training that will

different training situations.

have the desired impact if RLOs are

made generic for reuse and

independent of context.

Standard structure

RLOs are easier to use and

Less flexible; instructional design is

more reliable when fully

limited to the structure’s options

debugged; lead to more

and capabilities.

rapid development and

sometimes even better

designs than authors might

create.

Maintainability

Using RLO templates and

RLOs may have unnecessary

databases to store objects

overhead and complication

makes content easier to

compared to a simpler,

update, maintain, and

custom-built function providing

translate.

only what is needed.

RLOs can become more difficult and tedious than using a modern authoring system to build exactly what’s called for. Authors can become more k

fixated on maximizing the use of RLOs than maximizing the impact of the k

learning experience.

This is not to say RLOs are bad. In the hands of a professional instructional designer, who uses RLOs only where they are fully appropriate and avoids the temptation to compromise learning experiences just because fitting RLOs aren’t available, RLOs can provide an invaluable way to reduce the time and expense of creating excellent e-learning applications.

There’s a bit of a conundrum with RLOs or authoring by selecting a template and populating it with content. For example, very small RLOs would seemingly allow the greatest flexibility and applicability. They can be used almost everywhere. But because they are small, they carry minimal relevance to specific instructional contexts and are therefore instructionally weak. Please remember, a strong context is needed for maximum performance change. Context-neutral templates are generally undesirable learning objects, regardless of the number of times they might be reused.

Small and context-neutral objects must be assisted by other structures, RLOs and/or custom structures that build on context. And this means authors can be taken off task by trying to assemble and integrate RLOs to create the whole of a learning experience, while trying to avoid an encumbered patchwork that may be difficult to use and maintain.

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High

Breadth of RLO Utility

Applicability

Low

Low

Context Specifity of RLO

High

FIGURE 4.2

Specificity of RLOs versus applicability.

Conversely, larger RLOs, especially those embracing the specific nuances of content and context, can provide essential learning activities and offer great utility while working within the supported context but need considerable revision when used in alternative contexts (Figure 4.2).

Larger RLOs tend to work against the fundamental purpose of RLOs across contexts, but can provide outstanding utility within the domain for k

which they were created.

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Is lowering the quality of e-learning a fair trade-off to ease design, development, and maintenance? No. Simply said, poorly designed training is of little value, whether it’s easy to author and maintain or not.

Intrigue, challenge, surprise, and suspense are valuable in creating effective learning experiences. The drama of learning events is not to be overlooked when seeking to make a lasting impression on learners. Just as we have not yet seen automated ways to create such elements in other media, it will be a while before e-learning evolves to automated creation.

We still need to develop a greater understanding of interactive learning before we attempt to make courses by either automation or assembly-line production.

That said, RLOs have a valuable role to play in today’s professional e-learning toolbox. While small, general RLOs can be used for such util-itarian functions as recognizing learner gestures, presenting options, and showing progress, more complex, content-specific RLOs can be used when repetitive complex interactions serve as the basis for performance practice.

The smaller RLOs provide utility across many content domains, while the larger RLOs provide development and maintenance advantages within a defined domain.

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Art or Science?

A fascinating debate has carried on among our industry’s most knowledgeable and respected leaders and researchers. The debate concerns whether instructional design is, or should be, approached as an art or a science. If based on science, then it should be possible to specify precise principles and procedures, which, when followed properly, would produce highly effective e-learning applications every time. If instructional design is an art, then procedures remain uncertain, effective in the hands of some, who add their unique insights, but ineffective when used by others. It’s a lively debate in my mind, and I find myself in the frustrating position of agreeing with both sides wholeheartedly on many of their respective arguments.

I come out centered securely on the fence, uncomfortable as that is at times. It seems clear that a combination of science and art is required and that neither is sufficient without the other. I believe the advocates of each position actually accept this centrist position in their practice.

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What Is Creativity Anyway?

Creativity is often considered to be nothing more than originality or unusualness, but, on closer examination, it’s clear that divergence alone is not enough. For example, I may decide to cut my lawn with a pair of scissors. Generally, that would be considered more odd than creative. It would be unusual and unexpected but very inefficient. If I were able to find an unusual way to cut my lawn easily or enjoyably, then the solution would be considered creative. Therefore, creative acts are also measured by their utility— that is, their ability to accomplish a defined task with acceptable effectiveness or heightened appeal.

No one can produce optimal, meaningful, and memorable learning experiences in a single pass of analysis, design, and development. Certainly, experienced and talented people will do a better job than those with little experience or background. Although scientific methods are appropriate to investigate alternative instructional approaches, the science of instructional design is not yet sufficiently articulate enough to prescribe designs matching the impact of those devised by talented and, yes, artful instructional designers.

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It seems that no matter how complex some theories may be, and some are bewilderingly complex, dealing with the complexity of human behavior is beyond appropriate generalizations of research findings. By the same token, we need to draw heavily on research foundations to teach people the art of instructional design. Without the rudder of research, creative design results in applications that are simply different and unusual but not necessarily effective.

Art + Science = Creative Experiments

Within each e-learning project, we are looking for ways to achieve behavioral changes at the lowest possible cost and in the shortest amount of time. Creativity helps us achieve these goals with just the right blend of content, media, interactivity, individualization, sequencing, interface, learning environment, needed outcomes, valued outcomes, and learners. Each of these components is complex, and the integration of them with the others brings yet another layer of complexity. Each e-learning application is therefore something of an experiment—a research project in its own right—and creativity is needed to find effective solutions as quickly as possible.

This is not to say that each new application must be developed from k

a blank slate. Far from it; there is much more research and experience to k

draw upon than seems to be considered by most teams. An excellent com-pendium with interpretations for practical application has been available for some time and can be found in Alessi and Trollip (2001).

Problems Applying Research

Results

Use caution when applying research to instructional design. Specifically, don’t overgeneralize research findings. The temptation may be to apply theories hastily without carefully considering whether findings in one context apply to another context. Functional attributes of contexts—including characteristics of learners, expectations of them, prior learning experiences, desire for training, and so many more—differ more often than is apparent.

When I’ve asked my graduate students to justify various peculiarities in their designs, they could frequently and proudly cite published research Making Success Possible

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findings. But often, with a bit more analysis, we could see how the referenced findings could be valid and yet not actually support the graduate students’ design decisions. In many cases, one could cite other findings that would suggest doing quite contradictory things.

A scientist friend of mine, Bruce Mico, reminds me often: “No one is more skeptical of scientific findings than a good scientist.”

This is a valuable insight. Scientists know how often a seemingly solid scientific fact turns out to be misleading or true only in very specific situations, the nature of which is yet to be discovered.

Scientists are careful to address the applicability of their findings and to caution against overgeneralization. Researchers are continuing to look for principles that are broadly applicable and less dependent on contextual nuances. While many advances are being made—most promisingly, in my view, through a collection of theories known as constructivism (Duffy and Jonassen, 1992; Jonassen, 1999)—it is very important to realize that many appealing principles are far from universally true. It’s easy to make k

mistakes.

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Valuable as scientific findings should be, it’s perplexing to me that so many who know research literature well cannot or at least do not design appealing and effective e-learning applications. If a pill tastes too awful to swallow, it will remain in the jar, benefiting no one. Such is the case with many e-learning applications too awful to endure.

The problems appear to lie in two major areas. First, it’s important to keep not only the intent of a learning experience in mind but also the likely assessment the learner will make of the experience. Is it meaningful, frustrating, interesting, intriguing, painful, confusing, humorous, or enlightening? Learners are emotional, just as they are intellectual, and emotions have an effect on our perceptions and what we do. In addition, adult learners are zealous guardians of their time. If they perceive a learning experience to be wasting their time, they will become irritated and resentful. In that case, attention will shift away as engagement fades, and the motivation to escape will take precedence.

It’s often noted that a high percentage of learners do not complete e-learning courses. Optimists say attrition occurs because learners quit when they have gotten all they need from a course. Because e-learning offerings are intended to assist people individually, learners should, in 70

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fact, opt out when they’ve gotten all they need. Of course, the more likely explanation for not finishing is that learners have had enough. Not all they need, but all they can stand. In their judgment, the benefits of completing the course do not justify the time expense or the pain of sticking it out.

Harsh? I suppose so. Reality? I think so.

Second, many common design processes actually prohibit successful creativity. In general, they make impossible inspired design ideas and force designers toward the mundane—all with an explicit rationale and justification to present to management and concerned stakeholders. It’s amazing how readily organizations complain about their lack of empowering training and yet find themselves structurally, mentally, and even culturally defiant against changing to approaches that will get them to their beleaguered goals.

Chapter 14 discusses an effective process called the Successive Approximation Model (SAM). It offers a dramatically different approach to e-learning design and development, even though nearly all of the basic steps and procedures are found in every other formalized development process. It requires change, a new group dynamic, and managerial flexibility, but it’s worth it. It can make all the difference as to whether winning ideas will be discovered and incorporated in training or whether status quo k

practices will preclude improvement.

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A Pragmatic Approach

So if creativity requires guidance, current scientific findings are helpful but insufficient, and the processes typically employed don’t get us the solutions we need, what can we do? We can take a pragmatic approach that depends on some creativity, intuition, and talent, to be sure, but also depends on experience as much as published research, intelligence, and an iterative process that includes experimentation and evaluation. These foundations work well, but they work well only for those who are prepared and armed with the knowledge of how they work together.

The approach I advocate, and will present shortly, is pragmatic, validated through countless applications, supportive of creativity, and comparatively simple. What you’ll find here is:

• A frank, outspoken, impassioned, and blunt critique of what doesn’t work

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• A list of conditions and resources essential for success

• A process that promotes error identification and rectification as a manageable approach to achieving excellence

• Examples of good design you can use

Get ready; all this is coming up.

The Takeaways

This chapter reviewed a range of multifaceted situations in which e-learning might be a powerful component of a mission-critical solution, including some unexpected situations in which e-learning might be very helpful. It also presented a list of essential conditions for success:

• Performer competency is the problem.

• Good performance is possible.

• Incentives exist for good performance.

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• There are no penalties for good performance.

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• Essential resources for e-learning solutions are available.

Finally, this chapter showed that for e-learning or any training solution to succeed, it is essential that it be designed well—much better designed than what is typically seen—and this requires an investment of human resources going all the way up to the key visionary. If you are that visionary, you must be on guard, because people will let you down for many reasons (some of which were identified in this chapter), while earnestly doing what they think you want. You will need to invest the necessary time and resources to achieve your objectives.

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Chapter 5

Executive’s Guide

to Good e-Learning

Excellent e-learning is an investment that pays for itself over and over again. It’s ready to go any time learners are ready for it. Each positive e-learning experience energizes, focuses, and enables yet another learner to be both more personally successful and able to contribute more to the organization.

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Differentiating the Good and the Bad

While energizing, focusing, and empowering e-learning is the goal, e-learning often falls short because traditional instructional design principles are either misapplied or used inappropriately. Common sense would say to abandon poor practices when they yield little success, yet they are seemingly ingrained and live on. I don’t like to criticize earnest efforts. Even poor e-learning often takes considerable effort. But I do hope to dislodge organizations from adherence to ineffective principles frequently followed with something akin to religious fervor. It’s only right if it works; otherwise, it’s wrong regardless of its source.

Conversely, when we find approaches that work reliably, we should use them. And share them. And we should continue to explore and evaluate so we can discover new and more effective means to help learners learn.

We should be guided by values, not habits; by realized benefits, not traditions.

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The eLearning Manifesto and its list of

desired e-learning values have received

widespread endorsement by researchers

and thought-leaders. These values and

the principles offered in support of them

provide an excellent guide that diverges

notably from what characterizes so much

of today’s work. See Chapter 8 for a review

of the Manifesto.

I am admittedly irreverent in my regard for many design practices and vote strongly in favor of effective, pragmatic approaches. What I value are meaningful, memorable, and motivational learning experiences because they have the best chance of enabling people to do what they want and need to do. I hope you already share these values with me; if not (yet), I hope to convince you that these values provide helpful guidelines for your investment in e-learning and your employees.

This chapter is especially for executives, but also, I hope, it will be of value to everyone. It covers key design concepts at a high level but in sufficient detail to specify criteria to be met by any e-learning application your organization develops or purchases. It will also help you recognize k

good and poor designs to judge whether a proposed project or purchase k

is worth the investment.

Design versus Technology

Success with e-learning comes not from the fact it employs technology for delivery, but rather from how it interacts with learners individually.

In other words, it’s instructional design that determines the quality of all instructional experiences, whether delivered electronically or not. Technology has many capabilities, but we have to be selective of which ones we use, and when we use them. We have to avoid doing things just because technology enables them, whizzy or not, and harness technology in ways that achieve desired outcomes.

Whizhead: Hey! Look at how I got that graphic to spin around!

You: That’s great, Whiz, but um, why is that graphic spinning around?

Doesn’t all that commotion make it harder to concentrate on what’s really important?

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Whizhead: I just learned how to make things spin in 3D. I love these new software tools. Learners will think this is really cool.

You: Wouldn’t learners find it more useful to zoom in and out to inspect product details?

Whizhead: I don’t have time to do that. It took a while to get this thing to spin, and I think it’s cool! Don’t worry. They’ll love it and appreciate how up to date our technology is.

We must not mistake appealing new delivery technologies for good instruction—even if learners report liking it. Good design, not the latest delivery technology, is essential to success. Good e-learning design is good because it uses available technologies effectively to make learning happen. It’s the design that will make the experience boring or inspirational, exhausting or energizing, meaningful or meaningless. It’s the design that creates value out of the capabilities technology offers.

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Three Priorities for Training

Success

There are many facets of instructional design that may tempt us to lose focus. This is especially true in e-learning because its multimedia nature offers an endless array of prospects for invention and artistic expression.

Typically, there’s also the frustration of overwhelming amounts of content that subject-matter experts want to see included. The success of any effort to create effective e-learning depends on keeping priorities straight and focusing on those things that contribute to learning success.

This topic is actually one of the few simple and straightforward topics within all the complexity of successful instructional design. Design success comes from doing just three things well:

1. Ensuring learners are highly motivated to learn

2. Guiding learners to appropriate content

3. Providing meaningful, memorable, and motivational learning experiences

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k

We’ll review each priority briefly here, as it will be a recurring message throughout the book and given further attention in subsequent chapters.

1. Ensuring Learners Are Highly

Motivated to Learn

Learners must always do the learning; we cannot do it for them. Motivation is essential to learning because it energizes attention, persistence, and participation in learning activities—all the necessary components of a successful learning experience.

The importance of motivation is certainly not new in the literature of learning and instructional design (Keller and Suzuki, 1988; Keller, 1987; Malone, 1981). Robert Mager wrote, “No teaching goal can be reached unless the student is influenced to become different in some way than he was before the instruction was undertaken” (1968, p. 8).

Unfortunately, consideration and explicit treatment of motivation has been absent in the preponderance of e-learning. Only recently, most 76

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notably with heightened interest in gamification, has bolstering motivation crept into design plans here and there. This is good news, but learner motivation needs always to be front and center.

I’ve seen the remarkable effects of stimulating learner motivation and attitude, but there’s still much work to do before designers feel they can devote enough attention to this issue.

Advisory

Buyer Alert: Buyers of e-learning applications readily specify content coverage, but rarely request even a minimal amount of motivation. As a result, overt efforts to ensure sufficient learner motivation and an energized attitude get almost no attention at all.

Spend wisely! As shown in Figure 5.1, there is typically very little attention given to bolstering the learner’s motivation in e-learning designs.

In contrast to traditional practice, I would suggest that if you have a very small budget, it might be appropriate to spend nearly the entire budget on heightening motivation and to make learner attitudes as positive as possible. For more average size budgets, perhaps up to half the budget should be used to bolster motivation.

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k

Why spend so much on motivation? Highly motivated learners will find a way to learn. If necessary, motivated learners can be quite creative in finding sources of help, information, best practices, and so on. They will support one another, exchanging information and teaming up to find missing pieces. If your training program gets you only this far, you’ve Typical Emphasis on Motivation

More Effective Split

Motivation-building activity

Content-focused interaction

FIGURE 5.1

Emphasis on learner motivation.

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probably already won the toughest battle. Now you can go on to make your performance solution even more cost-effective by addressing the remaining two priorities.

2. Guide Learners to Appropriate

Content

Highly motivated learners are eager to get their hands on anything that will help them learn. To take advantage of this motivation, it is important to respond with appropriate materials in a timely manner.

There’s much more to this than meets the eye, and it’s not just the challenge of creating clear, understandable content—which does take time, effort, and expertise. But clarity is just one essential criterion for good content. Content must relate to what’s motivating the learner, and it needs to be focused not just on knowledge, but also on performance outcomes.

Making sure content is appropriate for an individual learner means either providing excellent navigation (indexing) to help learners identify appropriate material or applying an assessment that will determine what each learner needs and then making that specific content available.

In either case, e-learning is often a cost-effective means of providing access to appropriate content.

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Keep in mind that exposing learners to information is not teaching and will rapidly sap motivation if it doesn’t enable learners to accomplish what they’re seeking to do. Maintaining motivation while building performance skills and confidence requires well-crafted, rewarding learning experiences and plenty of learner practice, so be sure to address the third priority, too.

3. Provide Meaningful and Memorable

Learning Experiences

Motivation and good content are usually not enough for learners to acquire new skills reliably. Unless provisions are made to guide learners, help them practice sufficiently, and learn from mistakes, skill development will be too slow and require a lot of effort. In many cases, there is a wide chasm between (a) providing good resource materials and (b) achieving sustained performance competencies.

Delivering meaningful and memorable instructional experiences is important, and both are essential qualities. If either is deficient, you get 78

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no useful outcomes. That is, if you can’t remember what you’velearned, it won’t guide future performance. And if you can remember that you learned something, but just didn’t understand it—well, that isn’t going to help you either.

Meaningful

Memorable

Outcome

0

×

100

=

0

100 ×

0

=

0

The importance of practice cannot be overemphasized, especially practice that is spaced out over increasing periods of time (Thalheimer, 2006). One can read extensively about delivering good speeches, handling a difficult customer, or managing a complex project, but guided and independent practice will still be necessary to reach needed levels of proficiency. In many cases, it is preferable for learners to make mistakes in a learning environment where guidance is available and errors are harmless, rather than on the job where guidance may be more difficult to provide and errors could be costly and damaging to people, equipment, materials, k

or the business itself.

k

Advisory

Make no mistake! It is critical that learning experiences have three characteristics: They must be meaningful, memorable, and motivational. If a learner can’t understand the learning experience, or the experience seems irrelevant, it is obviously a waste of time for that individual. If a learner can’t remember what was learned, the experience is similarly unproductive. If a learner doesn’t bother to apply what was learned, the learning returns no value. The most expensive training programs are those that don’t work, regardless of how efficient the creation of them might have been, regardless of how graphically attractive they are, and regardless of how inexpensive it was to deliver them.

Let me emphasize the importance of meaningful, memorable, and motivational (M&M&M) qualities of learning experiences before we go on to specific design requirements within each of the components of e-learning.

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Meaningful Experiences

If a learner doesn’t understand, then that learner will not gain from the experience. This is instructional failure. Designers of single-channel deliveries for multiple learners, such as classroom presentations, must decide whether to speak to the least able learners (in hopes that other learners will tune in at the appropriate points) or target the average learner (in hopes that unprepared learners will catch up and others will wait patiently for something of value). The approach often results in many learning casualties and is always expensive and a waste of time.

Further, if learners don’t see valuable implications of learning the content, such as its applicability to the work they do or don’t see advantages of the process being taught over the one they currently use, the learning experience is also likely to be of little value. When different learners perform different functions, it is important to help learners see the relevance of the training to their respective responsibilities. We shouldn’t just assume they will figure it out on their own.

Well-designed e-learning has the means to be continuously meaningful for each learner. It can be sensitive to learner performance, identify levels of need and readiness, select appropriate activities, and engage learners in experiences that are very likely to be meaningful.

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Memorable Experiences

If meaningful experiences and the knowledge they convey are quickly forgotten, or if learners don’t remember to apply what they learned or know how to apply it on the job, the learning experiences might as well not have occurred. Employee time spent in training is expensive to employers.

It is not usually the goal of training simply to give workers some time off the job, only to return with no improved abilities. Thankfully, e-learning has many ways to make experiences memorable, such as using:

• Interesting contexts and novel situations

• Real-world (authentic) environments

• Problem-solving scenarios

• Simulations

• Risk and consequences (serious learning games)

• Engaging themes

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• Engaging media and interface elements

• Drill and practice spaced over time

• Humor

I need to mention that some of these elements easily become distractions, if not used well. Used effectively, however, they can make learning experiences more memorable. But they need to be used judiciously. And just as some advertising commercials can be recalled for their humor or creativeness, we don’t always remember what product they were attempting to promote. Not good.

Motivational Experiences

Learning is all about behavioral change. We don’t teach and learn just to fill out a report card; we teach and learn to perform tasks we couldn’t do before or to do them more proficiently. It’s most important neither instructional designers, their organizations, nor learners focus on posttest scores. The focus needs to be squarely on performance outcomes.

To get where we want to go, learners need to be motivated to learn and motivated to use their learning for improved performance. As we’ll k

detail in Chapter 9, there are many ways to do this. Then we’ll discuss k

seven keys to motivational e-learning in Chapter 10.

The Takeaways

It’s important to see and use e-learning as a means to an end. It’s not the ultimate goal. The ultimate goal is the targeted performance outcomes.

The three priorities for training success suggest a correspondingly prioritized approach for effective e-learning application.

1. First, use e-learning to provide multimedia experiences that stimulate emotions, set expectations of success, create a positive learning attitude, and help learners visualize success and the rewards that accompany success. If this is all you have time and budget to do, you may still succeed in reaching your performance goals, because highly motivated learners with the right attitude will overcome many obstacles to learn, even if they have to do it on their own.

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2. Second, use multimedia and navigation components of e-learning to help learners find the instructional content they need and to communicate content to learners clearly and on demand. It’s like setting out a smorgasbord for a hungry crowd!

3. Finally, use e-learning’s interactivity to present individually adjusted levels of challenge, engage learners in active learning experiences where feedback includes presenting the consequence of learner actions, and provide sufficient, spaced practice for long-term retention.

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Chapter 6

Where Does

e-Learning Fit?

If (and it’s an important if) there’s a performance problem, then, in most cases, the problem can be addressed effectively with learning. Instruction and consequent learning cannot overcome performance barriers such as the lack of necessary equipment and resources. It will not change behavior when there are greater rewards for continuing current practices.

k

It will not change behavior when the focus is simply on providing infor-k

mation, such as extoling the damages caused by smoking, poor diet, or lack of exercise. Performance improvement requires a combination of knowledge, performance practice and rewards.

But whatever business you’re in, whatever content and outcome behaviors you’re dealing with, if better outcomes can be achieved through enhanced skills, e-learning can probably have a valuable and cost-effective impact.

Of course, e-learning can be effective only if it is designed in ways that address the need. It’s an obvious truth, but too often e-learning’s capabilities are used simply to present information as shown in Figure 6.1

regardless of the need and desired outcome.

Fitting Strategy to Targeted

Outcomes

We need to take quite a few situational parameters into account in order to select an appropriate e-learning strategy, but even without digging deeply, it’s critical at least to get the broad strokes right.

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Desired

Follow

Remember

Perform

Outcomes:

Instructions

Instructions

Expertly

Typical

Provide Even

Instructional

Provide

Provide More

More

Strategy:

Information

Information

Information

FIGURE 6.1

Misaligned instructional strategies.

Consider simply the primary outcomes of (1) preparing learners to follow instructions (as in preparation to use Electronic Performance Support Systems), (2) preparing learners to perform without real-time aids, and (3) helping learners become expert performers. We find providing information is adequate only for the first—the outcome of following instructions. Even then, as we’ll see, it’s rarely sufficient.

Practice is necessary if people are expected to remember and perform tasks that have any amount of complexity, which is likely to be the case if we’re undertaking development of e-learning.

k

Challenges with simulated outcomes are optimal for creating k

expertise. Experts not only know how to handle common cases but also are able to extrapolate to new and unpracticed situations effectively.

It’s important to note that the outcomes listed in Figure 6.1 are simply points along a continuum. For example, between Remember Instructions and Perform Expertly is an important range of skills. In this region, we’d likely find situational assessment and decision-making skills required.

Although using this rudimentary framework could help improve effectiveness, there’s much more to be considered. But let’s continue to keep this as simple as possible.

The nature of the task and prior preparation of the learner are important to take into consideration. If the task is simple and safe for the learner, then the e-learning strategies suggested in Figure 6.2 are fitting. But if the task is a complex one for the learner or involves risk, such as physical harm or costs, then instruction needs to borrow from the more powerful strategies to the right as shown in Figure 6.3.

So, for example, if the desired training outcome is simply to prepare learners to follow available instructions but the task involves considerable risk, then a good measure of practice will be essential.

Note that a task that’s simple and/or safe for one individual may be complex or risky for another person with less experience. It can be very 84

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Desired

Follow

Remember

Perform

Outcomes:

Instructions

Instructions

Expertly

Appropriate

Challenge

Instructional

Provide

Provide Guided

and

Strategy:

Information

Practice

Simulate

FIGURE 6.2

Adapting e-learning strategies to primary performance outcomes.

Desired

Follow

Remember

Perform

Outcomes:

Instructions

Instructions

Expertly

Complex or Risky

Challenge

and

Simulate

Provide Guided

Task

For Learner

Practice

Provide

Simple & Safe

Information

k

FIGURE 6.3

Appropriate e-learning strategies considering (1) desired k

outcomes, (2) nature of the task, and (3) learner readiness.

important to adapt instructional strategies to the level of readiness of the individual learner. And this is something e-learning can do readily when designed and built to do so.

Type of Content

When we talk of instructional content, we need to focus on the type of outcome skills the courseware is designed to develop. When addressing the question of where e-learning fits, does e-learning work with the major classes of skills?

Cognitive Skills

Procedures, facts, and conceptual knowledge are all natural types of content for e-learning. These are vital components of learning almost anything. From food preparation to accounting, from aircraft navigation to marketing techniques, from quality manufacturing to drug abuse prevention, e-learning can help build cognitive skills.

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Soft Skills

Sometimes it’s thought that soft skills, such as management, leadership, interpersonal relationships, client management, and dealing with upset customers, are beyond the reach of e-learning. Yet, experienced e-learning program designers know that these are, in fact, areas in which e-learning has been singularly effective. Pioneering work done by the Internal Revenue Service to teach agents to deal with upset taxpayers, for example, and work done at Carnegie Mellon University (Andersen, Cavalier, and Covey, 1996) to teach ethics has demonstrated how uniquely powerful computer-supported learning environments can be for learning soft skills. We’ll examine some sample applications of this later.

Psychomotor Skills

There are, of course, skills that need physical practice. e-Learning is probably not the best way to learn to play the drums or to hit a baseball, yet these activities have critical knowledge components, such as knowing how to read a musical score or knowing when to bunt. Knowledge components can be taught through e-learning very effectively, as can various mental imaging techniques in which learners practice improved performance by visualizing and imagining it with little if any physical movement. These k

techniques are surprisingly able to improve performance (Korn and k

Sheikh, 1994). Don’t overlook the opportunity to use e-learning as an appropriate and effective part of a training program for behaviors that are primarily based on motor skills.

Interface devices and sensors are now being developed for application in various simulators and virtual reality systems and to assist persons with disabilities as well as recovering medical patients. Striving for perfection, some golfers and Olympic athletes analyze their performance using such technologies (Sandweiss and Wolf, 1985). These devices are rapidly becoming available for use with e-learning applications designed to teach a great variety of psychomotor skills. It’s clear the applicability of e-learning will expand ever wider as our experience grows and technologies develop.

You Have Choices

You don’t have to live with e-learning programs that don’t work. You don’t have to pretend your e-learning application is good when you know it isn’t or see no evidence of its benefit. You have options. Because a good e-learning program is a cost-effective way to get people to do the right things at the right times, it can help achieve vital business goals. Cloak-ing poor training with an on-the job training cover-up (whether it’s done 86

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consciously or not) neither fixes the problem nor achieves the many positive competitive outcomes that might otherwise be possible. And it costs plenty. This shouldn’t be a difficult choice because there are reliable ways to produce effective learning experiences. Going about it the right way won’t be a risk of replacing one ineffective program with another. But you do need to go about it the right way.

Smart e-Learning

There are critical and often overlooked fundamentals to being smart about e-learning (see Table 6.1). When the goal is not just to get some training in place but rather to change defined behaviors, you’re off to a good start. Then, you have to accept that good e-learning applications, while far less expensive than poor e-learning applications, are still an investment. Good training isn’t cheap in absolute dollars, and the major expense for e-learning is up front for design and development. This is why the rich can get richer and the poor do get poorer. The rich can more easily afford the up-front investment and enjoy the long-term benefits. With smart instructional design, however, good courseware is less expensive than you might think.

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TABLE 6.1

A Smart Approach to e-Learning

Critical Elements

Critical Because

Goal is to change behavior

It’s easy to assume that e-learning is only about

teaching things, but success isn’t the result when

people know the right things to do, yet continue to do the wrong things. Both the e-learning and the

environment in which it is applied must be designed to enable, facilitate, and reward good performance in order to achieve maximum success.

Adequate financial

While the return on an investment in a good

investment

e-learning program can be incredible, it takes an

up-front investment in design and development.

Inadequate investment can severely reduce the ROI,

even making it negative. (Don’t go with the

lowest-price option unless you’re sure that what you’ll get will meet your success criteria.)

Partnership between

If business managers abdicate their critical role in the business managers and

process of achieving needed human performance, it’s e-learning developers

much less likely that e-learning will succeed. Training designers need a continuing partnership with

management to know exactly what behaviors are

needed, to understand the challenges trainees will

k

face on the job, and to provide post-training support k

and incentives.

Partnership with

There are many ways to inadequately fund e-learning subject-matter experts

projects and thereby ensure their failure. One is to provide inadequate access to subject-matter experts (SMSs)—the people who really know what behaviors

are needed and what must be learned to enable

people to perform them. Almost continuous

availability to SMEs is required to ensure a training program will be worth the investment. Note that

SMEs include not only the people who perform tasks

being taught or teach courses and write manuals, but also the people who supervise operations and know

exactly what their teams need to do.

Partnership with learners

Learners should not be the blind victims of whatever instructional approaches experts think would be

effective. Learners can be helpful throughout the

entire development process, from definition of what needs to be taught, through the design process, and into the final evaluation.

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To be sure, neither the rich nor the poor benefit from just doing something, from just going through the motions. If you don’t focus intently on changing behaviors, there will be no winners, and e-learning will look like a frivolous undertaking. Even with little to spend, using what’s available wisely to address key behaviors can make a big impact. If you have little to spend, you can ill afford to waste what you have.

Over $51 billion was projected to be spent on e-learning in 2014

(Docebo, 2014). The likelihood is great that $25.5 billion of that will be wasted. If money is available, it will be spent, but it will achieve little of importance if we stay on the same path most are on today with their e-learning applications. You don’t have to take that path, rich or poor.

Partnerships

It takes careful planning, organization, and support to build and deliver good training solutions, regardless of the means of delivery. Design of successful e-learning systems can be done in-house or contracted to outside developers, but neither approach is successful enough to justify the k

costs without the involvement of management, subject-matter experts, k

and learners throughout the process. Many projects fail to reach their needed potential because these supportive people are not available enough or are not even asked to participate. If you’re planning e-learning development for your organization, be sure to make arrangements for adequate participation by representatives of each group.

Management Participation

Organizational leaders may provide financing for training development and assume their involvement is done, but this is often a serious mistake.

Management needs to provide not only the financial support but also continue to help clarify the vision, define success criteria, and provide a performance-centric environment.

Achieving an organization’s vision depends on human performance.

If everyone understands the goal, including those developing the training and support systems expected to help deliver critical performance, the probability of reaching the goal is much higher.

The criteria for success translate portions of the overall vision into specific performance requirements. The larger vision gives designers a vital context within which to work and to motivate learning. Everyone Where Does e-Learning Fit?

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needs to be clear that success won’t be achieved if the e-learning program doesn’t result in specific levels of performance required by and emanating from the overall vision, and that this is what the effort is all about.

Finally, financial support is only one kind of support that management needs to provide. Although financing is critical, it’s insufficient by itself to ensure success. Behavioral patterns are established in response to instructions, rewards, effort, available resources, perceived risk, observed behavior in others, team values, and so on. Being able to perform as management would prefer does not guarantee employees will be willing to perform in that way. Management must understand that change is difficult, that there is inertia behind existing behavior patterns. Change will not be accomplished unless management provides strong intentional support for change.

A visual is helpful. Management is responsible for one of the pillars needed for a successful e-learning program but the project still needs the skills of an on-target design and development team to turn the vision, criteria, and support into a successful investment in e-learning (Figure 6.4).

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Management

Management

Design

Design

FIGURE 6.4

Success requires management support and performance-focused design.

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Successful e-Learning

Support

Interactivity

Criteria

Content

Vision

Motivation

Management

Ineffective

Design

e-Learning

FIGURE 6.5

Bridge over troubled e-learning.

The design team’s challenge is to provide a strong matching pillar.

After defining the behavioral objectives that will get learners ready to perform correctly and adequately, designers focus on creating ways to ensure high levels of learner motivation. They then make sure that the enabling instructional content is clear and accurate, as a base from which k

to evolve meaningful and memorable learning experiences (Figure 6.5).

k

Both pillars are needed to achieve success in e-learning, although designers often struggle for success without much support from management. What they achieve is often commendable given the circumstances.

Management, in turn, needs designers who will strongly resist building superficial solutions, provide needed insights about instruction, learning, and human performance, and lead development through a participative process that effectively involves all needed people and resources.

Subject-Matter Expert Participation

Obviously, subject-matter expertise is important, but what is surprising to many is that this expertise isn’t just needed at the beginning of an e-learning development project; it is needed throughout. As application prototypes are built and reviewed, for example, needs and opportunities arise for additional content and revisions. If experts aren’t available, or aren’t available without considerable advance notice and scheduling, projects suffer—sometimes fatally.

Interactivity can be viewed as a dialogue between the learner and the e-learning application. The e-learning application represents the combined subject-matter, instructional, and media expertise of the design and Where Does e-Learning Fit?

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development team. The application becomes, if you will, an expert mentor with whom the learner interacts.

Interactive events evolve through the process of design and development (see Chapter 14 for details on the process). As they evolve, the design team looks for ways to make the learning experience as beneficial as possible. This frequently involves searching for ways learners can be allowed to make instructive mistakes. As this occurs, many possible learner behaviors are identified, quite often including a number that were not originally anticipated. Appropriate responses to these behaviors can be provided only if subject-matter experts are available to specify appropriate consequences and feedback. For example, a design team might ask, “What would happen in real life if an employee accidently held the on/off button down while turning the ignition key instead of just pressing and releasing the button first?” To which a subject-matter expert might respond, “The whole thing would blow up, and we’d have to evacuate the north side of the city.” In that moment, a potential behavioral mistake would have come to light and a learning opportunity would have been born.

Learner Participation

Many e-learning development teams seek the participation of prospective k

learners only near the end of the project. Learners are invited to use the k

application so that functional problems can be observed, ambiguities and problematic elements can be corrected, and learning effectiveness can be measured. Unfortunately, this is too late in the process to gain insight on structuring learning events and or to get input on shaping the experience as a whole.

All too often, organizations are ready to speak for their people—

including their learners—to make assumptions about what they will find interesting, what they do and do not understand, where their learning problems will be, and so on. When learners are put in a situation in which they can contribute their perspectives, many such assumptions may be disproved. Just asking potential and recent learners some basic questions often reveals important information for design that would otherwise have been missed.

Beyond answering initial questions, learners can make vital contributions when asked to review prototypes and interact with evolving e-learning applications, even if they are quite rough and quite incomplete.

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The Takeaways

Because of its interactive nature and ability to integrate multimedia, e-learning is suitable to training a wide range of subjects, including cognitive and soft skills and even some essential components of physical skills.

Developing optimal e-learning applications involves sensitivity to many perspectives and values. It involves the interplay of knowledge, technology, art, and design. It’s not at all like sending out for a pizza—listing a few parameters and getting a hot product delivered to your door. The effectiveness of the involvement and partnership of all key players will determine the ultimate success of any project. Unfortunately, this means management needs to be available, just as do subject-matter experts, designers, recent learners, and some prospective learners.

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Where Does e-Learning Fit?

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Part II

Great e-Learning

Design

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Chapter 7

Seven Simple Success

Strategies

I see my job as searching for the simplest, surest paths to instructional excellence and sharing the steps I’ve found along these paths in ways that don’t require a graduate degree to decode. “As simple as possible,”

as Einstein suggested, “but not simpler.”

So before you read further and we get into the details, you might want to review these simplifying principles that can help you achieve suc-k

k

cess with e-learning. You may find this is all you need to achieve the success you’re looking for.

As Simple as Possible

I have some simplifying strategies to share. If these strategies work as well for you as they have for me with a wide range of designers, they will lead not only to better products but also to the comfort of knowing you’re using time and effort wisely. Here are seven simple success strategies.

1

Simple Success Strategy 1

Ask, Would you want

to learn from this?

It’s a simple question—one I sometimes feel embarrassed to ask— would you want to learn from this? (I tend to ask this question of designers when I’m looking at a poor design and floundering to say something respectful k

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and helpful. Even a poor product can take a lot of time and effort to produce. I know that. We grow a bit sensitive to criticism after investing a lot of effort. But effort doesn’t necessarily make the product good, does it?

We all need to ask ourselves this question of our own work as well as of any e-learning we’re thinking of deploying.)

We have research to tell us how to build up from basic skills, combining challenges to learners in ways that develop effective decision-making skills. We know quite a lot about practice, what to practice and when.

We know some useful things about imagery and animation. We know the importance of performance confidence and that skill without confidence isn’t particularly valuable.

We also know that even the most knowledgeable persons cannot always design learning events that engage learners, optimize the use of their learning time, and produce valuable performance skills. Advanced practitioners and novices alike can find their earnest instructional design efforts falling short in a devastating manner. It’s the curse of learner boredom that so often thwarts well-intentioned efforts. And it’s so easy to bore learners: A truckload of text. Multiple-choice questions anyone can answer, whether they’ve acquired intended skills or not. A confusing, effort-absorbing user interface that gets in the way. An attempt to teach learners something they k

already know, as if their time were of no importance.

k

We can’t list all the potential barriers to success because there are so many ways to create e-learning that no one except its creator could tolerate, let alone love. Even then, I wonder, would the creator really choose to learn in this way if there were options? I doubt it.

The degree to which courseware appeals to learners may be of little interest to learning researchers. I don’t actually recall the issue of boredom ever being raised in my graduate school courses, but learner engagement is vital for success with e-learning. Knowing how to engage learners will help you overcome many barriers and increase your odds of success greatly.

To be sure, appeal alone doesn’t get you to success. Many well-intended efforts have loads of appeal but are instructionally impotent. Appeal is, however, one essential ingredient for success. Many of the chapters of this book reveal ways to increase the appeal of your e-learning, but it’s important to ask yourself continually, and then ask others, would you want to learn from this? Be honest. If you get anything less than enthusiastic yeses, figure out why or just try something different and ask again. It isn’t the effort that counts; it’s making good design decisions.

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2

Simple Success Strategy 2

Match Instructional

Strategy to Outcome Goals

As I sit back in my chair and contemplate recent achievements and disappointments in e-learning, it occurs to me there’s often a fundamental mismatch between the instructional strategy applied and the experience learners need to reach their goals. Correcting this common error could make a widespread improvement in the real and recognized value of e-learning, because this error is so prevalent and because it incapacitates so many well-intentioned efforts.

Although any mismatch of strategy to goal will defeat effectiveness, by far and away the most common design mistake made is simply presenting information to learners when instruction is needed to reach performance goals.

Instruction can take many forms, of course, but simply presenting information is by far the weakest—if it should be considered instruction at all.

As shown in Table 7.1, it’s common practice to simply present information for all levels of targeted performance goals, increasing the amount of k

k

information and adding comprehension and recall quizzes for higher level goals. Awareness goals, as discussed next, are not really performance goals and assume desired performance will happen when people are aware of what should happen, this is a chancy proposition. Better to define exactly what outcomes are desired and then apply an appropriate instructional strategy. Matching strategies are briefly described for three types of performance goals. See Figure 6.3 for more clarification.

TABLE 7.1

Matching Instructional Strategies

Performance

Typical

Matching

Goal

Strategy

Strategy

Awareness

Present information

Redefine goal in performance

terms

Follow instructions

Present more detailed

Provide worked examples and

information

practice exercises

Remember

Present information + quiz

Practice with fading support

instructions

Perform expertly

Present even more

Provide challenges, simulated

information with even more

outcomes, and extended

details

practice

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3

Simple Success Strategy 3

Challenge Awareness Goals

Fun to say, but even more important to say: Beware awareness goals. Often in the context of wanting to spend minimal effort and money, someone will defend an undertaking of little instructional effectiveness by saying, We just want people to be aware of …

The question is, why do you want people to be

aware? So they can do what? The first response might be an equally evasive stance: We just need people to know … Again, we must ask, why? Why do you want employees to know you have both a Features and Benefits flyer and a User Guide?

With persistence, the underlying assumption will usually come out; it just takes the perseverance of Colombo or the insistence of a child to ask

“why” repeatedly. You might eventually hear, We want our people to correctly confirm we do have the product they’re looking for. We want people to question an unusual entry on the balance sheet. We want people to select appropriately between the Features and Benefits flyer and the User Guide.

k

You can have confidence people are assuming desired performance k

will arise from awareness; otherwise, why would anyone make any training effort at all, even a minimal one? They are, conscious of it or not, assuming the effort will get learners to do the preferred thing—the right thing.

Goals for awareness, knowledge, and understanding are based on the notion that when people are aware, informed, and comprehending, they will do correct, helpful, beneficial things. This is a risky assumption. You may have knowledge and not know how to apply it, just as you can understand how something is done, but not be able to do it.

No education or training program is likely to be effective in achieving behavioral outcomes if only awareness, knowledge, and understanding are addressed. I dare say these are never appropriate training goals, although they may be useful intermediate learning objectives. The link between awareness and ability to perform does exist. The assumption that awareness will yield significant performance outcomes, however, is a poor one and usually leads to wasted efforts. So, avoid awareness goals. Pretty much always.

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4

Simple Success Strategy 4

Design Backward

Perhaps Yogi Berra was thinking of instructional design when he said,

“If you don’t know where you are going, you’ll end up someplace else.” It’s easy to lose your way designing instruction and end up not achieving your primary goals.

There’s an easy, simple success strategy to prevent this problem: start with the final course content; make sure it will have learners practicing the skills they really, truly need post-training. And then work backward one step at a time. If you should run short on time, at least the content you still need to develop will be the most introductory, simplest content to work with.

5

Simple Success Strategy 5

Think Context, Challenge,

Activity, and Feedback

(CCAF)

k

Perhaps the most helpful discovery in my endeavors to help e-learning k

realize its potential was the identification of the four components of impactful, interactive, instructional experiences. CCAF is not to be confused with the phases of learning, by the way, or with other theories that help us understand and promote human

learning. The components of CCAF define

and comprise learning events. In my expe-

Context

Challenge

rience, we have been able to do many of the

things researchers and theorists prescribe

for optimal learning events just by struc-

turing learning events on these four inter-

related components: context, challenge,

Feedback

Activity

activity, and feedback. I think you’ll expe-

rience this as well.

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What’s been particularly gratifying is that the CCAF framework leads so readily not only to effective e-learning experiences, but also to powerful Serious Learning Games (SLGs).

Later in this book, you will find a full review of CCAF with a more extensive discussion and helpful examples. But here are the basics of how to use the CCAF concept to create learning experiences that improve performance:

1. Identify the Target Proficiency (Activity)

You can start with any one of the components, actually. For me, it often feels natural to start with activity, but you should start with whichever feels most comfortable to you. Following this Simple Success Strategy, ask yourself or your team what is the final performance you want learners to demonstrate proficiency in before completing their training. This is usually pretty easy because it’s what the whole training program is being built to produce. You need to determine how learners will demonstrate their abilities such that they can be assessed.

2. Identify the Context(s)

What are the contexts in which this activity will actually occur?

k

We want the skills learned in training to transfer to performance k

in real situations, so we want the context, one or many situations, to be representative of what the learner will actually see, feel, hear, and experience when performing the target proficiency in real life.

We call those authentic contexts.

3. Create Challenges

Given the authentic contexts in which learners may find themselves, what should they be able to achieve? That is, what problem should they solve or what decisions should they make? Learners address the challenges through the actions they take, as identified and enabled in design task 1 above.

4. Show Consequences (Feedback)

Experience-focused learning emphasizes use of consequences as a primary form of feedback. While novice learners are likely to need both explanatory and judgmental feedback as well, advanced learners may gain the most simply from seeing the consequences of their actions. It can be particularly impactful to suggest learners deliberately take wrong actions to see the consequences.

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Employing CCAF in design, as well as in documenting and communicating about instructional design, helps keep focus on essential elements of successful e-learning. Many of the examples you will see in this book are documented for you by calling out these four components.

6

Simple Success Strategy 6

Think Emotion-Arousing

Experiences

(Not Presentations)

For performance outcomes, presentations don’t cut it. Instead of putting great amounts of time and energy into the preparation of information for presentation, it’s best to think in terms of experiences we can enable—meaningful, memorable, and motivational experiences.

The computer—desktop, laptop, or mobile device—is an active platform and a platform we come to with the purpose of doing things. Together with its media-capable display and mouse, touchpad, stylus, camera, k

and/or microphone, the delivery platform sets user expectations for action.

k

Simply putting static information on the screen is wasting the potential of the technology and a disappointment to learners. And worse, although we tolerate it, static information presented on such devices is likely to be poorly absorbed and quickly forgotten, whereas activity-charged experiences are remembered much longer.

Not all experiences are alike. It’s not just any activity that fills the bill. Clicking the Next button is hardly a memorable activity. Although in instruction we’re definitely trying to stimulate cognitive activity, we achieve even greater impact when we also evoke an emotional response.

Many studies confirm that emotional stimuli enhance learning retention and without it, memories fade much faster (McGaugh, 2013).

Perhaps nothing is as emotionless as blocks

of text or pages of bullet points. It isn’t just the EMPOWER

formatting we’re talking about. It doesn’t mat-

NECT

ter if you have to press keys, touch a screen, or

N

O

click a button for information to be revealed;

C

O

ET

just requiring an input to reveal information

R

A

C H ESTR

adds no emotion unless there’s a context, a

purpose, and maybe a challenge.

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I’ve written much about the many means of engaging learners both cognitively and emotionally. In my book Successful e-Learning Interface: Making Learning Technology Polite, Effective, and Fun (Allen, 2011), I’ve gathered together bunches of ways designers achieve both cognitive and emotional learner engagement, such as by having learners imagine themselves in a high-ranking position with great authority or having the chance to be a hero if they can solve a tough problem quickly. This approach is an example of using the context of a story to get learners to care about outcomes—a story in which the learner plays a key role. Whatever the stimulus, it’s much more than an embellishment. It is a powerful technique to be sure learner emotions are involved.

7

Simple Success Strategy 7

Use the Successive

Approximation Model (SAM)

SAM is an iterative, agile process

Start

End

for the design and development of

EVALUATE

e-learning. It’s a much simpler pro-

k

cess than what’s been traditionally

k

used; it’s faster and more effective too.

DEVELOP

DESIGN

Figure 7.1 illustrates the basic itera-

tive process of the model, in which

evaluation, design, and development

FIGURE 7.1

Basic Successive

Approximation Model (Simple SAM).

are interwoven and performed multi-

ple times.

Some see SAM as the latest incarnation of the legacy ADDIE model (Analysis, Design, Development, Implementation, and Evaluation), although to me this perspective suggests critical aspects of SAM haven’t been understood. Let’s be clear about this: all processes include analysis, design, development, implementation, and evaluation, but that doesn’t make them ADDIE. It’s when you do each of these things, to what extent, and for what purpose that are critical to process definition. In these aspects, there are great and important differences between SAM and ADDIE.

The good news is that we’ve moved beyond the question of whether e-learning can be effective; we know it can be. In truth, it doesn’t matter how one sees the relationship between SAM and ADDIE or any other model used to manage how instructional design and development happen.

What’s important is that we have new, faster, and more effective methods 104

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to create effective e-learning. SAM is one of them. SAM and agile concepts, in general, have really raised the level of what’s possible without raising costs or extending time lines. This is very good news.

The bad news? We now focus so much on production efficiency and production cost reduction, we often sacrifice learning effectiveness in the process. For some inexplicable reason, organizations continue to think of training as a cost rather than as an investment made for identified gains—revenue and profit gains—and with the expectation of achieving those gains. They all but eliminate opportunities for potentially huge competitive business advantages in order to spend less on training development. It’s more important now than ever to build the best learning events possible within given constraints—sometimes ridiculous constraints considering what’s at stake. And SAM is one proven method of doing that.

Covered in more depth in Chapter 14 and as the entire focus of the book Leaving ADDIE for SAM (Allen and Sites, 2012) and the associated Field Guide (Sites and Green, 2014), SAM recognizes the importance of the Simple Success Strategy 1 question ( Would you want to learn from this? ) and integrates it into the process. By iteratively, quickly, and inexpensively building prototypes and examining them, designers and stakeholders can consider whether they’d want to learn in a proposed manner. The process k

takes quick steps to envision a possible instructional treatment. It then k

asks, Why wouldn’t we do this? Considerations include those listed below.

Why wouldn’t we do this (proposed instructional activity)?

• Would it engage a sufficiently broad spectrum of learners?

• Would it lead to proficient performance?

• Does it focus on what’s truly important?

• Are the delivery methods used to full advantage?

• Would it provide enough practice?

• Is it confusing or boring?

• Does it relate to previous and subsequent learning?

• Would it cost too much?

These are just a few of the questions under the very constructive inquiry, Why not do what’s just been proposed? Within the context of the process, there’s no expectation you would actually do what is proposed initially. The purpose of the exercise is to narrow in on a good design Seven Simple Success Strategies

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by beginning with what might seem desirable and then questioning it.

After taking stock, the cycle repeats by proposing something that would seem to have more strengths and fewer weaknesses and then scrutinizing it similarly. Generally three repetitions do it.

The Takeaways

Developing great learning experiences involves proper alignment of many factors. It’s much simpler to just present information than it is to actually help people learn and build skills. While the simplest strategies are often ineffective, there’s been a tendency to think developing truly effective instruction is too slow, too complicated, too expensive, and just too hard.

It’s not as difficult as many assume, but we have to focus on the right things.

To simplify developing good learning experiences while not relinquish-ing effectiveness, consider these seven strategies: 1. Ask yourself during the design phase, would you want to learn from a proposed approach? If not, it’s probably not a good one.

k

2. Carefully match your instructional strategy to the outcome goals you k

care about most. If you need learners to process insurance claims properly, make sure they practice processing insurance claims as part of their training. Don’t just enable them to answer questions about how it’s supposed to be done.

3. Make sure you have the right goals, being especially wary of

“awareness” goals. Awareness goals are sought when people haven’t wanted to think hard enough to define what measurable outcomes are really important and desired. When someone claims they only need awareness, they’re assuming they’ll get something more.

They’re assuming awareness will lead to desired performance.

Why not train for that performance and, in that way, be much more likely to get it?

4. Begin designing the final learning and practice activities first. They are the most important as they should have learners performing tasks at the same level as their jobs require. It’s vital to get this right. Then step back and design activities that prepare learners for what you’ve already designed, repeating until you’ve delivered a complete sequence of learning experiences necessary to take your learners from where they are now to a successful outcome.

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5. Because effective learning experiences, including SLGs, are built from the CCAF components of context, challenge, activity, and feedback, consider designing your courseware from the start by defining each of these components, working backward, of course, from the targeted outcome performance.

6. Stimulate emotions along with cognitive activity. Use a story context or timed performance. If the experience evokes an emotional response, it is much more likely to be remembered longer.

7. SAM is a very successful and simple model for designing and building instructional applications. It’s a bit of a “just do it”

approach that encourages design experimentation in prototypes using the actual delivery media proposed and asking, “Why not do this?” Answers guide the next experiment leading to the same question. About three iterations are usually sufficient to have done sufficient analysis and design to plan out the remainder of the work.

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Chapter 8

The Serious e-Learning

Manifesto

k

k

In the 1960s, it seemed that emerging instructional technology would truly change the world for the better—or at least the world of education.

It wasn’t a complicated vision. It was simply the belief that we could provide learning experiences that were:

Consistent and Impartial Instead of learning opportunities varying widely in quality, depending on the abilities, health, and even the mood of instructors, they would be consistent, impartial, and developed by the world’s best talent.

Individualized The programs would continuously assess each learner’s individual needs and adapt accordingly.

Free National governments would make access to libraries of educational programs free to all citizens, with or without enrollment k

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in educational institutions, to create a wiser public and a more compassionate and connected world.

Competitive Improvement Instructional programs would improve continuously through competition, public and expert assessment, and an open market for commercial offerings.

More than 50 years later, we haven’t made nearly the progress expected. The vision is still alive, at least with me, and significant progress has been made in some aspects. Clearly, e-learning is widely accepted, even with its many shortcomings. But it’s disappointing that so much of the progress has been made on the technology side, offering greater and greater practicalities, while so little benefit has been realized through instructional designs that realize the promise of e-learning.

Quality Obligations

When we create instructional programs, we have a much greater responsibility than jotting down a plan for tomorrow’s class. A greater responsibility than outlining presentation topics. A greater responsibility k

than readying a set of visuals.

k

In a classroom, we can help students advance, depending on their varying degrees of readiness and abilities and our instructional competence and agility. If we’re good at it, don’t have too many students, and our students have uncanny similarities, a classroom experience can be a successful event for all. But what if students are diverse in abilities, interests, and readiness as they usually are? It’s very likely, even if you’re a great instructional mar-vel, that a lot of learner time will be wasted, whether in waiting for help or waiting for the next topic.

Perhaps a Hippocratic oath for us instructional designers could first admonish us to:

Waste no learner time. Neither frustrate, bore, nor disenfranchise any learner.

With apologies to Albert Einstein, Stephen Hawking, and space-time curvature, lost learner time is never retrievable or reusable. And worse, negative attitudes shaped toward learning by poorly taught subjects preclude future successes and contributions. Poor instruction is regrettable to an extreme (regardless of how rapidly it was produced).

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Unlike a teacher in a classroom, the computer can be doing something different with each student at every moment simultaneously. It can accelerate or slow the pace; it can heighten or lower the challenge; it can skip ahead or provide extended practice or remediation. Most important, the effectiveness of computer-delivered instruction can be improved systematically through evaluation and revision. No matter how poor the first version might be, an instructional program can eventually reach extraordinary effectiveness through iterative refinement.

Page Turners

A fun novel may be called a page turner, but it is not a compliment when describing e-learning. Unfortunately, over the last decade, we’ve seen page-turning presentations, sans critical instructional elements, in all sorts of disguises, rolled out in droves, boasting of compromises to the lowest common platform capabilities so as to be responsive or adaptive to any device. All of this regardless of whether the instructional need were simply for information or advanced skill development.

To be sure, there are cases in which access to good information is all k

k

that’s needed. We will discuss those instances in a later chapter. But it’s clear that we’re far too ready to assume an online textbook is sufficient to develop skills and improve performance.

Basic Principles

I’ve been delighted (and enlightened) to work with thought leaders in e-learning to address what’s become an epidemic of abandoned basic instructional principles. Year after year, we see courseware designs at tradeshows and conferences that reveal new and inventive ways to make page turners look like something better. We see tremendous effort put into creating distracting treatments while neglecting the basic principles of effective instruction and the unique opportunities e-learning provides.

But no matter how well disguised, such neglect wastes learner time and sacrifices opportunities.

What to do? Spearheaded by industry thought-leaders and stalwarts Julie Dirksen, Will Thalheimer, and Clark Quinn, we decided to create what is now called The Serious eLearning Manifesto. The crafting of the The Serious e-Learning Manifesto

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Manifesto took months of discussion, consideration, and writing, because it was important to get it right. We wanted it to clarify the concerns we shared and become the foundation of our craft and profession—the basis of instructional design curricula everywhere. It needed to be based on sound research, practical for application, and successful in the field.

The Manifesto was reviewed, revised even more, and endorsed by dozens of industry spokespersons who became the Manifesto trustees in the process. It has since been endorsed by over a thousand professionals worldwide. You can access and endorse the Manifesto yourself at

www.elearningmanifesto.org.

Design Values

The Manifesto sets forth a list of values that should guide the design of e-learning (and any instructional design, for that matter) along with a comparative list of values that are currently shaping the preponderance of work being done today. The values contrast strongly with one another, helping to define what we should and should not do in our design work.

Let’s review each comparison.

k

k

Comparison of Typical e-Learning and Serious e-Learning Characteristics

Typical e-Learning

Serious e-Learning

Content versus Performance Focus

Typical e-learning focuses on presentation

Targeted toward achieving performance

of content. That leads to making sure all

outcomes, serious e-learning starts with

the information is presented in orderly

focus on needed behaviors and then

fashion—clear and complete. With a high

constructs contexts in which those

percentage of authoring time consumed by

behaviors can be developed and

content preparation, instruction tends to

practiced. If authoring begins with

focus on knowledge acquisition instead of

designing active learning experiences

building performance skills. Interactive

and then creates content required by

learning events that take additional time to

them, the end product tends to be quite

develop may be either omitted altogether

different from typical e-learning and

or superficial.

much more impactful.

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( Continued)

Typical e-Learning

Serious e-Learning

Efficient for Authors versus Meaningful to Learners Although the history of e-learning boasts

Serious e-learning prizes learning

successful learning in significantly shortened

experiences that produce superior

learning time, it also takes a considerable

post-learning performance in the

investment of time to design and build

shortest learning time. For serious

learning experiences that achieve these

e-learning, such learning experiences

important results. The desire for shorter

and successful performance outcomes

development time has fueled a movement

are mandatory. To a certain extent, the

toward rapid authoring, which has achieved more authoring time invested, the

speed mostly by using templated

shorter the required learning time will be

interactions. Templates are typically

and the better the performance

generalized for wide applicability, but that

outcomes will be. More authoring time

often renders designs that are less than ideal and less required learning time is for specific uses.

preferable to less authoring time and

subsequently extended learning time.

Attendance versus Engagement

Many of today’s programs are evaluated by

If learners find open programs engaging

how many learners have been put through

and beneficial and encourage colleagues

them. A larger throughput indicates a more

to take them, there’s good reason to

successful undertaking. The assumption, of

think these programs will have a more

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course, is that the program works for

positive impact. Engaging learners with

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learners and achieves the performance the

helpful, relevant learning is preferred to

organization needs. Outcomes often go

forcing learners into required training.

unmeasured, leaving usage as the primary

measure of achievement.

Knowledge Delivery versus Authentic Contexts

Organizing and preparing information for

The desired outcome of learning is the

presentation takes a lot of time and effort.

ability to do something the learner

In addition, technology allows highly polished couldn’t do before. If reading how to do presentation of information, including videos,

something can ensure successful

three-dimensional illustrations and

performance, then knowledge delivery is

animations, graphic effects, paging effects,

enough. But, in many cases, learners

and more. Authors have an almost endless

need to be put in situations in which

list of options to choose from, which easily

they can learn to recognize salient

distract authors from the greater opportunity

aspects of a situation, respond to them,

e-learning provides—the ability to provide

note the consequences, and practice

learners with interactive experiences.

until they can act effectively with

Unfortunately, typical e-learning tends to

confidence. Realistic or authentic

build only on the technology’s ability to

contexts in which the learner may be

disseminate information rather than on its

called on to perform make learning

ability to let people learn from witnessing the experiences relevant to the learner and consequences of their actions in situations

heighten the meaningfulness of the

resembling those they may actually

instruction.

encounter.

( continued)

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( Continued)

Typical e-Learning

Serious e-Learning

Fact Testing versus Realistic Decisions

Typical e-learning takes advantage of the

Although excellent performance has

convenience of standard-form questions to

knowledge prerequisites, serious

assess retention of facts. Multiple-choice

e-learning doesn’t consider retention of

and matching questions are very common

facts a valid measure of performance

(and quick to implement). But short-term

readiness. Rather, learners must be

fact retention has little to do with

asked to make realistic decisions and

performance proficiency.

execute procedures as may actually be

required.

One Size Fits All versus Individualized Challenges Typical e-learning ignores individual

To avoid severely frustrating slower or

differences and assumes all learners will

less well-prepared learners and boring

benefit sufficiently from the same

more advanced learners, serious

instruction. All learners see the same

e-learning works to provide

presentations and receive the same tests.

growth-enabling challenges for each

learner at (for practice) and just above

(for advancement) their current skill level.

Onetime Events versus Spaced Practice

Typical e-learning sequences through

On the basis of solid research, we know

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topics, progressing steadily to the end of

that practice sessions need to be

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instruction and probably a posttest.

repeated and spaced gradually farther

Practice is often minimal, but if it’s

and farther apart. Learning dissipates

included, it’s usually a block of practice

quickly after a single session of practice

exercises that learners must complete.

but persists for much greater lengths of

time when multiple sessions are spaced

apart.

Didactic Feedback versus Real-World Consequences Typical e-learning gives instantaneous

Effective performance derives in large

judgment in the form of “correct” or

part from predicting the consequences

“incorrect.” Sometimes the reason for the

of various decisions and being able to

judgment is included, but learners rather

evaluate alternative consequences as

quickly become focused on getting positive

good or bad. On the basis of these

feedback and avoiding negative, rather than

skills, people can correct errors as they

fully understanding the relationship between

occur and perform at a level higher than

their decisions and the real-world

simply following a preset script. Serious

consequences they are likely to cause.

e-learning puts learners in situations in

which the primary feedback is a

representation of what would really

happen given the choice(s) the learner

made.

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The Principles

The Manifesto provides guidance for achieving the characteristics of serious e-learning with a set of 22 principles. The principles constitute a pledge taken by the author-instigators, trustees, and signatories to use their best efforts to break the trends of typical e-learning and do work that has credible possibilities of producing successful and valuable learning that changes behavior and improves performance. They are set forth as follows:

1. Do Not Assume That Learning Is the Solution We do not assume that a learning intervention is always the best means to helping people perform better.

2. Do Not Assume That e-Learning Is the Answer When learning is required, we do not assume that e-learning is the only (or the best) solution.

3. Tie Learning to Performance Goals

We will couple the skills we are developing to the goals of organizations, individuals, or both.

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4. Target Improved Performance

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We will help our learners achieve performance excellence, enabling them to have improved abilities, skills, confidence, and readiness to perform.

5. Provide Realistic Practice

We will provide learners sufficient levels of realistic practice, for example, simulations, scenario-based decision making, case-based evaluations, and authentic exercises.

6. Enlist Authentic Contexts

We will provide learners with sufficient experience in making decisions in authentic contexts.

7. Provide Guidance and Feedback

We will provide learners with guidance and feedback to correct their misconceptions, reinforce their comprehension, and build effective performance skills.

8. Provide Realistic Consequences

When providing performance feedback during learning, we will provide learners with a sense of the real-world consequences.

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9. Adapt to Learner Needs

We can and should use e-learning’s capability to create learning environments that are flexible or adaptive to learner needs.

10. Motivate Meaningful Involvement

We will provide learners with learning experiences that are relevant to their current goals and/or that motivate them to engage deeply in the process of learning.

11. Aim for Long-Term Impact

We will create learning experiences that have long-term impact—well beyond the end of instructional events—to times when the learning is needed for performance.

12. Use Interactivity to Prompt Deep Engagement

We will use e-learning’s unique interactive capabilities to support reflection, application, rehearsal, elaboration, contextualization, debate, evaluation, synthesis, and so on—not just in navigation, page turning, rollovers, and information search.

13. Provide Support for Post-Training Follow-Through We will support instruction with the appropriate mix of after-training follow-through, providing learning events that rein-k

force key learning points, marshal supervisory and management k

support for learning application, and create mechanisms that enable further on-the-job learning.

14. Diagnose Root Causes

When given training requests, we will determine whether training is likely to produce benefits and whether other factors should be targeted for improvement. We will also endeavor to be proactive in assessing organizational performance factors—not waiting for requests from organizational stakeholders.

15. Use Performance Support

We will consider providing job aids, checklists, wizards, sidekicks, planners, and other performance support tools in addition to—and as a potential replacement for—standard e-learning interactions.

16. Measure Effectiveness

Good learning cannot be assured without measurement, which includes the following:

a. Measure Outcomes

Ideally, we will measure whether the learning has led to benefits for the individual and/or the organization.

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b. Measure Actual Performance Results

Ideally, an appropriate time after the learning (for example, two to six weeks later), we will measure whether the learner has applied the learning, the level of success, the success factors and obstacles encountered, and the level of supervisor support where warranted.

c. Measure Learning Comprehension and Decision Making during Learning

At a minimum, during the learning, we will measure both learner comprehension and decision-making ability. Ideally, we would also measure these at least a week after the learning.

d. Measure Meaningful Learner Perceptions

When we measure learners’ perceptions, we will measure their perceptions of the following: their ability to apply what they’ve learned, their level of motivation, and the support they will receive in implementing the learning.

17. Iterate in Design, Development, and Deployment We won’t assume that our first pass is right, but we will evaluate and refine until we have achieved our design goals.

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18. Support Performance Preparation

We will prepare learners during the e-learning event to be motivated to apply what they’ve learned, inoculated against obstacles, and prepared to deal with specific situations.

19. Support Learner Understanding with Conceptual Models We believe that performance should be based on conceptual models to guide decisions and that such models should be presented, linked to steps in examples, practiced with, and used in feedback.

20. Use Rich Examples and Counterexamples

We will present examples and counterexamples, together with the underlying thinking.

21. Enable Learners to Learn from Mistakes

Failure is an option. We will, where appropriate, let learners make mistakes so they can learn from them. In addition, where appropriate, we will model mistake making and mistake fixing.

22. Respect Learners

We will acknowledge and leverage the knowledge and skills learners bring to the learning environment through their past experience and individual contexts.

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A Goal to Strive For

Although seemingly ideal, the Manifesto sets forth such a strong contrast to typical design practices that significant movement in the proposed direction will take time. It’s not simply a lack of guidelines that are at fault today, constraining what’s done to the simplest, fastest, and often minimally effective e-learning. We have to realign the pervasive mind-set.

The Manifesto urges designers to recognize the fundamental difference between presentations of information and instruction—to understand the different uses and values of each, and to avoid indiscriminant application.

While the Internet has achieved remarkable and genuinely awe-inspiring capabilities for searching, retrieving, and presenting information, instruction requires a good deal more than this.

I don’t doubt we’ll get to automated instructional design at some point.

Even if it made some egregious errors at first, my guess is it would out-shine much of what’s done today in the stampede to churn out as much courseware in as little time as possible. But research on the artificial intelligence required and attempts to create intelligent tutoring systems have yet to provide practical, suitable systems.

In the meantime, however, there’s much to be gained by incremen-k

tally incorporating the values and principles of the Manifesto into our k

work. Even if adopted just one at a time, the guidelines can contribute hugely to the success of e-learning to the benefit of our learners and their organizations.

The Takeaways

Perhaps because modern technology facilitates rapid development and dissemination of information, the slower and more arduous efforts to use this same technology for serious (read “effective”) instructional uses have been obscured. While access to information at the right time and place can certainly facilitate performance, presentation of information is only one component of what needs to be done to develop skills and motivate performance change.

Substituting presentations for instruction is, sadly, only one of the egregious errors commonly made today. In the rush to do things fast, cheaply, and easily, focus has turned away from well-established instructional values. In the pursuit of fast, cheap, and easy, valuable instructional impact has been lost. Too often, today’s instructional technology 118

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is grossly underutilized and falls far short of the contributions it could otherwise make.

The Serious eLearning Manifesto is an industry effort to return professionalism to the field. Endorsed by hundreds of experienced thought leaders, the Manifesto online at www.elearningmanifesto.org offers the following support to industry workers:

• A list of values that are guiding typical e-learning design and development

• A contrasting list of preferred values known to be much more effective

• Short commentaries on all listed values

• A set of 22 principles that can guide and assist e-learning designers to incorporate the preferred values

• Comments and endorsements posted by hundreds of people working with e-learning

• An opportunity to add your own endorsement to the initiative k

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Chapter 9

Motivation in Learning

I am sometimes asked why I’ve stayed in the field of technology-based instruction for so many years. I can tell you that once you experience some successes in helping people learn and see what is possible through creative uses of technology, the allure of repeating and enhancing those successes is very strong. Let me tell you a story of an early success with the PLATO system:

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True Stories—School Break In

A custodian at a public school in the eastern United States was at his wit’s end.

After repeatedly lecturing teachers and staff about turning off the building lights when they left in the evening, lights were still being found ablaze many mornings when the building was unlocked for the day. No one would admit leaving lights on. To the contrary, everyone assured the custodian that lights were switched off as the last person left.

In desperation, a security guard was posted. Sure enough, the lights went off as the last employee left, but sometime later in the evening the guard heard a noise outside. While he was outside checking, lights came on inside the school building!

The guard quietly reentered the building to see what was happening. To his great surprise, he found a room full of kids hard at work studying math on PLATO

computers. The noise he had heard was the kids getting into the ventilation ductwork so they could crawl through to the classroom. Once in, of course, it was very dark. Scary. So, the kids turned on the lights!

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How often do kids break into school to study? How many situations do you know of in which schoolchildren voluntarily assemble to do yet more schoolwork?

I have had many experiences in which I have personally seen technology-based instruction make a dramatic difference in the lives of learners. Each one of them has given me a craving for more. Each one of them has shown me how much untapped potential lies in e-learning.

One area that definitely deserves more attention is the ability of e-learning to motivate learners. Although outstanding teachers do their best to motivate learners on the first day of class and continually there-after, many e-learning designers don’t even consider the issue of learner motivation, let alone take action to raise it. They tend to focus instead on the meticulous presentation of information or content. Perhaps they believe the techniques teachers use to motivate learners are beyond the capabilities of e-learning. Instead of looking for alternative ways to use the strengths of e-learning technology to address motivation, they focus only on content.

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The e-Learning Equation

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To learn is an action taken by and occurring within the learner. Instructors cannot learn for their learners, and neither can e-learning technology even with all its graphics, animations, effects, audio, interactivity, and so on. Learners must be active participants and, in the end, do the learning.

Learner motivation determines the level of participation in learning activities and the degree to which learners will make the effort needed to learn. Motivation is an essential element of learning success.

With apologies to Albert Einstein, let me advance a conceptual model through a simple equation:

e = m 2 c

where

e = edification (or e-learning outcomes)

m = motivation

c = content presentation

The equation suggests that if there is no motivation ( m = 0), there are no learning outcomes ( e = 0), regardless of how perfectly structured and 122

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presented the content may be. Of course, if the content is also inaccurate or faulty ( c = 0), the amount of learning will also be null. However, as the equation suggests, emphasizing motivation in an e-learning course can have an exponentially greater impact than comprehensive content presentation. This is an essential insight often missed by e-learning designers.

No matter what the speculative value of c (content presentation) might be, when m = 0, e = 0. If you think about it, you know this represents a common situation and outcome. You’ve surely attended a class that went into a topic you didn’t see as valuable or applicable to you. You started thinking about something else and later jerked to attention, realizing you had no idea of what had been said. Your motivations redirected your attention elsewhere and by not attending to what was happening, you had no chance of learning from it.

Motivation and Perception

Our selective perception allows us to filter out uninteresting, unimportant stimuli. It’s vital that we have the capability of ignoring unimportant stimuli; otherwise, we would be distracted by the flood of sensory input coming our way in any moment and unable to focus. Without selective k

perception, we wouldn’t be able to attend properly to important events.

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Of the countless stimuli vying for our attention, most are unimportant and need to be ignored. As we sit in a lecture, for example, we can study the finish of the ceiling, note the styles of shoes people are wearing, and check to see whether our fingernails are trimmed evenly. The more we attend to unimportant things, the more difficult it becomes to attend effectively to those things that might actually be important to us.

Our motivations influence our perceptions and how we filter stimuli. We attend to things of interest, whether those things paint exciting opportunities or present dangers. When we see the possibility of winning a valued prize or avoiding classroom embarrassment by correctly and quickly answering a question, for example, we focus and ready our whole body to respond. At that moment, we become completely oblivious to many other stimuli so we can focus exclusively on responsive behavior.

Conversely, if we expect little benefit from taking action or producing a correct answer, we might remain fully relaxed, not trying to generate any answer, and perhaps not even listening to the question. We might, instead, begin watching the behaviors of those really trying to win. If people-watching provides little entertainment, that ceiling may take on a new fascination. There’s a good likelihood we’ll never even hear the Motivation in Learning

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Motivation Level

Not interested.

Willing to attend

Some interest,

Interested.

Committed to

No attention.

(nice break).

desire to do well.

See value.

improvement.

No learning even

Respond to

Prepare to pass

Attend fully to

Monitor own

while going through

novel items,

test, forget

presentations,

accomplishment;

the motions.

ignore others.

everything afterward.

persist through

find missing info;

confusing or

rehearse, practice,

difficult material.

organize as needed.

No behavioral

No behavioral

No behavioral

Some behavioral

Behavioral

change

change

change

change

change!

FIGURE 9.1

Effect of motivation on behavior.

question or the correct answer, because we’ll be listening to our internal thoughts instead.

Motivation and Persistence

As the gateway to learning, motivation first helps us attend to learning events. It then energizes selected actions we take in response to them.

Viewed from the perspective of whether we achieve targeted behavioral k

changes, instructional success correlates with motivation as shown in k

Figure 9.1.

When we’re motivated to learn, we find needed information even if it’s not so easily accessed. We make the most of available resources.

We stay on track with even a disorganized or inarticulate lecturer. We ask questions, plead for examples, or even suggest activities and topics for discussion. If the lecturer proves unable to assist, we turn to other learners, the library, or even other instructors for the help we need. We might switch to another class if that’s an option, but somehow, if our motivation is high enough, we learn what we want to learn. And to the extent possible under our control, we refuse to waste time in unproductive activities.

Premise 1: Motivation is critical for learning. If motivation to learn is low, very little if any learning will occur.

Premise 2: If motivation to learn is high, learning will occur even if instructional materials are poor and minimal assistance is available.

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Instructional Design Priorities

As we’ve seen, motivation controls our perception—what we see, hear, and experience. Motivation also fuels our persistence to achieve selected goals. Strong motivation, therefore, becomes critical for sustained learning.

There may be exceptions to this statement, as there are to most rules; however, many situations that appear to be exceptions are not.

We learn things, for example, from simple observation. We learn from traumatic events, from surprises, and from shocking happenings. Are these exceptions? We find concurrent motivations at work even in these cases. Our motivations to belong, to be safe, to avoid unemployment, or to win can all translate readily into motivation to learn. They cause what appears to be involuntary learning but is, nonetheless, motivated learning.

Learning motivation is nearly always energized by other motivations, whether negative (such as avoidance of embarrassment, danger, or financial losses) or positive (such as competence, self-esteem, recognition, or financial gain).

Conclusion: As our formula, e = m2 c, tells us, it is more important to bolster learner k

motivation than it is to articulate content clearly.

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Although it seems logical and is certainly the norm, delineation of content is almost always the wrong initial focus of instructional design. Designers should consider what can be done to be sure learners are well motivated initially and remain motivated throughout the learning experience.

E-Learning Design Can Heighten

as Well as Stifle Motivation

In a self-perpetuating way, e-learning can help build the motivation needed for success. Heightened motivation increases the effectiveness of e-learning and therefore promotes more learning. This self-energizing system should be fostered.

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The alternative is an opposing, deadly cycle. Poor e-learning saps any motivation learners have. As learners suspect their e-learning work is of little value, they pay less attention and participate less, thus reducing the possibility that the learning experiences will be of value. With evidence that e-learning isn’t working for them, learner interest and motivation continue to drop. This self-defeating system should, of course, be avoided.

E-Learning Dropouts

Many e-learning designs tacitly assume, expect, require, and depend on high learner motivation, as evidenced by the good measure of persistence it takes just to endure them. If learner motivation wanes before the completion of instruction, learners drop out mentally, if not physically. Know what? This is exactly what is reported: 70 percent of learners drop out of their e-learning applications without completing them (Islam, 2002).

Optimists claim (or hope) that high e-learning dropout rates simply reflect the attrition of learners who have gotten all they needed. Learners quit, it is reasoned, because their needs have been satisfied, and they feel ready to meet their performance expectations. This may be their excuse, but I doubt that learners feel their initial e-learning experiences were so successful that they need not complete the training.

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Moviegoer: This movie is so good! Let’s leave now. I don’t care how it ends.

Reader: This book is so good I don’t think I’ll read any more of it.

E-Learner: This e-learning application is so good, I think I’ll quit before I learn anything more.

Does this logic sound right to you? e-Learners more likely drop out because they can’t take the boredom and frustration than because the instruction has served their needs so well nothing more could be of value.

The time, effort, and patience required are greater than the perceived benefit. So they quit.

Even Excellent Instruction Must Be Sold

to the Learner

To create successful e-learning—or any successful learning program, for that matter—we need to make sure that value to the learner really is there.

But perhaps just as important, we also need to make sure learners see and appreciate that value in concrete terms. Each learner must buy into the value of the learning—not just in general but for specific, personally 126

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meaningful benefits. In other words, we need to sell learners on the truthful proposition that participation will provide benefits that make learning worth the time and effort. Doing so will create vital initial motivation and give the program a chance to succeed.

I’m not talking about marketing spin meant to mask a miserable experience (although if the experience is going to be miserable, it’s more important than ever to maximize learner motivation). Nor do I suggest cajoling learners or propositioning them: “If you struggle through this, you’ll be much the better for it.”

Adult learners are sensitive to manipulation. If they feel they are being manipulated, they are likely to react defensively. They may become motivated, but motivated to prove the instruction was a waste of their time.

Active rebellion, of course, is even worse than no motivation. Everyone has much to gain if the learner sees the personal advantages of learning.

Again, the value must truly exist and learners must be able to envision and appraise the benefit firsthand.

All of this is done to ensure that the m in e = m 2 c reaches the highest value possible.

It Isn’t Bad News That Motivation

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Is Essential

k

Knowing the importance of learner motivation gives us an explanation behind many e-learning failures and points the way to success. This is good news as it helps us understand our task more clearly.

Actually, even better news lies in knowing motivation levels change from situation to situation and from moment to moment. In other words, motivation levels are context-sensitive and can be influenced. We don’t have to be satisfied with the levels of motivation learners carry into a learning event. If a learner’s motivation is low, we can do things that are likely to raise it.

e = m 2 c

As noted in contrast to Einstein’s equation ( e = mc 2), I squared the motivation factor. This is done to emphasize not only that motivation is essential, as would be indicated simply by e = mc, but also that the learning outcome is more likely to be affected by motivational factors than it is by content presentation. Again, if motivation is high, learners will make the most of available content information. If motivation is low, refining presentation text and graphics may help to improve attention somewhat, but not to the same level as heightening motivation.

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It’s also critical that these two elements complement each other. Content can be structured and presented in ways that are sensitive to the issue of motivation. That is, just as confusing and incomprehensible content presentation can counteract motivation (i.e., c can be 0), selection of the right content at the right time can stimulate motivation.

Further, interactivity allows learners to act on their motivations, to choose what’s relevant to them at a particular time. Seeing their initiative advance them toward meaningful goals reinforces motivation. We might, therefore, extend our equation to include the value of interactive design, adaptability to individual needs, and learner control: e = m 2 ci

where

i = interactive adaptability

The equation is not to be taken in any literal, computational sense, of course. We have no practical units of measurement applicable to content presentation or standardized measures of motivation. However, the factors that determine learning as shown here are operative and easily observed in real learner testing. The equation serves as a reminder to pay attention to k

each and every factor.

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Motivation to Learn versus Motivation

to Learn via e-Learning

Motivation has focus. It has a goal. We can and perhaps always do have a varying set of simultaneous motivations with their accompanying individual goals. They can be supportive of, or competitive with, each other.

In certain contexts, one motive will have sufficient strength to dominate all our attention. At these moments, stimuli unrelated to the dominant motivation won’t even reach our consciousness.

Realizing the context sensitivity of motivations, we can also understand that e-learning events have the power to both increase and to decrease learner motivation. Like every other aspect of human behavior, learner motivation is complex, but a simple view of motivation is sufficient to reveal powerful design principles for interactive instruction.

The simple view is this:

• If we want to learn, we will find a way.

• If we don’t want to learn, we won’t.

• If we want to learn but the e-learning application isn’t working for us, we will find a way around it and turn to something else.

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When we want the cost savings, quality control, easy access, and other advantages of e-learning, the question becomes, How do we get learners to want to learn via e-learning?

The answer: Seven Magic Keys (see Chapter 10).

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Chapter 10

Seven Magic Keys

to Motivational

e-Learning

Yes, I actually do have seven “Magic Keys” to making e-learning experiences compelling and engaging. As described in the previous chapter, motivation is essential to learning and one of the most important success k

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factors for us to consider in designing and delivering instructional events.

Creating great e-learning is never as easy as following a recipe. I can’t emphasize enough that there is a lot to know about instructional design and that although good e-learning design may look simple, it isn’t. A great idea will often look obvious after it’s been implemented, but uncovering the simple, “obvious” ideas can be a very challenging task. The keys to enhancing learning motivation put forth in this chapter are magical because they are such reliable and widely applicable techniques.

Their presence or absence correlates well with the likely effectiveness of an e-learning application—at least to the extent that it provides motivating and engaging experiences. Thankfully, these features are not often more difficult to implement than many less effective interactions. These are realistic, practical approaches to highly effective e-learning.

Let’s begin with Table 10.1, which lists seven ways to enhance motivation—the Seven Magic Keys—and then discuss them in more detail with examples.

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TABLE 10.1

Ways to Enhance Learning Motivation—

the Seven Magic Keys

Key

Comments

1.

Build on anticipated

Help learners see how their involvement in the e-learning outcomes.

will produce outcomes they care about.

2.

Put the learner at risk.

If learners have something to lose, they pay attention.

3.

Select the right content

If it’s meaningless or learners already know it, it’s not for each learner.

going to be an enjoyable learning experience.

4.

Use an appealing

Novelty, suspense, fascinating graphics, humor, sound, context.

music, animation—all draw learners in when done well.

5.

Have the learner

Having people attempt real (or “authentic”) tasks is much perform multistep tasks.

more engaging than having them repeat or mimic one step at a time.

6.

Provide intrinsic

Seeing the positive consequences of good performance feedback.

is better feedback than being told, “Yes, that was good.”

7.

Delay judgment.

If learners have to wait for confirmation, they will typically reevaluate for themselves while the tension

mounts—essentially reviewing and rehearsing!

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Using the Magic Keys

You don’t have to use every Magic Key in every application to make them effective. You would be challenged to do it even if you were so inclined.

However, the risk of failure rises dramatically if you employ none of them.

Although it’s rather bold to say, I contend that if you fully employ just one of these motivation stimulants, your learning application is likely to be far more effective than the average e-learning application. Everything else you’d do would become more powerful because the learner would be a more active, interested participant.

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1

Magic Key 1: Build

on Anticipated

Outcomes

We have motives from the time we are born. As we mature, learned motives build on and expand from our instinctive motives. All our learned motives can probably be traced to our instinctive motivations in some way, but the helpful observation here is that human beings have an array of motivations that can be employed to make e-learning successful.

A simple and effective technique to build interest in an e-learning application is to show how it will bring learners benefits like comfort, competence, influence, self-esteem, and other prime motivations. The question is how to communicate those benefits.

Instructional Objectives

Much has been made of targeted outcome statements, or instructional k

objectives, perhaps beginning with Robert Mager’s insightful and pragmatic k

how-to books on instructional design, such as Preparing Instructional Objectives (Mager, 1997c), Measuring Instructional Results (Mager, 1997b), and Self-esteem

Respect

Competency

Money

Power

Control

Safety

Comfort

FIGURE 10.1

Prime motivators.

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Goal Analysis (Mager, 1997a). Instructional designers are taught to prepare objectives early in the design process and to list learning objectives for learners at the beginning of each module of instruction. Few classically educated instructional designers would consider omitting the opening list of objectives.

Mager provides three primary reasons why objectives are important: Objectives … are useful in providing a sound basis for (1) Selecting or designing instructional content and procedures (2) Evaluating or assessing the success of the instruction (3) Organizing learners’ own efforts and activities for the accomplishment of the important instructional intents. (Mager, 1997c, p. 6)

There’s no doubt about the first two uses. If you don’t know what abilities you are helping your learners build, how can you know if you’re having them do the right things? As I’ve emphasized before, success depends on people doing the right thing at the right time. If no declaration of “the right thing” is established, you can neither develop effective training nor k

measure the effectiveness of it—except, perhaps, by sheer luck. Objectives k

are a studied and effective way of declaring what the “right thing” is. As Mager says, “if you know where you are going, you have a better chance of getting there” (Ibid).

It’s the third point that’s of interest here—using objectives to help learners organize their learning efforts. Certainly, objectives can help. When objectives are not present, learners must often guess what is important. In academic or certification contexts when objectives are not shared, learners must guess what will be included in the all-important final examination.

After they have taken the final exam, learners know how they might have better organized their learning efforts. But, of course, it’s too late by then.

There is a bit of gamesmanship here that some instructors use. They justify it by saying comprehensive tests would be too difficult to prepare, require too much time to take, and be too laborious to score. If students don’t know what’s going to be tested, they’ll have to prepare themselves for testing on all topics, even if the test only covers a sampling.

There’s logic to it, but definitely downsides as well. Are the topics which are not tested unimportant? If scores are to be reflective of performance mastery, what are we to assume about untested skills? Aren’t some performance skills more important than others? And if so, shouldn’t 134

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learners be aware of this so they can concentrate their study on the most important things? Aren’t some objectives just enablers, the mastery of which has little value on its own? Do courses impart so many useful skills they can’t all be tested?

For objectives to provide benefits to learners, learners have to read, understand, and think about them. Unfortunately, learners rarely spend the time to read objectives, much less use them as learning tools. Rather, they discover that the objectives screen is, happily, a screen that can be skipped over quickly. Learners think, “I’m supposed to do my best to learn whatever is here, so I might as well spend all my time learning it rather than reading about what I’ll learn.” Next.

Lists of Objectives Are Not Motivating!

Let’s just admit it: Listing objectives at the start of a courseware module looks professional and makes us feel we’ve done the right thing, but those lists probably aren’t going to contribute much to the learning experience.

Many designers hope objectives will not only help learners organize their study but also enhance their motivation to learn the included content. Will they? Obviously, objectives do nothing if learners don’t read them as we’ve said. But just how readable are they? Following Mager, k

knowledgeable instructional writers know objectives should have three k

parts (see Figure 10.2).

Instructional writers have learned the importance of writing behavior-based objectives that are observable and measurable. (See Table 10.2 to get the gist of it.)

Measurable behavioral objectives are, indeed, critical components to guide the design of effective training applications. Designers need such objectives, and none of these components should be missing from their design plans. But the question here is about their use as learning motivators.

You can hardly yawn fast enough when you read a stack of statements containing “proper” objectives like:

Conditions under which

performance must be demonstrated

A description of behavior that

demonstrates learning

The criterion for determining

acceptable performance

FIGURE 10.2

Components of instructional objectives.

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TABLE 10.2

Behavioral

Objectives—Acceptable Verbs

Not Measurable

Measurable

To know

To recall

To understand

To apply

To appreciate

To choose

To think

To solve

Given a typical business letter, you will be able to identify at least 80 percent of the common errors by underlining inappropriate elements or placing an “X” where essential components are missing.

After reading a few of these objectives, will you be motivated? Sure.

You’ll be motivated to skip the rest and move on. Objectives are important for us as designers and attainable outcomes are valuable to learners, but listing such statements as these in bullet points at the start of a program is boring and ineffective. If there are better ways to motivate learners, what are they?

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How about Better-Written Objectives?

We can and should write objectives in more interesting ways and make them more relevant to the learner. Indeed, when they’re deciding just how much energy and involvement to commit, learners want to know in what way the material will be meaningful to them personally (i.e., how the instructional content relates to their personal network of motivations).

Effective objectives answer the question and give motivation a little boost (see Table 10.3).

TABLE 10.3

More Motivating Objective Statement

Instead of Saying …

You Could Say …

After you have completed this chapter,

In a very short time, say about two hours,

given a list of possible e-learning

you will learn to spot the flaws in typical

components, you will be able to select

designs that make e-learning deathly

the essential components of high-impact

boring and you will be able to fix them.

e-learning.

Ready?

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Remember the more fully learners recognize and value the advantages of learning the material at hand, the more effective the material will be.

But if you agree on this point, you might wonder whether a textual listing of objectives is really the best way to sell anyone on learning. Good question. Yes, we can do better.

Don’t List Objectives

If learners aren’t going to read objectives, even valuable and well-written objectives, listing them at the beginning of each module of instruction isn’t a very useful thing to do. In fact, it may do more harm than good since it communicates to learners from the beginning that yours will be just another typical boring e-learning experience.

In e-learning, we have techniques for drawing attention to vital information. We use interactivity, graphics, and animation—in short, all the powers of interactive multimedia—to help learners focus on beneficial content. Why, then, shouldn’t we use these same powers to portray the objectives and sell the learning opportunity to the learner?

Instead of just listing the objectives, provide meaningful and memorable experiences.

Example 1: Put the Learner to Work

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Perhaps the clearest statement of possible outcomes comes from setting the learner to work immediately on a stated task. If learners try and fail, at least they’ll know what they are going to be able to do when they complete the learning far more clearly than they could glean from reading a list of objectives.

In this award-winning example, Expedia needed to train all their phone-based customer service representatives on a vast amount of travel knowledge for every major city in the United States. Traditional methods of informative presentations with assessments had not been effective, leading Expedia to a learner-centric design focused on the authentic on-the-job activities trainees could expect to perform. The content ranged from information about local attractions to neighborhood characteristics, hotels, and transportation choices. (See Figure 10.3.) Let’s walk through the example. Learners are presented with a series of customers who wish to book a dream vacation. The performance task requires learners to choose the best lodging, attractions, activities, and transportation based on simulated customers profiles and preference-revealing quotes. (See Figure 10.4.)

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Example

Expedia

Expedia Customer Service Training

https://www.alleninteractions.com/expedia

Context: Customers call in to request their perfect vacation in a specific city. Situations are presented along with a map of the city and a catalog of vacation choices.

Challenge: To create the perfect vacation by matching the best lodging, attractions, must-sees, and transportation choices to the customer’s wants and needs.

Activity: Using an on-screen map, navigate to the best neighborhood for the customer and choose the most appropriate hotel. Then choose the best attractions and transportation choice. All choices come with on-demand ability to learn more about them. After submitting the k

selected trip, the learner must fine-tune the trip, repeatedly if k

necessary, until a completely satisfied customer is attained.

Feedback: Upon configuring each vacation to the customer’s satisfaction, a customer comment card is presented with specific feedback on each choice, either positive or negative.

To find the best lodging choice, a comprehensive list of neighborhoods is presented with descriptions. Each neighborhood contains a number of hotels, at least one of which matches the customer needs and preferences.

Other categories contain simple lists with item descriptions that provide sufficient information to match specific needs/wants. (See Figure 10.5.) Once the entire trip has been planned, the learner receives a comment card with customer feedback. (See Figure 10.6.)

The learner must then correct all problems with the trip until the customer is completely satisfied. (See Figure 10.7.) At that point, another customer calls in with different needs and preferences. Once learners have repeated enough exercises, they have much higher prospects of getting a trip right on the first try. A trip planned successfully on the first try is quite rewarding. This learner-centric design 138

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FIGURE 10.3

A meaningful task challenge takes the place

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of traditional learning objectives.

with multiple scenarios effectively motivates learners to familiarize themselves with each neighborhood, hotel, attraction, and so forth during the pursuit of the perfect vacation.

You might be concerned that some failures, especially early on, will frustrate or demoralize learners. It is always an appropriate concern that initial challenges may produce more negative frustration than positive motivation. Interactive features must be provided to protect learners from becoming overwhelmed and discouraged. Either the software and/or the learner must be able to adjust the level of challenge when appropriate.

Please see Magic Key 2 for a discussion of risk management.

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FIGURE 10.4

Jumping right in: The initial activity is interesting and authentic.

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FIGURE 10.5

Listening carefully: Learners need to take cues from the customer’s profile and comments.

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FIGURE 10.6

Consequences provide memorable feedback.

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FIGURE 10.7

A personal thank-you provides effective rewards.

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Example 2: Drama

Motivation is not an exclusively cognitive process. Motivations involve our emotions and our physiological drives, as well. Good speakers, writers, and filmmakers are able to inspire us to take action, to reevaluate currently held positions, and to stir emotions that stick with us to guide future decisions.

Imagine this scenario. Airline mechanics are to be trained in the process of changing tires on an aircraft in its current position at a gate. You can easily imagine the typical first page of the training materials to read something like this:

At the completion of this course, you will be able to:

■ Determine safety concerns and proper methods of addressing each.

■ Confirm and crosscheck location of tire(s) to replace.

■ Select appropriate chock or antiroll mechanisms.

■ Secure chocks according to approved procedures.

■ Obtain appropriate replacement tire.

■ Etc.

Now imagine this approach:

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You press a key to begin your training. Your computer screen slowly fades k

to full black. Lightning crashes and your screen flickers bright white a few times. You see a few bolts of lightning between the tall panes of commercial windows just barely visible. Through the departure gate window, you see an airplane parked at the gate. The rain is splashing off the fuselage. A gust of wind makes a familiar threatening sound.

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The scene cuts to two men in yellow rain slickers shouting at each other to be heard over the background noise of the storm and airport traffic.

“You’ll have to change that tire in record speed. The pilot insists there’s a problem, and that’s all it takes. We have to change it. There’s going to be a break in the storm and there are thirty-some flights hoping to get out before we’ll probably have to close down again.”

“No problem, Bob. We’re on it.” Return to the windows, where we now see people at the gate—a young man in business attire is pacing worriedly past an elderly woman seated near the windows.

“Don’t worry, young man. They won’t take off if the storm presents a serious danger. Even in a storm and with all the possible risks of air travel, I still think it’s the safest way for me to get around.”

“Oh, thanks, ma’am. But you see, my wife is in labor with our first child. I missed an earlier flight by ten minutes, and now this is the last one out tonight. I’m so worried this flight will be delayed for hours—or worse, even cancelled due to weather. I’m not sure what my options are, but I need to get home tonight.”

Back outside, Bob runs up to three mechanics as they run toward him k

in the rain.

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“All done, Bob. A little final paperwork inside where it’s dry, and she’s set to fly.”

“Your team must have set a record. Even under pleasant circumstances, I don’t know any other employees who could have done such a good job so fast. The departure of this aircraft won’t be delayed one minute because of that tire change. A lot of people will benefit from your work tonight.

“This is going to headline the company’s newsletter!”

I hope you can see how this dramatic context can much more effectively communicate the learning objectives and motivate learners to pursue them.

Who wouldn’t want to be a hero in this circumstance? Who wouldn’t begin thinking, “I’ll bet I could learn to do that … maybe even do it better.” And, then, “I wonder what it takes. Hope I get a chance to find out in this learning program.”

An emotion-arousing motivational event like this can be done through everything from a few stick figures with audio to a full fidelity video of professional mechanics or actors. The expense can be kept small, yet the benefit to performance and learning can be invaluable.

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2

Magic Key 2: Put

the Learner at Risk

When do our senses become most acute? When are we most alive and ready to respond?

It’s when we are at risk. It’s when we sense danger (even imagined danger) and must make decisions to avert it and protect ourselves. It’s when we see an opportunity to win accompanied by the possibility of losing.

Games energize us primarily by putting us at risk and rewarding us for success. Although it’s easy to point to the rewards of winning as the allure, it is also the energizing capabilities of games that make them so attractive.

It feels good to be active, win or lose. Risk makes games fun to play.

Proper application of risk seems to provide optimal learning conditions. I used to think, in fact, that putting learners at some level of risk was the only effective motivator worth considering in e-learning and the most frequently omitted essential element. Although I have identified k

other essential powerful motivators—the other Magic Keys—I continue k

to believe that risk is the most effective in the most situations. There are pros and cons, however (see Table 10.4).

Problems with Risk as a Learning

Motivator

Consider instructor-led training for a moment. In the classroom, putting the learner at risk can be as simple as the instructor posing a question to an individual learner. The risk of embarrassment goes far beyond failing to TABLE 10.4

Risk as a Motivator

The Positives

The Negatives

Energizes learners, avoids boredom

May frighten learners, causing anxiety that

inhibits learning and performance

Focuses learners on primary points and

May rush learners to perform and not allow

on performance

enough time to build a thorough

understanding

Builds confidence in meeting challenges

May damage confidence and self-image

through rehearsed success

through a succession of failures

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answer correctly. Public performance can affect social status, social image, and self-confidence for better or worse. Even if we’re in a class in which we know none of our classmates, being asked a question typically causes a rush of adrenaline because of what’s at stake.

Competition is a risk-based device used by many classroom instructors to motivate learners. In some of my early work with PLATO, I managed an employee who considered one of PLATO’s greatest strengths to be its underlying communication capabilities that were able to pit multiple learners against one another in various forms of competitive interplay.

Although these capabilities were often used just for gaming, he was intrigued with the idea of using them to motivate learners.

Competitive e-learning environments can certainly be created, but, unfortunately, pitting learners against one another may create a counter-productive win/lose environment. It may be true that even the losers are gaining strengths, and they may be effectively motivated to do their best as long as the situation or their competitors don’t overly intimidate them. Anonymity can help. But it’s difficult to prevent nonwinners from seeing themselves as losers. As one axiom puts it: Winners focus on winning.

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Losers focus on winners.

As trainers, our goal is to make all learners winners. And to that end, we need learners focusing on skill development, not each other.

Private versus Social Learning

Environments

There are advantages to being in the company of others when we learn.

We are motivated to keep up with other learners and benefit from their questions. We learn from watching the mistakes and successes of others.

Communication with others helps round out our understanding. In addition, successful public performance gives us confidence—a performance attribute that can be lacking when learning and practice take place only in private.

However, the risk of public humiliation causes, for many, an immediate and unpleasant rush of adrenaline. While a successful public performance can easily meet our two essential criteria of being a meaningful and memorable learning event, the event may be memorable because of the fear associated with it. And although traumatic experiences may be Seven Magic Keys to Motivational e-Learning

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memorable, the emotional penalty is too high. For many individuals, practice in a private environment avoids all risk of humiliation and can bring significant learning rewards.

Interestingly, research finds people respond to their computers as if they were people (Reeves and Nass, 1999). We try to win the favor of our computers and respond to compliments extended to us by software. Quite surprisingly, solo learning activities undertaken with the computer have more characteristics of social learning environments than one would expect. Talented instructional designers build personality into their instructional software to maximize the positive social aspect of the learning environment.

Asynchronous electronic communications, such as e-mail, and synchronous learning events, such as are now possible with various implementations of remote learning, can build a sense of togetherness. Where resources are available to assist learning through such technologies, a stronger social learning environment can be offered, although in this case, just as with other forms of e-learning, design of learning events, not the mere use of technology, determines the level of success achieved.

For many organizations, though, one of the greatest advantages of e-learning comes from its constant availability. When there’s a lull in their k

work, employees can be building skills rather than unproductively waiting k

for more work assignments or scheduled classes to roll around. Instant availability and the possibility of spending whatever time happens to be available whenever it is available are important benefits of e-learning.

Unless you can count on the availability of appropriate colearners at all times, it is probably best to design independent learning opportunities at least for a good share of your learning events.

Don’t Baby Your Learners

Some organizations are very concerned about frustrating learners, generating complaints, or simply losing learners because they were too strongly challenged. They are so concerned, in fact, that they make sure learners are unlikely to make mistakes. Learners can cruise through the training, getting frequent rewards for little accomplishment.

The organization expects to get outstanding ratings from learners on surveys at the end of riskless courses, and may indeed get them even if no significant learning occurred (Thalheimer, 2016). But even better ratings may be achieved by actually helping learners improve their skills. More importantly, both individual and organizational success might be achieved.

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A lot is learned from making mistakes. And people like overcoming challenges! Look at how many people go back to the golf course week after week and spend a fair amount of money for the privilege of overcoming challenges.

Go ahead, break the rules and put learners at some measure of risk.

Then provide structures that avoid the potential perils of doing so. Here are some suggestions:

Avoiding Risk Negatives

The advantages of risk are great, but they don’t always outweigh the negatives. Fortunately, the negatives can be avoided in almost every instance, so that we’re left only with the truly precious positive benefits. Effective techniques include:

• Allowing learners to ask for the correct answer. If learners see they aren’t forced into a risk and can back out at any time, learners often warm up to taking chances, especially when they see the advantages of doing so.

• Allowing learners to set the level of challenge. Low levels of challenge become uninteresting with repetition. Given the option, learners k

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will usually choose successively greater challenges.

• Complimenting learners on their attempts. Some encouragement, even when learner attempts are unsuccessful, does a lot to keep learners trying. It is important for learners to know that a few failures here and there are helpful and expected.

• Providing easier challenges after failures. A few successes help ready learners to take on greater challenges.

• Providing multiple levels of assistance. Instead of all or nothing, learners can ask for and receive help ranging from general hints to high-fidelity demonstrations.

Using these techniques, it is possible to offer highly motivating e-learning experiences with almost none of the typical side effects that accompany learning risk in other environments.

Staying Alive

Why do kids (and adults) play video games for hours on end? Shortly after home versions of games like the classic Super Mario Bros. became Seven Magic Keys to Motivational e-Learning

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FIGURE 10.8

Computer games successfully teach hundreds of facts and procedures.

available, our son and all the children on our block knew every opportunity hidden throughout hundreds of screens under a multiplicity of changing k

variables. They stayed up too late and would have missed meals, if allowed k

to, in order to find every kickable brick in walls of thousands of bricks (see Figure 10.8). They learned lightning-fast responses to jump and duck at exactly the right times in hundreds of situations. And for what? Toys?

Money? Vacations? Prizes? Nope.

We play these games as skillfully as possible for the reward of being able to continue playing, to see how far we can get, to avoid dying and having to start over, to feel good about ourselves, and to enjoy the energy of a risky, but not harmful, situation.

In the process of starting over (and over, and over), we practice all the skills from the basics through the recently acquired skills, overlearning them in the process and becoming ever more proficient. We take satisfaction in confirming our abilities as our adrenaline rises in anticipation of reencountering the challenges that doomed us last time.

Imagine, in contrast, the typical schoolteacher setting out to teach students to identify which bricks hide award points. There would be charts of the many thousands of bricks in walls of various configurations. You can just imagine the homework assignments requiring students to memorize locations by counting over and down so many bricks and circling the correct ones. Students would be so bored that behavior problems would soon erupt.

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The teacher would earnestly remind students that someday in the future, they would be glad they could identify the bricks to kick. Great success would come to those learners who worked diligently to pinpoint all the correct bricks. After several years of pushing groups of students through these exercises, a bored teacher might turn to e-learning for help. With a happy thought of transferring the teaching tedium to the computer, the teacher would likely create an online version of the same grueling instructional activities.

To me, this sounds similar to a lot of corporate training. Although we might not see our trainees pulling one another’s hair, making crude noises, and writing on desks, we can be sure they will be checking e-mail, catching up on social media, and even ordering holiday gifts online when learning tasks are so uninteresting.

Just teaching one task within the complex behaviors of the venerable Super Mario Bros. player would be a daunting challenge for many educators; yet, millions of people have become adroit at these tasks with no instruction— at least with no typical instruction. Why aren’t these obviously effective instructional techniques applied to e-learning, with all its interactive multimedia capabilities?

Good question. Why not, indeed!

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Repetition and Goals

Repetition through practice is a primary way of preventing memory loss (see Figure 10.9). Although strong stimuli, such as traumatic and emotionally charged events, can stick with us without repetition, new information and skills often require rehearsing.

The good news is that e-learning is a perfect medium for practice, having infinite patience and the ability to retrieve practice exercises from a pool if not to actually generate as many exercises as may be needed.

Stimuli

Attention

Rehearsal

Sensory

Short-Term

Long-Term

Memory

Memory

Memory

Memory Loss

Memory Loss

Memory Loss

FIGURE 10.9

Learning through rehearsal

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The bad news is that practice is often boring. Think of all the things we cajole our children into practicing as they grow up: alphabet, multiplication tables, notes of the base and treble clef, spelling, etc. We often search for more ways to get kids to practice and have to get creative in our methods. And this is exactly what we must do in e-learning design as well.

This is where goals come in. By establishing performance goals, we draw attention away from repetition and toward results—the progress toward goal achievement. If learners fail over and over again, they will generally want to stop. But by setting increasingly challenging goals, learners will receive interim and practice-sustaining rewards. Visible progress keeps learners trying.

Adding risk into such a framework is rather straightforward and can increase motivation to persevere to a level of mastery. Having incremental goals, perhaps the most obvious means of harnessing risk is to limit the number of attempts permitted at each advanced level before setting the learner back a level.

Let’s look at a very successful example.

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Example

Short-Order Chef

E

http://zebr.as/1KJiQWw

Context: A short-order cook is presented with customer orders, ranging from easy to very complex. These orders are presented in the visual environment of a grill, with raw food items, a clock, and a server whose attitude changes based on responsiveness of the kitchen.

Challenge: Place items on the grill in the right order and at the right time to serve a timely, quality meal with all items properly cooked and none having gotten cold waiting for others to finish preparation.

Learners risk having to start an order all over if some items get cold before others are finished. If the learner cannot produce a satisfactory order in acceptable time, the learner will either have to replay the current level or, after repeated failure, drop back a level. Orders increase/decrease in complexity based on success/failure.

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Activity: Drag and drop food from storage bins onto the cooktops and when properly cooked, move items onto the appropriate plates and serve them to the customers. As orders are completed successfully (both quality and time), learners advance to more difficult levels.

Feedback: Graphic imagery for cooked, burned, and cold food reveals the consequences of learner actions, while a server smiles or frowns.

The top chef also provides quality checks on the served order.

Learners are put to “work” almost immediately not just to make the learning active but also as a means of determining the right level of challenge and practice needed for each learner (see Figure 10.10).

Adequate but minimal instruction is given so learners can begin showing what they know, can, and can’t do almost immediately (see Figures 10.11 and 10.12). The amount of instruction and the level of challenge adapt to the learner throughout.

As learners progress, the variety and number of items needing to be served simultaneously increases. In Figure 10.13, the apprentice cook is facing “Challenge 4” which includes a total of six items, three for each of two plates. All items are cooking and this learner was smart enough to k

align cooking items to plates to minimize having to spend time rechecking k

FIGURE 10.10

Alert to active learning appears even in the initial screen.

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FIGURE 10.11

Active learning begins almost immediately.

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FIGURE 10.12

A quick performance-monitored walkthrough leads to more detailed instruction only if needed.

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tickets when it becomes time to plate. Customer wait time is shown and keeps the pressure on.

Because each food item requires a different amount of cooking time, all six items will be ready to plate together only if they started cooking in the proper sequence and were timed properly. The cook will then need to get items to the plates quickly enough to prevent those items still cooking from burning and those items plated from getting cold.

There are many ways to fail a challenge, and for most people a considerable amount of practice is necessary to reach and meet the final goal.

Feedback (see Figure 10.14) is detailed after each challenge is completed or time runs out.

Resources are available for learners. They inform how to cook each item and how long. Learners can reference the information between challenges and even during them, but if referenced during a challenge, cooking items may burn if in progress while the learner is away. To increase the risk of burned items or unacceptably slow service, when learners return to the kitchen from looking up information, they find a delaying mess of broken eggs to pick up (Figure 10.15). “Oh, no!” Learners are effectively encouraged to internalize critical information rather than looking everything up as they try to cook.

k

Learners are given only a couple of chances to succeed at each level.

k

The major risk is that multiple failures will produce the dreaded black FIGURE 10.13

Challenge levels advance to demand authentic skilled performance.

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FIGURE 10.14

Feedback notes all errors specifically and indicates this learner can try this level again.

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FIGURE 10.15

Challenge levels advance to demand authentic skilled performance.

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FIGURE 10.16

The risk of dropping down a level is a constant motivator.

screen (Figure 10.16) and set the learner back a level where it’s necessary to work back up. It’s even possible that the learner will regress more than k

k

one level and need to climb back up through continuous successes.

This use of risk is amazingly effective in getting learners to practice.

Learners witness that just knowing what to do isn’t nearly enough to perform successfully and that practice really is necessary. But practice can be fun and very much is in this e-learning. Whether relevant or not to them personally, we’ve found almost everyone who gives this lesson a try feels compelled to reach and succeed at the top level. But it’s unlikely you’ll get there without some intensive practice.

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3

Magic Key 3: Select

the Right Content

for Each Learner

What’s Boring?

Long presentations of information you already know, find irrelevant, or can’t understand.

What’s Interesting?

• Learning how your knowledge can be put to new and valuable uses

• Understanding something that has always been puzzling (such as how those magicians switch places with tigers)

• Seeing new possibilities for success

• Discovering talents and capabilities you didn’t know you had k

•

k

Doing something successfully that you’ve always failed at before Moral? It’s not enough for learners to believe there is value in prospective instruction (so that they have sufficient initial motivation to get involved). There must also be real value to sustain the required engagement. The content must fit with what they are ready to learn and capable of learning.

Individualization

From some of the earliest work with computers in education, there has been an alluring vision: a vision that someday technology would make practical the adaptation of instruction to the different needs of individual learners. Some learners grasp concepts easily, whereas others need more time, more examples, more analogies, or more counterexamples. Some can concentrate for long periods; others need frequent breaks. Some learn quickly from verbal explanations, others from graphics, and others from hands-on manipulation. The vision saw that, while instructors must generally provide information appropriate to the needs of the average learner, technology-delivered instruction could vary the pacing and selection of content as dictated by the needs of each learner.

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Not only could appropriate content be selected for each learner’s goals, interests, and abilities, but instruction could also be adapted to interests, cultural backgrounds, and even personal lifestyles.

Perhaps no instructional path would ever be the same for two learners. It would be possible for some learners to take cross-discipline paths, whereas others might pursue a single topic in great depth before turning to another topic. Some learners would need to keep diversions to a minimum as they worked on basic skills; others would benefit from putting basic skills into real-life contexts almost from the beginning. Areas of potential individualization seemed almost endless and possible. And given enough learners across which to amortize the cost of development, the individualization could be quite affordable.

Many classroom instructors do their best to address individual needs, but they know there are severe limits to what they can do specifically for individual learners, especially when there are high levels of variation among learners in a class. The pragmatic issues of determining each learner’s needs, constructing an individual road map, and communicating the plan to the learner are insurmountable even without considering the mainstay of the typical instructor’s day: presenting information. It’s difficult to handle more than a small number of learners in a highly indi-k

vidualized program without the aid of technology. With e-learning, we do k

have the technology necessary for truly exciting programs that can adapt effectively to the needs of individual learners. Through technology, the delivery and support of a highly individualized process of instruction is quite practical, and there are actually many ways instruction can be fitted to individual needs.

Fortunately, it’s not necessary to get esoteric in the approach. The simplest individualized approaches contribute great advantages over one-size-fits-all and often have the greatest return on investment. They may require an expanded up-front investment, of course, as there’s hardly anything cheaper than delivering one form of the curriculum in the same manner to many learners at the same time. But there are some practical tactics that result in far more individualized instruction than is often provided.

Let’s look at some alternative paradigms to see how instruction has been individualized. Our emphasis here will be on just one parameter—content matching. Efforts to match preferences, psychological profiles, and other learner characteristics are technically possible.

But where we haven’t begun to match content to individual needs, we’ll hardly be ready for the more refined subtleties of matching instructional approaches to learners.

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Common Instruction

The most prevalent form of instruction

Begin

does not attempt to adapt content to learn-

Tell

ers. Learners show up (Figure 10.17). The

Repeat

presentations and activities commence. After

Common

(as Time)

Test

Instruction

a while, a test is given and grades are issued.

Permits

Tell, test, grade. Done. Next class, please.

Grade

This common form of instruction has

been perpetrated on learners almost since

End

the concept of organized group instruction

FIGURE 10.17

Common

originated. It’s as simple and inexpensive as

instruction paradigm.

you can get, and it’s credible today not because

of its effectiveness but because of its ubiquity.

It’s unfortunate that so many use common instruction as a model for education and training. This tell-and-test paradigm is truly content-centric. With honorable intentions and dedication, designers frequently put great effort into the organization and presentation of content and sometimes into preparation of test questions, but they do nothing to determine the readiness of learners or the viability of planned presentations for specific individuals. Consequently, although k

the application easily handles any number of learners and has almost no k

administrative or management problems, it doesn’t motivate the learner.

The effectiveness of common instruction ranges widely, depending on many factors that are usually not considered, such as motivation of learners, their expectations, their listening or reading skills, their study habits, and their content-specific entry skills (Figure 10.18). It is often thought that the testing event and grading provide sufficient motivation, so the issue of motivation is moot.

Besides, motivation is really the learners’ problem, right? If they don’t learn, they’ll have to pay

Individualization

the consequences—and hopefully

+ will know better next time.

Wrong thinking, at least

FIGURE 10.18

Individualization rating for

in the business world. It’s the

common instruction.

employer and the organization as

a whole who will pay the consequences—consequences that are far greater than most organizations recognize.

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Selective Instruction

Begin

Selective instruction adds a front end filter to

common instruction. The front end is designed to

improve effectiveness of the legacy common instruc-

Test

tion by narrowing the range of learners to be taught.

Clever, huh? Change the target audience rather than Assess

offer better instruction.

Entry

Reject

Skills

Student

Most American colleges and universities employ

selective instruction at an institutional level; that is, Admit

they select and prepare to teach only those learners Common

who meet minimum standards. Students are chosen

Instruction

through use of entry examinations, measures of intellectual abilities, academic accomplishments, and so End

on. The higher those standards can be, the better the outcomes will be.

FIGURE 10.19

It makes sense that learners who have been

Selective instruction

highly successful in previous common instructional

paradigm.

activities will deal effectively again with common

instruction’s unfortunate limitations. Organizations of higher learning will, therefore, find their instructional tasks simplified. They need to do little k

in the way of motivating learners and adapting instruction to individual k

needs. They can just find bright, capable, energetic learners, and then do whatever they want for instruction. The learners will find a way to make the best of it and learn—at least enough to pass a test at the end of the course.

It dismays me that our most prestigious institutions boast of the high entrance examination scores achieved by their entering learners. What they know, but aren’t saying, is that they will have few instructional challenges, and their learners will continue to be outstanding performers. By turning away learners with lower scores, they will have far less challenging instructional tasks and will be able, if they wish, to devote more of their time to research and publishing. They actually could, if they wished (and I don’t mean to suggest that they do), provide the weakest instructional experience and still anticipate impressive learning outcomes.

We do need organizations

that can take our best learners

Individualization

and move them to ever-higher

+ levels of achievement. But per-

haps the more significant instruc-

FIGURE 10.20

Individualization rating for

tional challenges lie in work-

selective instruction.

ing with more typical learners

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who require greater instructional support for learning. Here, common instruction probably has been less effective than desired and should be supplanted by instruction that is based more on our knowledge of human learning than on tradition.

Remedial Instruction

Recognizing that issuing

Begin

grades is not the purpose of

Present

training, some have tried modify-

Information

ing common instruction to help

failing learners. In this remedial

Repeat

Test

approach, when testing indicates

(As Time)

that a learner has not reached an

Permits

acceptable level of proficiency,

Alternate

Acceptable

alternate instructional events are

Presentation

Yes

No

provided to remedy the situation.

These added events, it is

End

hoped, will bring failing learn-

FIGURE 10.21

Remedial instruction

ers to an acceptable level of

paradigm.

performance.

k

Remediation is something of

k

an advance toward purposeful

instruction, because, rather than simply issuing grades, it attempts to help all learners achieve needed performance levels.

If learners fail on retesting, it is possible to continue the remediation, perhaps by providing alternate activities and support, until they achieve the required performance levels.

One has to ask, if the remediation is more likely to produce acceptable performance, why isn’t it provided initially? The answer could be that it requires more instructor time or more expensive resources. If many learners can succeed without it, they can move on while special attention is given to the remedial learners.

The unfortunate thing about remedial instruction is that its individualization is based on failure. Until all the telling/testing is done, instructors may not discover that some learners are inadequately prepared for the course, or don’t have requisite language skills, or aren’t sufficiently motivated. Although more appropriate learning events can be arranged after testing reveals individual problems, precious time may have been wasted. The instructor and many learners (including those for whom the instruction is truly appropriate) may have been grievously frustrated, and 160

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Individualization

remedial learners may be more

+ confused and more resistant to

learning in their reluctance to

have more experiences of failure.

FIGURE 10.22

Individualization rating for

All in all, remediation repre-

remedial instruction.

sents better recognition of the

true goals of instruction, but employs a less-than-optimal process of reaching them.

Individualized Instruction

The same components of telling, testing, and deciding what to do next can be re-sequenced to achieve a remarkably different instructional process.

As with so many instructional designs, a seemingly small difference can create a dramatically different experience with consequential outcomes.

A basic individualized system begins with assessment. The intent of the assessment is to determine the readiness of learners for learning with the instructional support available. Learners are not ready if, on the one hand, they already possess the competencies that are the goal of the program, or, on the other hand, they do not meet the necessary entry requirements to understand and work with the instructional program. Unless assumptions k

can be made accurately, as is rarely the case despite a common willingness k

Begin

Test

End

Record

Performance Data

Learning

Learning

Event

Event

Learning

Select

Learning

Event

1 or more

Event

Learning

Learning

Event

Event

FIGURE 10.23

Individualized instruction

paradigm.

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to make assumptions regarding learner competencies, it’s very important to test for both entry readiness and prior mastery.

Record keeping is essential for individualized programs to work, because progress and needs are frequently reassessed to be sure the program is responding to the learner’s evolving competencies. Specific results of each testing event must be kept, not just as an overall performance score but also as a measurement of progress and achievement for every instructional objective each learner is pursuing.

As progress is made and records are updated, the questions of readiness and needs are posed. If there are (or remain) areas of weakness in which the training program can assist, learning activities are selected for the individual learner. Any conceivable type of learning activity that can be offered to the learner can be selected including workbook exercises, group activities, field trips, computer-based training, videos, and so on.

The individualized learning system is greatly empowered if alternate activities are available for each objective or set of objectives. Note that it is not necessary to have separate learning activities available for each objective, although it helps to have some that are limited to single objectives wherever possible. An arrangement suggested by Table 10.5 would be advantageous and perhaps typical. However, great variations are workable; k

it is often possible to set up an individualized learning program based on a k

variety of existing support materials.

Looking at Table 10.5, you can see how an individualized learning system works. If a learner’s assessment indicated needed instruction on all four objectives, what would you suggest the learner do? You’d probably select resources A and D, because we don’t happen to have one resource that covers all four and because together A and D provide complete coverage of the four objectives.

Further, to the learner’s benefit, these two resources cover more than one objective each. When resources cover multiple objectives, it is more likely that they will discuss how various concepts relate to one another.

Such discussions provide bridges and a supportive context for deeper understanding. Some supportive context, particularly important for a novice, is likely to be there in the selection of A and D in the preceding example, whereas it would be less likely in the combination of C, B, and F.

Just as with remedial instruction, if a prescribed course of study proves unsuccessful, it’s better to have an alternative available than to send the learner simply back to repeat an unsuccessful experience. If the learner assigned to A and D were reassessed and still showed insufficient mastery 162

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TABLE 10.5

Learning Resource Selection

Learning Resources

A

B

C

D

E

F

Basics

Basics

Introductory

Blog on

Tutorial on

Group

Manual

Manual

Video

Recent

Problem

Discussion

Objective

Text in

Exercises in

Discoveries

Solving

on Science

Number

Chapter 1

Chapter 1

1

X

X

2

X

X

3

X

X

X

4

X

X

of Objective 3, it would probably be more effective to assign Learning Resource E at this point than to suggest repetition of D.

The closed loop of individualized instruction systems returns learners to assessment following learning activities, where readiness and needs are again determined. Once the learner has mastered all the targeted objectives, the accomplishment is documented, and the learner is ready k

to move on.

k

The framework of individualized instruction is very powerful, yet, happily, very simple in concept. Its implementation can be extraordinarily sophisticated, as is the case with some learning management systems (LMSs) or learning content management systems (LCMSs), whether Managers

Competency

Individualized

Specialists

(ability to do

Instruction

the right thing

at the right time)

Support

Persons

FIGURE 10.24

Framework of individualized

instruction adapts to job requirements.

Individualization

+

FIGURE 10.25

Individualization rating

for individualized instruction.

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custom-built or off the shelf. However, it can also be built rather simply within a single instructional application and have great success.

Note that this structure does not require all learners to pursue exactly the same set or the same order of objectives. Very different programs of study are easily managed. Learners who require advanced work in some areas or reduced immersion in others are easily accommodated (Figure 10.24).

Practical Solutions

As we have noted, there is a continuum of individualization. Some individualization is more valuable than none, even if the full possibilities of individualized instruction are beyond reach for a particular project. One of the most practical ways of achieving a valuable measure of individualization is simply to reverse the paradigm of tell and test in common instruction.

Fixed Time, Variable Learning

With the almost-never-appropriate tell-and-test approach, exemplified by prevalent instructor-led practices, learners are initially told everything they need to know through classroom presentations, textbooks, videotapes, and other available means. Learners are then tested to see what they have learned (more likely, what they can recall). After the k

k

test, if time permits (since instructor-led programs almost always work within a preset, fixed time period, such as a week, a quarter, or a semester), more telling will be followed by more testing until the time is exhausted (Figure 10.26). The program appears well planned if a final test

Tell

Test

closely follows the final content pre-

sentation, just before the time period

expires.

When e-learning follows this

Repeat as time permits

ancient plan, the plan’s archaic

weaknesses are preserved.

FIGURE 10.26

Tell and test.

Fixed Content, Variable Learning

Similarly, instead of a predetermined time period, content coverage can be the controlling factor. Just like above, the process of alternately telling and testing is repeated until all the content has been exhausted. The program then ends.

To emphasize the major weakness of this design (among its many flaws), the tell-and-test approach is often characterized as fixed time, variable learning— or, in the case of e-learning implementations, fixed content, 164

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variable learning. In other words, the approach does not ensure sufficient learning to meet any standards. It simply ensures that the time slot will be filled or that all the content will be presented.

Fixed Learning, Variable Time and Content

To achieve success through enabling people to do the right thing at the right time, we are clearly most interested in helping all learners’ master skills. It is not our objective simply to cover all the content or fill the time period. To get everyone on the job and performing optimally as quickly as possible, we would most appropriately choose to let time vary, cover only needed content, and ensure that all learners had achieved competency.

Put the Test First

Many instructional designers embark on a path that results in tell-and-test applications. They may disguise the underlying approach rather effectively, perhaps by the clever use of techno-media, but the tell-and-test method nevertheless retains all the weaknesses of common instruction and none of the advantages of individualized instruction.

Let’s compare the tell-and-test and

test-and-tell methods (see Table 10.6).

Test

Tell

The advantages gained by simply

k

k

putting the test first and allowing

learners to ask for content assistance

as they need it are amazing. As pre-

viously noted, just a slight alteration

Repeat as to achieve

of an instructional approach often

mastery

makes a dramatic difference. This is

one of those cases. There is very little

FIGURE 10.27

Test and tell.

expense or effort difference between

tell-and-test on the one hand and

test-and-tell on the other, but the learning experiences are fundamentally different.

Getting novice designers to break the tendency to begin their applications with a lot of presented information (telling) is not simple. Indeed, almost everyone has the tendency to launch into content presentation as the natural, appropriate, and most essential thing to do. I have been frustrated over the years as my learners and employees, especially novices to instructional design, have found themselves drawn almost magnetically to this fundamental error. I have, however, discovered a practical remedy: After designers complete their first prototype, I simply ask them to switch it around in the next iteration. This makes content presentations available on demand and subject to learner needs.

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TABLE 10.6

Selecting Content to Match Learner Needs

Tell and Test

Test and Tell

Because they have to wait for the

Learners are immediately confronted with

test to reveal what is really important

challenges that the course will enable them to

to learn (or it wouldn’t be on the test),

meet. Learners witness instantly what they

learners may have to guess at what is

need to be learning.

important during the extended tell

time. They may discover too late that

they have misunderstood as they stare

at unexpected questions on the test

that will determine their grades.

All learners receive the same content

Learners can skip over content they already

presentations.

know as evidenced by their initial performance.

Learners are passive, but they try to

Learners in well-designed test-and-tell

absorb the content slung at them,

environments become active learners; they are

which they hope will prove to be

encouraged to ask for help when they cannot

empowering at some point.

handle test items. The presentation material

(which can be much the same as that used in

tell and test) is presented in pieces relevant to

specific skills. Learners see the need for it and

put it to use.

It’s boring.

Not likely to be boring.

k

k

Example

Cooking with Flair:

Preparing Fruits, Salads,

and Vegetables

Context: Preparation of a fresh fruit platter.

Challenge: Identify and properly treat fruits that discolor without preventative treatment when exposed to air.

Activity: Select various fruits and either place them directly on the platter or dip them in acidic fruit juice first.

Feedback: When fruits that need to be dipped in acidic fruit juice are served without being dipped, they turn black. At this point, relevant tutorials are presented to cover needed principles.

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This example, drawn from e-learning initiatives at the National Food Services Management Institute, illustrates the power of the test-and-tell technique to select the right content for each learner, and avoids instruction on principles some learners may already know. Cooking with Flair: Preparing Fruits, Salads, and Vegetables teaches a range of facts and procedural information regarding the preparation of fruits and vegetables. The target learners usually have some general but incomplete knowledge of the topics to be covered, and the gaps in their knowledge can vary greatly.

A typical strategy in such a context is to tell everybody everything, regardless of whether or not they need it. This is rarely helpful, as learners tend to stop paying attention when forced to read information that they already know or, on the other end of the scale, that they can’t understand.

This is exactly the type of situation in which test-and-tell is most powerful.

We’ll look at a module called “Do the Dip!,” in which learners are to master how to keep freshly cut fruit from turning brown (Figure 10.28).

The principle at hand: fruits that tend to darken should be dipped in a k

k

FIGURE 10.28

Do the Dip!: Learners must decide whether or not it is appropriate to dip fruit when preparing a fresh fruit tray.

Source: Cooking with Flair: Preparing Fruits, Salads, and Vegetables.

Courtesy of National Food Service Management Institute, University of Mississippi.

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dilute solution of citrus juice, while other fruits do not need to be treated in this way. The learner is to learn how this principle affects common fruits. The setup here is very simple. Learners are given a very brief statement that sets the context. Then, they are immediately tasked with the job of preparing a fruit tray. They can place the cut fruit directly on the serving tray, or they can first dip the fruit in a dilute solution of lemon juice.

If the user correctly dips a fruit, the information regarding that choice is confirmed with a message and a Do the Dip! flag on the fruit (Figure 10.29). Whether the learner already knew the concept or guessed correctly, the “tell” part of the instruction is contained in the feedback—presented after the learner’s attention has been focused by the challenge.

How about when the learner is wrong? When a fruit is not dipped when it should be, the fruit turns brown and unappealing, while instructional text specific to the error is presented on the screen (Figure 10.30).

After the exercise is complete, the learner is given a summary screen: a complete and attractive fruit platter and screen elements that further reinforce the lesson of which fruits require a citrus treatment (Figure 10.31).

This is a small and straightforward application of the test-and-tell principle, used to select what information to present to the learner and k

k

when simply to confirm the learner’s present knowledge and skills. You should notice this magic key in action in more sophisticated ways in nearly every other example described in this book. It’s engaging, efficient, and effective.

FIGURE 10.29

Correct responses are reinforced with a Do the Dip!

stamp on selected fruit.

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FIGURE 10.30

Incorrect responses result in brown, unappealing fruit.

k

k

FIGURE 10.31

Success results in a completed platter and reminders posted on each fruit.

Nonetheless, a common response from instructional designers is, “Isn’t it unfair to ask learners to do a task for which you haven’t prepared them?” (Interestingly, we rarely if ever hear this complaint from actual students.) But it really isn’t unfair at all. Quite the reverse: The challenge focuses learning attention to the task at hand, allows Seven Magic Keys to Motivational e-Learning

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capable learners to succeed quickly (saving time and frustration), provides learning content to the right people at the right time, and motivates all learners to engage in critical thinking about a task instead of simply being passive recipients of training. When the “tell” information is presented in the context of a learner action (i.e., right after a mistake), learners are in an optimal position to assimilate the new information meaningfully into their existing understanding of the topic.

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4

Magic Key 4: Use an

Appealing Context

Learning contexts have many attributes. The delivery system is one very visible attribute, as is the graphic design or aesthetics of an e-learning application. More important than these, however, are the role the learner might be asked to play, the relevance and strength of the situational context, and the dramatic presentation of context.

It’s easy to confuse needed attributes of the learning context with ornaments and superfluous components. Unfortunately, such confusion can lead to much weaker applications than intended. However, a strong learning context can amplify the unique learning capabilities of e-learning technologies. Let’s first look at some mistakes that have continued since the early days of e-learning.

The Typing Ball Syndrome

When I did my first major project with computer-based instruction, it was k

with computer terminals connected to a remote IBM 360 central com-k

puter. The terminals were IBM 3270s, which had no display screen but were more like typewriters, employing an IBM Selectric typewriter ball.

Continuous sheets of fanfold paper were threaded into the machine.

A ball spun and tilted almost magically to align each character to be typed.

With thin, flat wires manipulating the ball’s mechanism, the ball, like a mesmerized marionette, hammered the typewriter ribbon to produce crisp, perfectly aligned text.

FIGURE 10.32

IBM Selectric typewriter and type ball.

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Selectric typewriters were something of an engineering fascination.

They so quickly produced a clean, sharp character in response to a tap on the keyboard, it was hard to see the movement. And yet, since a perfect character appeared on the paper, you knew the ball had spun to precisely the correct place and had tapped against the ribbon with exactly the right force.

If the Selectric typewriter was fascinating, the IBM 3270 terminal was enthralling. Its Selectric ball typed by itself like a player piano! Looking very much like the Selectric typewriter with a floor stand, the terminal was able to receive output from a remote computer and could type faster than any human. The keys on the keyboard didn’t move. The ball just did its dance while letters appeared on the paper.

The computer could type out information and learners could type their answers, to be evaluated by the computer. The technology was fascinating.

There was much talk about this being the future of education.

It felt like classroom delivery of instruction was near the end of its life span, and, despite fears of lost teaching jobs, there was great excitement that private, personalized learning supported by amazingly intelligent computers would truly make learning fun and easy.

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Novelty versus Reality

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There were some very positive signs that technology-led instruction would indeed be a reality in the near future. Learners eagerly signed up for courses taught with the use of computer terminals. Seats filled up rapidly, requiring dawdling learners to sign up for traditionally taught classes or wait another term to see if they would be lucky enough to get into one of the computer-assisted classes.

But some disturbing realities crept in, realities that countered initial perceptions and rosy predictions. For one thing, it took a lot longer for information to be typed out than to find it in a book. While you didn’t get to watch them being typed, books are pretty fast at presenting information—and they are portable, too. They don’t make any noise, either—so they can be used in libraries and other quiet places that are conducive to study. They often include graphics and visual aids—things our Selectric typewriters couldn’t provide. You can earmark a page and easily review. You can skim ahead to get some orientation and get a preview of what was to come.

Learners, the harsh but insightful critics that they often are, did the most unexpected thing. Instead of sitting at the terminals waiting for the typing ball to spit out text, they simply took their “borrowed” copies of printouts to a comfortable location and studied them. Sometimes they’d 172

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work together in pairs or groups: Using just the printout, one learner would read the computer’s questions, and another learner would answer them. The first learner would look up and read the feedback for that particular answer, and together, they would have a pleasant, effective learning experience. They were executing, in effect, the programmed instructional logic. It was much better than sitting at a typing machine.

Why bring up this “ancient” history? We’re not dealing with typing balls anymore.

Isn’t this irrelevant?

Not at all. Each time a new technology comes on the scene, we expect too much of it and require too little of ourselves to use it effectively. We are ready to think that each new technology solves everything. For learning, the Internet has repeated the typing ball scenario—almost to the letter!

The typing ball was not essential to learning in any way. Learners quickly dispensed with it and created a more effective context in which they could freely discuss the content, not only in a more convenient manner, but in a more meaningful manner, as well. In fact, the typing ball context was not really an instructional context at all; it was simply a new technology for k

instructional delivery. This seems like an obvious confusion to us today, but k

this mistake has been made time and again as new technologies have arrived to save the future of education. It is happening now, with the Internet and mobile devices.

Novelty Is Short-Lived

Any attribute of the learning context can be made novel. The reaction to the novelty, almost by definition, will be one of instant interest and enthusiasm. Novelty draws attention and energizes exploration.

After the initial novelty-based interest, however, the next level of evaluation sets in. Newness doesn’t last very long. Once we see something, experience it, and put it in its place among other familiar notions, it is no longer new. If a novelty doesn’t introduce something of real value, it quickly loses value or becomes an irritant.

In other words, novelty has a single, short life—too short to sustain interest, much less learning and involvement.

Much e-Learning Depends on Novelty

So it’s short-lived too. A terrible mistake made in e-learning is assuming that when new technology is employed, it provides better instruction.

Because it comes in a new form and has such incredible attributes as Seven Magic Keys to Motivational e-Learning

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worldwide access and 24/7 availability, it appears that its instructional effectiveness is better. Inexplicably, many even assume instructional development will be faster and easier: “We can put our PowerPoint slides on our phones. It’ll be fantastic training.”

Wrong on all counts. Actually, e-learning tends to expose instructional deficiencies and exacerbate their weaknesses.

Weak instructional design applied on a small scale, perhaps in just one class, doesn’t do much damage. When parts of a book are poorly structured, for example, an instructor can likely overcome the problem through use of supplemental materials, class activities, or in-class presentations.

However, when a poor instructional design is broadcast to hundreds or thousands of learners, it can wreak havoc that is not as easily corrected. As I’ve noted, organizations tend to look the other way and avoid questioning instructional effectiveness, even though the damage in lost opportunities, wasted time, severe mistakes, and accumulated minor mistakes can be quite significant.

Much early web-delivered e-learning repeated the history of computer-assisted instruction (CAI). Actually, in many ways, contemporary e-learning has been more unguided than early CAI systems, which, in many cases, did conscientiously attempt to develop and apply k

instructional theory. Almost from their introduction, web-delivered k

e-learning applications have bet on the novelty of computer presentation. e-Learning proponents often base their enthusiasm on the novelty of using computers for new purposes, rather than on a true appreciation of the potential computers offer.

Anticipated Benefits of e-Learning

■ Quick, easy, fun learning

■ Access to current information 24/7

■ Learning on personal time rather than during work time

■ Access to reference material as needed

■ Unrestricted time to review, answer questions, and so on

■ Personalized programs

■ Lower training costs

Pioneering applications drew attention because they painted a picture of people happily learning whenever and wherever it might be 174

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convenient—easy, fast, and cheap. But novelty, with its fleeting contributions, left exposed many weakly designed applications and put the effectiveness of e-learning in question.

Questions about what it takes to be effective are slowly—surprisingly slowly—coming to the front. Technoblindness, fueled by euphoric views of potentialities, may have caused us to neglect the truth. Many have charged into e-learning investments, empowered by not much more than a fascination with its novelty and some fanciful dreams. But they forgot to consider the learning context.

Context Elements to Consider

There are many types of context decisions to make. Remember that we are vitally concerned about the motivational aspects of everything we do in e-learning. We should make context choices first to stimulate learning motivation and second to assist learners in transferring their newly learned knowledge and skills to real-world tasks.

As David Jonassen observes:

The most effective learning contexts are those which are problem- or case-based and activity-oriented, that immerse the learner in the situ-k

ation requiring him or her to acquire skills or knowledge in order to k

solve the problem or manipulate the situation. Most information that is taught in schools, however, is stripped of its contextual relevance and presented as truth or reality. Our youth are daily subjected to acquiring countless facts and rules that have no importance, relevance, or meaning to them because they are not related to anything the learners are interested in or need to know. (Jonassen, 1991, p. 36) Although many consider content presentation to be most important and others dwell on user interface, neither of these is likely to produce optimal or even excellent learning opportunities if a well-conceived context isn’t used to make the experience meaningful and memorable.

Jonassen reiterates, “Instruction needs to be couched in a context that provides meaning for the learners, a context that activates relevant schemata, that engages learners in meaningful problem solving” (Ibid).

Table 10.7 presents some contextual ideas to heighten motivation and facilitate meaningful transfer of learned skills.

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TABLE 10.7

Motivating Contexts

To Stimulate Learning

Suggestion

Comments

Require the learner to solve problems

It is more interesting to assemble or operate

and do things.

simulated equipment or software, diagnose

system faults, or find an accounting error, for

example, than to simply answer a bunch of

questions.

Use a timer for learners to beat.

A simple mechanism such as a countdown timer

stimulates learner attentiveness.

Use suspense.

You can set up consequences for errors that

accumulate. The learner must not make too many

errors or a tower will topple, a company will lose a contract, or a chemical solution will explode.

Set a maximum number of allowed

If the learner makes one too many errors, he or

errors.

she has to begin all over again, as in many video

games.

Dramatically demonstrate the impact

Drama gets our emotions involved and makes

of poor performance.

experiences more real and personal.

Dramatically demonstrate the impact

A positive impact on the organization or on the

of good performance.

learner personally is a goal of interest. A dramatic revelation of what is possible can be very

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motivating.

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To Transfer Skills

Provide feedback from a simulated

Feedback might stress how the consequences of

supervisor or coworker.

the good or poor performance affect them

personally, their team, and the organization as a

whole.

Ask learners how they think what they

Address the question head-on. Encourage

are learning applies to their actual

learners to develop their own examples of realistic jobs.

ways to apply what they’ve learned. They might

even work out a personal agenda or time line for

fully implementing their new skills.

Create an unreal world.

It is sometimes more effective to invent a

completely new world for the examples and

situations that learners will be working with. This may help learners avoid getting caught up in the

details of their own specific processes and see

opportunities for improvement more easily.

Use job tasks as the basis for lesson

Designing job-based training maximizes the

design, case studies, and examples,

probability that learners will be able to retrieve

or follow-up projects.

their new knowledge and skills when they are back

at work. In other words, let the practical tasks that learners need to perform drive the content and

sequence of the training.

( continued)

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TABLE 10.7

( Continued)

To Transfer Skills

Suggestion

Comments

Use guided discovery or cognitive

The learning is inherently contextual or situated in apprenticeship.

the job.

Incorporate case studies and

It helps to set standards of excellence against

examples that reflect best practices

which learners can evaluate their own

of proficient employees.

performance abilities.

Provide a variety of examples and

To ensure that learners will be able to apply their problems based on documented

new skills appropriately in work situations, ensure events.

that the problems and situations presented during

training reflect the richness and diversity of what they will encounter in their everyday tasks.

Use a high-fidelity simulation while

It’s worth the effort to make the simulation as

training procedural tasks.

much like the real thing as possible, because

transfer is enhanced to the extent that actual tasks share common elements with rehearsal tasks.

Assign projects to be completed

Learners may not always see how what they have

during or after the class.

learned can be applied. Immediately applying new

skills outside the training context can be very

helpful.

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Space out the review periods time.

Rather than giving learners one shot at learning a

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new skill and amassing all practice activities into one episode, spread out the intervals of practice

over time to facilitate retention of new skills.

Give practice identifying the key

If learners begin analyzing where and when new

features of new situations wherein

skills are applicable, they may begin setting

learners might apply their new skills

expectations regarding where and when they will

appropriately.

personally begin to apply them.

Provide skill-based training at a time

The smaller the separation in time between

when learners actually need it

the learning episode and the application of that

(just-in-time training).

learning, the greater the likelihood that the learner will transfer skills to that situation.

Embed the physical and

This helps to guarantee that learners will retrieve psychological cues of the job into the

the relevant knowledge and skills when they sense

instruction.

those same cues back in the work environment.

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Learning Sequences and Learning

Contexts

Breaking complex tasks apart and teaching components separately can be an effective instructional practice. Part-task training is effective and efficient because it allows learners to focus on component behaviors and master them before having to deal with the interrelationships among sequences of behaviors to be performed.

Risk of Part-Task Training

One has to be careful here, however. Breaking instruction into pieces for reduced complexity and easier learning can have exactly the opposite consequences: increased complexity and learner frustration.

How many piano learners, for example, have given up the instrument entirely because they could not sit for hours to practice finger exercises and arpeggios? Fingering skills are certainly important, but such drills are far from what the music learners desires to play. They want to learn music that is enjoyable to play and something they’re proud to play for others. If the finger exercises don’t demotivate them, the simplistic nursery school songs strung one after another are enough to disinterest many potential musicians. Every music learner wants to play cool songs as soon as pos-k

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sible. The songs don’t have to be overwhelmingly complex or difficult to play, they just need to represent an accomplishment that is meaningful to the learner.

Maintaining Context

Critical elements of a meaningful context can easily be lost when instruction is broken into pieces, but beginning with a clearly articulated and learner-valued goal can help. Then subtasks can be defined and learned with the larger goal kept in mind. Removing some context momentar-ily can be helpful, as long as enough context exists for the learning to be meaningful, or the relationship of the content to the ultimate goal is clear. The importance and relevance of the subtasks must be clear to the learner and revisited often. It is easy to assume that learners see this relationship, when, in fact, they may not. There are some easy techniques that help considerably, although they again fly in the face of traditional instructional design practice. The first step is to reconsider where you start learners.

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Don’t Start at the Bottom of the Skills

Hierarchy

A valued tool of instructional designers is the skills hierarchy. Desired skills are broken down into their constituent parts, and then ordered in a prerequisite sequence or hierarchy. The target skill resides at the top, while the most basic, elementary skills sit at the bottom, with intermediary skills building the hierarchical tree (Figure 10.33).

If the hierarchy is accurately constructed, tasks in the tree cannot be learned or performed before the skills below them have been learned. The hierarchy, therefore, prescribes a useful sequence for teaching. You start at the bottom, where all learners can be assumed to be able to learn the skills.

Once these prerequisite skills have been mastered, you can move up a level.

Break the rules! Instead of beginning with the tedious task of explaining a flush, royal flush, pairs, and so on to teach poker, deal the cards and play the game. Maybe you have all participants organize their cards and lay them face up. An experienced poker aficionado might announce who has the best hand and ask the learners to figure out why it’s so strong. Of course, the best way to put the learners at risk is to give them a pile of chips and have them begin betting. Once students are in danger of losing chips (or gaining the whole multicolored pile), they ask good ques-k

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tions, learn winning combinations faster, and pay greater attention to explanations. There’s no better way to learn about bluffing than to lose your chips to someone who wins the hand with two jacks!

Play Poker

Bluff bad

Bid good

hands

hands

Identify different

Physically

“hands”

sort cards

Identify Flush

Identify Royal Flush

Identify Pairs

FIGURE 10.33

Partial skills hierarchy for playing poker.

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Boring!

Now, think about this:

Question: Where do the least interesting tasks probably lie?

Answer: At the bottom of the skills hierarchy.

Question: Where do the most interesting tasks probably lie?

Answer: Higher up the hierarchy, probably near the top.

Question: If you start at the bottom, is it clear to learners why they are learning these skills?

Answer: No, but we tell them these skills will be important. They’ll see it later.

Question: If you start at the bottom, are you starting with the most boring elements of the content with little contextual support?

Answer: Yes.

Suggestion: Don’t start at the bottom.

Keep Your Eye on the Target

If you want to be a lawyer, chemist, or romance novel writer, you probably have an expectation of what your life will be like in those occupations. It is this vision that motivates the necessary dedication of considerable time and effort to learn the many essential facts, concepts, and skills.

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Although we may well have misconceptions about what is involved in appealing professions, we often set out on major journeys toward them with considerable optimism and enthusiasm, only to have that optimism and enthusiasm severely challenged by boring introductory courses. I hear fairly often of people who gave up their interest in careers because they couldn’t imagine taking any more courses like the introductory courses.

A Great Learning Journey Starts … in the

Middle?

Good e-learning designs do a lot to keep activities relevant and interesting. They don’t work on the all-too-common instructor admonishment,

“Trust me. Someday you’ll be glad you know this.”

How do good designs avoid the problem of uninteresting, seemingly irrelevant starter content? They start somewhere in the middle of the skills hierarchy, if not at the top, and let learners participate in leading the charge to fill in the missing pieces as necessary.

As you look at a skills hierarchy (and, by the way, you should construct one just for the experience), scan up from the bottom in search of a point 180

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where a collection of prerequisites comes together in support of a skill or concept. Look at that skill or concept and see if it is a useful one. Points of convergence on a skills hierarchy often identify a capability that new learners can see as meaningful and desirable.

Sometimes It Starts at the End

As presented in the discussion of Magic Key 3, a test-and-tell sequence is a useful strategy. (Don’t get it backwards.) I don’t literally mean to start with a typical academic test, of course. You should build a context in which the learner has the opportunity and impetus to apply the skills resident at this selected point in the hierarchy.

The learner may or may not be able to perform well, but either outcome is helpful. If the learner does well, you might decide to jump up to the next point of convergence in the hierarchy and repeat the process. If the learner does not do well, you will be ready to respond to the learner’s requests for help by supplying appropriate instructional experiences for the prerequisite content. If the learner accurately identifies a need, you would respond to it, reinforcing the learner’s perception of the need’s relevance.

As you generate a contextual understanding, learners are learning much k

more than just a collection of skills. They are preparing personal per-k

spectives, a set of values, and a cognitive map to guide performance and continuing learning.

In other words, context doesn’t have to sit in the background only.

It can be an important component of the interaction with learners to provide a structure for understanding, learning, and intelligent performance.

Novelty Can Be a Valuable Tool

We earlier debunked technological novelty as an instructional context; however, novelty does have value. Novelty is powerful for only a short time, but it can be useful when applied thoughtfully and purposefully.

Although it is not a substitute for effective learning interactions, novelty does have two important uses in effective e-learning:

• Novelty draws attention and energizes curiosity.

• Novelty can help make an experience memorable.

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Drawing Attention

As previously discussed, the most important thing designers must accomplish is motivating learners to learn. This is done by connecting with learners’ needs and creating interest. And this means first getting their attention and helping them build positive expectations, curiosity, and a willingness to try (Figure 10.34).

Because novelty loses its value quickly, its use is well suited to attracting attention. It increases learner receptivity to messages that market the value of learning the content and skills at hand.

Memorable Experiences

An unexpected quip, a fascinating morph, an amusing sound, or a simulated explosion could provide an element of appeal or surprise that learners will remember for some time. It’s important, of course, that these elements be closely tied to important learning points. We don’t want to end up with the effect of a clever TV commercial that viewers can remember in great detail, except for one minor point—the product or company being promoted.

As we know, to be effective, e-learning experiences must be both meaningful and memorable. A novel context can help tremendously to k

attract attention, giving us the opportunity to market the value of learning k

the content. Through demonstrations, testimonials, or “give this a try”

experiences, novelty can turn the attention it won into perceived value.

But we have to get off the novelty as soon as possible. Amusement is not the goal. It is a tool and means to better learning.

Just one more step: how do we turn motivation into learning and realized value?

Novelty

Marketing

Learning

Perceived

Real

Attention

Value

Value

FIGURE 10.34

Learning begins by drawing the learner’s

attention.

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Example

Supply Chain Training

Case Study: www.alleninteractions.com/manhattan

Demo: http://myalleni.net/clients/demo/supply_chain/

Context: Head of a handbag company needs to optimize its supply chain to increase quality, sales, and profitability.

Challenge: Make the best supply chain decisions based on market trends and customer needs, to maximize key performance indicators (KPIs).

Activity: Given a company with customers, products, and a defined supply chain, work through a “year in the life” of that company by choosing the best decision at each key milestone or event.

Feedback: Immediate through a company dashboard and delayed through a final scorecard with detailed evaluations of each decision per its effect on each KPI.

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Manhattan Associates needed to train their employees on how decisions and operations impact business, products, customers, and the market. In order to provide meaningful context to the learning experience, employees are put into the role of a customer who gets to build, experience, and then affect the supply chain through the “handbag story”—one of a number of context-based challenges—incorporating every component of the supply chain cycle. By allowing learners to experience the impact and consequence of each of their choices during a supply chain optimization game, concepts are made clear, understandable, and highly memorable.

The power of a story to provide a compelling context is shown in this example, which immerses learners with this scenario: Ralph Retailer quickly realizes how difficult it will be to order handbags from Artie Guy to make sure he always has enough handbags at each of the stores to support customer demand. He also needs to consider that he shouldn’t have too many handbags, which would make things confusing and possibly require him to move to a larger warehouse.

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He asks his very intelligent son, Ronnie, to take over the job of ordering handbags. He provides him with two goals: satisfy at least 98 percent of customer demand, but maintain no more than a 10-day supply of handbags in either the warehouse or any one of the stores.

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FIGURE 10.35

Story, art, and CCAF combine into a compelling context to make content interesting.

FIGURE 10.36

Key performance indicators (KPIs) provide authentic performance feedback.

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FIGURE 10.37

Feedback comes primarily as consequences to

learner decisions.

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FIGURE 10.38

Real-world problems emerge as learners work to achieve their primary goals.

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FIGURE 10.39

Weather, mechanical breakdowns, political unrest, and many more challenges crop up.

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FIGURE 10.40

Help is always available, but the scenario clock presses on.

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Example

Why Does Glue Stick?

Context: An elephant (as a weighty object) wants to cross a chasm.

Assorted objects and glues are all that are available to make a bridge.

Challenge: Determine which glues will create a weight-bearing bond between a variety of materials.

Activity: Select from and drag available objects made of various materials to form a bridge. Then select from a variety of glues the one you think will form a stable bond between each pair of objects you chose.

Feedback: If the bond is very weak, the newly attached object falls. If the object adheres, it remains in place until the elephant tests it. If the bond is insufficient, with a great look of surprise on its face, the elephant falls; otherwise, the elephant crosses safely and is followed by k

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a group of friends.

KTCA-TV and 3M Company, Inc., in association with ICONOS, Inc., created a series of classic e-learning experiences to accompany the public television program Newton’s Apple. The intent was to provide highly interactive and educational experiences as companions to the popular television series. The “Why Does Glue Stick?” segment is a masterful example of how a creative context—in this case novelty, sequencing, and skills transfer—can impact motivation.

The novelty in the challenge is apparent immediately (Figure 10.41).

The learner needs to build a bridge to help an elephant cross a chasm. The tricky part is that the bridge must be built by gluing together such diverse objects as a circular saw blade, a birdhouse, and an aquarium. Luckily, there are five adhesives available for use in solving this puzzle.

Again, using one of my favorite techniques, the learner is thrown into the middle of the content. You will find no boring discussions of glue characteristics here. While the context is unusual, it shines the spotlight fully on the content at hand: Which among various adhesives work with which surfaces?

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FIGURE 10.41

The learner chooses objects and glues to build a bridge to get the elephant from its glass ledge to the grassy cliff.

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To build the bridge, the learner chooses an object to glue to an existing object and an adhesive to use. If it is a successful combination, the elephant takes one step closer to its destination (Figure 10.42). If the adhesive does not hold, the learner gets a surprising and humorous result (Figure 10.43).

Now, critics might suggest this is just unfair to the learner. How is the learner to know how to combine these unusual items into a bridge?

If this were all there were to the piece, the criticism might be justified.

As it turns out, the technical information necessary to make informed decisions is easily available to the learner. Clicking the magnifying glass initiates an investigation mode, through which the learner can read about the adhesives and the surfaces, even to the detail of seeing electron micro-scope images (Figure 10.44).

Learners can research adhesives and make informed decisions, or they can experiment with materials and adhesives to see what will work. Ultimately, a successful effort is rewarded: A whole herd of elephants charges across the learner’s bridge (Figure 10.45).

It should be obvious how the novel context empowers learning in this example. But skills transfer was also addressed in the design.

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FIGURE 10.42

A successful combination: Super glue attached the

saw blade to the glass platform!

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FIGURE 10.43

An unsuccessful combination: Rubber cement didn’t

hold the phonebook to the sawblade and the elephant comes tumbling down.

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FIGURE 10.44

Learners can explore the characteristics of adhesives in detail.

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FIGURE 10.45

The task is completed successfully, allowing elephants to cross the bridge in glee.

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How can that be? It hardly seems possible to imagine a less useful task than building a bridge out of a preposterous combination of items so that elephants can cross a gap.

Actually, it’s the preposterousness of the setting that enhances the transferability of this content. Imagine if the task were something more like gluing a metal number to a door. Because the task is so reasonable, it is easy to focus too tightly on the details of the metal number and the door, which are really irrelevant to the higher-level concept. Because it is non-sensical even to attempt to build a bridge from an aquarium and a saw blade, the learner naturally generalizes the learning to the underlying, more important concept of surface types. The learner is figuring out in general how one might bond paper to metal or glass to wood. And that is really the point of the exercise.

Carefully selecting the right novel context made this great learning experience possible. Brilliant.

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5

Magic Key 5: Have

the Learner Perform

Multistep Tasks

Everyone likes doing things that are rewarding—things that have specific personal value. Most things of value require more than just recalling an answer, or even a bunch of answers; they require the performance of many small tasks and making multiple decisions along the way. They frequently require execution of a multistepped plan that must be adapted to fit a specific situation.

In other words, life and job performance aren’t very much like a school test. They are much more complex. They involve simultaneous or integrated performance of different types of behaviors, judgments, and often interpersonal skills. Judgments typically include setting priorities, sequencing steps (planning), deciding the degree of perfection necessary, and deciding how to use time, and perhaps other resources, most k

effectively. Contingencies often have to be considered in case things don’t k

go as expected. New plans may be needed as more information becomes available.

Authentic Tasks

Much has been made of standardized question forms, such as multiple choice, true/false, matching, and fill-in-the-blank structures. While they have their uses, they do not create engaging learning activities. Because they look at isolated points of knowledge, they frequently provide little of the critical performance context.

Learning tasks must be authentic— they must relate directly to the effective performance of tasks on the job. Authentic tasks are far more appealing than almost any rhetorical or academic task. They heighten our propensity to get involved. And that’s what we are after: involvement, engagement, and learning— the kind of learning that leads to performance success.

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Example

POST LERT First

Responder

e

https://sales.alleni.com/client/POST/index.html

Context: As a first Responder police officer, you need to investigate terrorist activity, identify risks, help determine the appropriate steps to secure the scene, and request appropriate resources.

Challenge: Identify and report all pertinent information as well as request proper personnel without causing undue hardship to others and self, while avoiding raising concern about innocent activities.

Activity: Select from fairly large representative lists of possible actions in any order to approach scenes of potential terrorist attacks, secure scene/people/self, gather information, report, or request appropriate k

resources and follow-up actions within a certain amount of time.

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Activity completes upon learner’s request for feedback or “death” of the learner’s character.

Feedback: Delayed and based on adherence to the official “RAIN”

process. Prescriptive steps to improve performance are provided when the process is improperly completed.

Learning Audience: Over 85,000 California law enforcement officers.

The Issue: Given the current climate and realities of terrorism, there is a tremendous need to counter terrorism in all its stages through effective, concrete strategies. It is not enough for law enforcement officers to know relevant terminology, indicators, and procedures (even if they could pass a posttest); they must be able to make effective decisions in a variety of high-pressure situations.

The e-Learning Solution:

• Give officers extensive practice working in simulated situations with realistic outcomes that could result from their decisions. The experiences help trainees learn to think as a terrorist might think, so they can predict what actions might need to be countered.

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• Present content in a challenging and meaningful context (explore and respond to events in the fictional “River City”) to ensure learning transfers to improved performance on the job.

• Use a combination of photographs, illustration, photo-realistic backgrounds, audio, and text to create an engaging and multisensory experience.

• Reinforce concepts and learning points with supporting interactions and a terrorism liaison officer as a host.

• Use real-life cases as the basis for scenarios.

• Provide links to resources and job aids.

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FIGURE 10.46

Learning begins with an open challenge.

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FIGURE 10.47

Learner-selected questions reveal information that may or may not be relevant.

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FIGURE 10.48

Information accumulates as learners explore.

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FIGURE 10.49

When learners signal they’re done investigating, they’re asked for their assessments.

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FIGURE 10.50

Learners practice identifying concerning information.

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FIGURE 10.51

Follow-up activities are taken based on learner-selected concerns.

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FIGURE 10.52

Uncertainty and ambiguity are typical conditions learners must work with. Judgment is minimized in favor of consequences and delayed performance assessments.

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6

Magic Key 6: Provide

Intrinsic Feedback

Intrinsic feedback allows learners to see for themselves that their performance was correct and effective or incorrect and ineffective. It doesn’t rely on the usual instructor assessment and didactic comment.

It doesn’t misdirect learners’ efforts toward pleasing the instructor, rather than learning essential skills. It doesn’t suggest that learning is about getting a good grade or passing a test.

Intrinsic feedback allows learners to see how their correct performance is empowering to them and how, step by step, they are becoming more capable, powerful, and valuable people. As a result, learners are usually eager to learn more.

How does this work in e-learning? It requires a learning context in which learners can try different approaches and solutions and see the results. The concept is quite simple, but important and powerful. To make it more concrete, consider the contrasting feedback designs described in k

Table 10.8.

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Don’t Tell Learners If They Are Right or

Wrong

At least not too quickly. First, let learners see for themselves whether or not their performance works as well as it needs to. Some aspects of a simulation are needed for this, although not necessarily a complex or even visual one. For example, the familiar story problem, often used in mathe-matics, provides the needed improvement over bare arithmetic problems.

Intrinsic feedback responds within context, such as reporting where the train stopped, whether the apples overflowed the pie pan, or if the corporation was fined for tax underpayment.

The feedback can be entirely visual to demonstrate outcomes of student performance. This is often best, but you need to be sure learners fully grasp the quality of their performance and in what way it needs to be improved. In fact, it may be wise to ask learners to rate their own performance and to state their own plans for improvement. But don’t give 198

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TABLE 10.8

Examples of Extrinsic and Intrinsic Feedback

Learning

Typical Extrinsic

Intrinsic

Behavior

Feedback

Feedback

When learning

“That’s correct.”

Key business indicators

management techniques,

show increased profit

a learner provides clear

margins and reduced

objectives to employees.

employee complaints.

Your boss compliments

you on your work.

When learning subtraction,

“Not so good. Let’s go

Shopkeeper says, “This

a learner deducts 166 from

through the rules of

must be my lucky day.

1,000 and gets 44.

borrowing again.”

After buying that $166

watch you’ll have $44 left

from your $1,000 bonus,

right?”

When learning electronics,

“No, that’s not the correct

Circuit graphically melts

a learner mistakenly

power source. What

down with sparks, smoke,

connects a 400-volt lead

voltage do you need for

animation, and sound.

to a 12-volt circuit.

the 12-volt circuit?”

When learning music

“No, that’s not correct.

Music plays with

composition, a learner

Think how many quarter

strange, unexpected

puts only three quarter

notes you need in 4/4 time

consequences.

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notes in a common time

and try again.”

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measure.

feedback yet, even if you know their plans will fail. Let learners try their plans and see the results. Provide hints if their next plans repeat previous errors.

Intrinsic feedback in e-learning typically causes a positive domino effect. Consider these likelihoods:

• The design will probably speak to learning outcomes the learner values.

• The context will relate strongly to actual work or performance conditions.

• Tasks are likely to be multistepped.

It’s actually possible that all seven of the Magic Keys to motivating e-learning will be incorporated as a result of working toward intrinsic Seven Magic Keys to Motivational e-Learning

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feedback. If you specify intrinsic feedback as a design requirement, you’re likely to build very effective e-learning—and it won’t be boring.

EXAMPLES

Intrinsic feedback is featured in nearly all of the examples included in this book because I feel it’s fundamental to good design. Intrinsic feedback couples very nicely with delayed judgment, the next Magic Key, so review all examples with an eye for intrinsic feedback.

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7

Magic Key 7: Delay

Judgment

In e-learning, it’s possible to assess each gesture a learner makes and communicate the appropriateness of the gesture to the learner. This capability is, in fact, one great advantage of computer-delivered instruction.

Unfortunately, judgment of every step transfers responsibility for monitoring the validity of a course of action from the learner to the instructor or instructional application. Sometimes it’s appropriate to give immediate feedback, but often it isn’t.

Many e-learning designs that try to go beyond presentation of information use personal mentoring as a model of instruction. We feel greatly privileged to have an accomplished individual attend only to us and assist us in a course of learning, so it would seem that good emulation would create a welcome learning opportunity. Unfortunately, assumptions about what good mentors do are often faulty.

A good mentor allows learners to make mistakes and then helps them k

understand why the mistakes occurred and also the consequences that k

occurred. A good mentor knows when to keep quiet, when to present information, and when to ask questions. In many cases, it is much better to allow learners to evaluate their own performance than to immediately evaluate it for them. If judgment is immediately imposed on learners, they are robbed of a very beneficial activity, however grateful they may be. Discerning between good performance and poor performance is an important component of learning.

A-ha!

When I ask instructional designers what constitutes good instructional design, I receive a wide range of answers. One frequent and fascinating response is that good instructional applications invoke a steady stream of

“A-ha!” experiences. Everyone agrees. Epiphany is a wondrous thing!

Great satisfaction comes from meeting a challenge successfully, even if the competency demonstrated is relatively useless. When the competency really means something, when it actually empowers us to do things we care about, the success—the “A-ha!”—can be prodigious. It is, in fact, this quality that we seek and should perhaps expect from a technology that has so few boundaries.

Too bad we so often get “Huh?” instead of “A-ha!

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Valuable U-Turns

If an assessment is given following each response, it’s harder for learners to focus on the bigger context; they tend to focus only on the singular response at hand. There are occasions when what we are trying to teach is an isolated, single response, but most education and training challenges are far more complex. For these types of learning, delayed judgment is appropriate.

Suppose learners were working on the following subtraction problem.

It wouldn’t be surprising if a learner began by subtracting 8 from 20, getting 2:

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Buzz! You could make the e-learning application respond instantly, indicating that an error was made. You could tell the learner to reverse the numbers—to subtract 20 from 108, and then use the sign of the larger number. But what if you waited? The learner might proceed with: And then realize that the approach wasn’t working. The number 12

really doesn’t describe any relationship between ±108 and 20. If the learner held the bigger concept of negative numbers and positive numbers lying on a continuum:

–30

–20

−10

0

+10

+20

+30

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and therefore understood that the positive number (20) would push the negative number (108) back 20 notches toward 0, the learner might, on his or her own, decide to try an alternative approach, quite possibly constructing the correct one along the way:

Of course, there are other things learners might do as well, such as getting +88. They might also get −128 or +128. Having time to evaluate is precious, important learning time. Our software should not interrupt and intrude into it. But it can and should silently monitor learners’ various attempts, respond to questions, and provide reminders when asked, otherwise staying silent until the learner concludes he or she has reached the correct answer. A wonderful opportunity exists for an “A-ha!” realization at this point, and learners will need only the slightest confirming feedback k

to feel rewarded.

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Immediate feedback deprives learners of opportunities to make U-turns—that is, opportunities to correct themselves, to go back a few steps, or to start over to see if they are right or what might be going wrong. By evaluating a specific response within a meaningful context, learners begin to take responsibility for evaluating their behaviors.

Just as important as having the basic skills is the ability to assess one’s own work properly and habitually. It contributes greatly to success in real-world performance. Providing opportunities to build and rehearse these work habits, supported by e-learning software, provides a vastly more interesting, valuable, and effective learning experience. It’s not boring, either.

It’s important to remember that the appreciation and understanding of context may well be more important than any one skill and that developing each related skill will be much easier if the learner has a firm grasp of the big picture—of the context. Delayed judgment is an extremely helpful technique for keeping a proper orientation and avoiding the acquisition of detached skills and facts that tend to have value only for answering multiple-choice questions. Interestingly, e-learning is uniquely capable Seven Magic Keys to Motivational e-Learning

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of giving both instantaneous judgment and delayed judgment. We need to use these capabilities wisely.

Why, You Ask?

We can’t see what learners are thinking, and neither can e-learning software, unless learners communicate each step as they work toward an answer. Although one can consider requiring learners to declare each intermediate step, it sometimes makes more sense to ask afterward. In doing so, we might actually facilitate learning epiphanies.

The technique is reasonably simple. After learners have responded (answered a question, solved a problem, made a decision, etc.), you ask them, “Why is this the right thing to do?” or “Why is this the correct answer?” (See Figure 10.53.)

There are then four possibilities—two when learners give the correct answer and two when they don’t.

Even when giving the correct answer, learners may or may not be able to justify it—such as in the case of a lucky guess.

With an incorrect answer, learners may cite valid attributes about the answer given, but these attributes would not relate sufficiently to the k

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FIGURE 10.53

Ask learners why their answers are correct.

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problem and therefore wouldn’t justify the answer. Alternatively, learners may give points that would actually justify another answer, perhaps even the correct answer, but not the one given.

Delayed Judgment

Critical to the full effectiveness of this approach is the delay of judgment.

Feedback is not given until learners have submitted justification for their answers (i.e., learners are not told whether they are correct immediately after they answer). This delay is crucial, because while learners are working on justifying their answers, there is a high probability they will realize they have given the wrong answers. We therefore allow learners to back up and change their answers and to do so as many times as they desire until they have both answered correctly and justified their answers.

It’s very rewarding for instructional designers to observe learners working through an implementation of this paradigm. Many learners cannot help muttering out loud as they realize they cannot justify their answers and that the answers they gave were wrong. Learners may feel privileged by the ability to correct themselves. Combined with multistep tasks and opportunities to back up, delayed judgment can provide fascinating and effective learning experiences.

Many permutations of this design are possible. The approach can be k

k

articulated into sophisticated paradigms, including those effectively incorporating artificial intelligence. But the use of this design is quite practical once the basics have been implemented. The structure can be used over and over again with different content for cost-effective, rapidly implemented learning solutions.

Example

AUTONATION

e

www.alleninteractions.com/autonation-service

Context: An interactive sales scenario with simulated customers with concerns, questions, and buying parameters.

Challenge: Using the provided sales model, good relationship and persuasive selling techniques, and access to the sales manager, close the sale on an identified vehicle with acceptable terms.

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Activity: Given an offer and customer(s), learners interactively choose the best answers and questions to communicate and also when to go to the sales manager or attempt to close the sale.

Feedback: Immediate feedback is given via customer satisfaction meter, facial expressions, and customer responses. Delayed feedback is given based on results of “the close.”

Target Audience: All service advisors, including new service advisors with no relevant experience, new service advisors with previous experience, existing service advisors, and service manager mentors.

Learning Challenge: The customer care learning and performance team needed to create a brand environment that fostered superior customer satisfaction and retention with every interaction. To accomplish this goal, they needed engaging, consistent, and repeatable training that engaged learners in customer-focused simulations designed to emulate AutoNation’s expectations for a peerless customer experience consistent with their brand.

Learning Solution: This e-learning solution provides many scenarios where service advisors make choices that impact their success in a simulated environment, allowing them to practice and prepare for real k

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customer interactions. Launched in April 2014, this interactive e-learning course provides engaging practice and simulations that define the service advisor role throughout the AutoNation customer care service process. There are eight comprehensive modules designed to guide the service advisor through the AutoNation way of delivering a peerless customer experience. By the end of the course, learners are able to improve their performance of the service process to meet and exceed AutoNation’s customer care standards.

In this solution, delayed judgment is essential since in real sales situations there may be many paths to a sale, though some are better than others. The required skill is much more than just knowing what to say or when to ask for the deal; it requires the sales person to assess the situation and react to questions, objections, and even responses to previous decisions that may have been less than optimal. Once the learner selects the “Ask for the Sale” button, he or she is presented with the outcome of his or her sales approach. The outcome could be customers walking away for good, wanting to take more time, making a counteroffer, asking more questions, or going ahead with the deal.

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FIGURE 10.54

The dialog may take many paths. Some messages are good at some times and not at others.

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FIGURE 10.55

Intermediate consequences are

evident in the customer replies.

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FIGURE 10.56

The delayed final feedback is structured to

reinforce the company’s sales process.

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The Takeaways

I can’t stress strongly enough the importance of considering motivational factors in instructional design. In many of my presentations, I do my best to make the following case: If you do nothing other than address learner motivation, you may have done the best and most important thing you can do. In a presentation to one of America’s most prestigious corporations, I explained why this is so important and the effects of doing it well. I listed some specific ways you can do it, which are described in this chapter.

I demonstrated examples.

The response?

“This was very interesting, but we really need practical help and direction on how to design e-learning applications. We have a lot of content and not a very big budget. What’s the most cost-effective way to present a lot of content?” Sigh. Just shoot me!

Presenting a lot of content that has no chance of affecting behavior (or even of being recalled a few days after training) can never be cost-effective.

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Period. It’s a waste of money and a lot of time. With all apologies, no matter how politically correct and popular it may be, it remains a stupid thing to do.

Look: Dealing with motivation to learn is doable. It is what you need to do. It will turn heads and engender questions—possibly skepticism. But do it anyway. It’s right, and it works—big time.

Apply as many of the Magic Keys as you can, but always one or more: 1. Build on anticipated outcomes

2. Put the learner at risk

3. Select the right content for each learner

4. Use an appealing context

5. Have the learner perform multistep tasks

6. Provide intrinsic feedback

7. Delay judgment

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Chapter 11

Navigation

The two-dimensional world of computer displays prohibits exploration of an e-learning application in the ways we naturally like to explore things, such as the way we examine a book by leafing through its pages. We can’t lift an e-learning application to sense the volume of its contents. We can’t typically skim through its contents, observe the style and clarity, review the illustrations, skim through reference citations, or check for specific items via an index.

Navigation is the component that controls the learner’s ability to size k

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up an application, determine its value, and access its contents. It is the steering wheel of the application. It is the component that determines the learner’s ability to explore and to control the application for personal needs. Unfortunately, in e-learning we can see only what the designers and programmers chose to reveal, and that isn’t typically very much.

Navigation is only one component of an e-learning application, but it is an essential component that is often given too little design attention, with the result of entrapping learners into a fixed flow. Too often, navigation is offered as the application’s interactivity, which means there won’t really be any interactive instruction.

Victim or Master?

Learners are sometimes so controlled by e-learning applications they feel victimized. They have few options, if any, beyond how to answer questions. Learners can perform the next step put in front of them or quit—and that’s it. Those are the options.

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Good navigation does just the reverse. It provides learners as many options as are reasonably possible to help them feel comfortably in control and, most important, having everything they need for learning.

Navigation Services

Where navigation stops and individual interactions start is sometimes a gray area. Navigation gets learners to the interactions and resource materials needed, but because it overlays all the other components, developers can use navigation to allow learners to exercise control to get the most out of their time. When navigation is built thoughtfully, learners can use it to great advantage, allowing navigation to become something of a learning event itself. A valuable learning activity can be deciding when to take control and use a navigation service versus continuing a current activity.

In the pursuit of helping learners become life-long learners and able to take advantage of learning opportunities that may not be well structured, learners need to take responsibility for finding the guidance they need, getting evaluation for their performance, and practicing. Navigation in e-learning can give learners practice in taking responsibility for getting k

the most of the learning time.

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Navigation can be many things. Services include:

• The ability to preview and personally assess:

What can be learned

What the experience will be like

How valuable it will be

How much time it will take

How difficult it will be

The structure of the content

What media will be available

• The ability to:

View menus and submenus

Select menu items

Determine whether prerequisites exist and if they have been met Go to selected items

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Determine where they are within the structure

Back out of selected items

Resume partially completed topics

Access help on using the application

Access instructional help, examples, glossaries, reference material, or other resources

• Basic controls to:

Back up and review

Back up and try different answers or options

Skip ahead, preview, and return

Bookmark and return to points of interest or concern Restart and resume

• Once learning has begun, the ability to determine: How much has been accomplished

The scores or mastery levels earned

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How much remains to be learned

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• Dashboard ability to see performance details, such as: How much time was spent in each activity

How many trials were necessary for initial success

How many practice sessions occurred

What the scores on practice sessions were

Navigation ties together the structural components at many different levels, much like the trunk of a tree with all its limbs. Interactions are the essential leaves on the tree, organized into branches and giving the whole structure a reason to exist.

Reusable Navigation

Because navigation can provide many valuable learning and interface functions, designing and developing good navigation structures can be difficult and costly. The details are surprisingly tedious to work out. Fortunately, navigation is an area in which reusability can save e-learning Navigation

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design and development costs. Although custom-designed and -built navigation can capitalize more strongly on unique aspects of the content, successful structures can often be reused in a variety of applications. Once the user interface is refined and the underlying programming is perfected, navigational structures should need only minimal testing for reuse. More of the budget can then be applied to building better navigation capabilities that are devised specifically for the instructional content.

Developers commonly choose a mixture of custom development and reapplication of existing navigation structures. After a number of e-learning applications have been developed, teams often find they can reuse many of the navigational structures with only moderate amounts of revision. The revisions allow better integration with the subject matter and the overall instructional context chosen for the application. Yet reuse allows development of more sophisticated learning aids than could be afforded by just one project. To achieve appreciable savings from reapplication, it is important to organize and structure navigation systems carefully so that modification and reapplication is possible.

Learning Management Systems

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A word about learning management systems (LMSs). Commercial LMSs have evolved over time, adding valuable services and capabilities, but also high costs and complications. The LMS concept, formerly known as computer-managed instruction (CMI), was developed to make delivery of individualized instruction practical. It was needed because individualization allowed students to take the varying amounts of time to learn, causing scheduling complications not faced in traditional synchronous instruction.

The concept of an LMS is not new. See Mitzel (1974) and Szabo (1976) for foundational discourse on the origins of LMSs. LMSs were invaluable for individualized instruction when the development and delivery of e-learning was very costly. It intermixed all available forms of instruction, including classroom instruction and e-learning, and provided a foundation to which related instructional events could be added over time without disruption. The practicality of CMI led me to focus much of my early career in e-learning on it beginning with the development of

“Bio/CMI,” an LMS used in the National Science Foundation’s Biology Learning Demonstration Center at The Ohio State and South Dakota 214

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State Universities in the early 1970s (Allen, Meleca, and Myers, 1973).

Subsequent to that, I initiated development of the PLATO Learning Management System beginning in 1974 at which time my research noted there were already about 40 documented LMSs, but none of them used in multiple locations (except mine!). I am a strong proponent of LMSs as support necessary for practical individualized instruction, but I’m dismayed at the direction many of them have taken.

The primary concept of an LMS is to provide services for individualized instruction through:

• providing registration and courseware access services to learners, including e-learning and all other forms of learning available to learners

• automatically collecting, analyzing, and reporting information regarding each learner’s progress and performance

• facilitating optimal learning by directing individual learners to the learning events that would statistically seem most beneficial

• providing actionable feedback with respect to the value, strengths, and weaknesses of each managed learning resource

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These capabilities are far from trivial, but they can be built far more easily today, especially the administrative features of learner registration and data collection. But the primary instructional value isn’t the administration of enrollment. The instructional requirement is for systems to be smart enough to assess learner progress and needs algorithmically, select optimal learning experiences from among those made available, measure the effectiveness of those selections in general and for each individual, and improve selection effectiveness as accumulated data validate. These were actually the capabilities of early systems, such as the system provided by PLATO, that modern systems need to embrace more fully.

When LMSs enable the invaluable benefits of individualization, learner navigation is handled partially by the LMS in concert with navigation provided within the courseware itself. It’s important that LMSs communicate in an articulate manner with courseware such that learner options are activated when most appropriate. Further, the system should learn and communicate the advisability of alternate paths learners might choose to override system-generated prescriptions. In this way, technology-enhanced instruction can begin to realize the promise it’s held for many decades.

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Navigation Imperatives

There is much to navigation design, as you can deduce from the number of possible capabilities listed earlier. There are many successful approaches, but for each one, there are also many unfortunate paths. To provide practical guidance here, I have focused on essential navigation design concepts and those most frequently misapplied or overlooked. The result is a list of simple imperatives—simple in concept if not always in implementation.

Navigation Imperatives

1. Let learners see what’s here.

2. Let learners see how the content is organized.

3. Let learners see where they are.

4. Let learners go forward (when they want to).

5. Let learners back up (when they want to).

6. Let learners correct their errors (themselves).

They aren’t imperatives in the sense that omission means certain fail-k

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ure. They are imperatives in the sense that e-learning is usually much, much more effective and able to provide the needed return on investment when the imperatives are implemented. Whether you are buying, building, or contracting for the development of an e-learning solution, the imperatives should usually be included in the specifications. Why wouldn’t you?

Let’s look at each imperative individually.

Navigation Imperative 1: Let Learners

See What’s Here

Children have their school day structured for them and make few decisions about how their time will be spent. In contrast, as adults in a much too hurried world, most of us are constantly trying to assure ourselves that we are using our time wisely. Our time is valuable—we don’t want to throw it away unless we choose to do so. We guard against letting others waste it.

Even if we actually have only a few options, we don’t like being treated as schoolchildren. We don’t like to hear, “This is good for you. Do it now.”

We like to know how long something is likely to take, to have the option of doing it now or later and to decide in what order we will do things.

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As adults, we like to know the purpose of our activities. We like to get some perspective, consider options, and then decide whether to make the commitment or to search for other options.

Sure, adult learners can be forced into the schoolchild’s role. Some adults snap right into it, having become accustomed to it and probably successful at it in their youth. But even those willing victims are likely to have a better experience if they have the means to survey the next opportunity before the event launches in earnest irrespective of reservations and readiness. How long will it take? What does it cover? How hard will it be?

Does this look interesting?

Is It Bigger than a Breadbox?

Taking a content-focused stance, many designers launch right into instruction following a list of learning objectives. (By now you know what I think about that.) If they follow my suggestions, they will make the effort to communicate the value of the pending learning experience in a meaningful way before attempting to deliver it. They will build motivation and note special learning aids that have been provided. But what authors might not think to do is give learners any sense of how big this thing is, what shape it is, what kind of crust and filling it has.

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You can size up a book fairly easily. You can assess some of its characteristics even as it sits on a shelf. Pick it up and you can quickly check to see how many pages it has, about how much is on a page, how it’s divided up, how big the divisions are, what the illustrations are like, how useful the index and glossaries appear to be, and so on. In just a few minutes standing in a bookstore, you can set some fairly reasonable expectations of what reading a book will be like.

Of course, the book designer is doing everything possible to give you a positive impression quickly. But you have the option to jump directly to the meat of the offering if you want to. And see for yourself.

Not so with e-learning, unless the means are provided to browse, play around, test features, and get to randomly selected points. Learners need Navigation

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your help to be able to do those things that give them a sense of control and self-determination.

Example

Sneak Peek

https://zebrazapps.com

Previewing

ZebraZapps is a next-generation system for authoring and publishing instructional software and other interactive applications. In it, we’ve attempted to solve many of the causes that inhibit e-learning from being what it should and can be. For example, one of the reasons learners don’t get the opportunity to browse through courses prior to working through them is that authors want to control every movement of the learner—what learners can and can’t see at all times. It’s the victimization of learners I talked about earlier. Another reason is that most authoring software doesn’t make it easy for learners to skip around, do a little of this here k

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and a little of that there and yet not lose their place anywhere they started working. But it should. This can help learners optimize use of their time and take more ownership of their learning.

ZebraZapps as a terrific, easy-to-use (you just switch it on) utility to allow learners to familiarize themselves with an instructional application.

It displays course content in book-like format and allows learners to flip through it. Learners can be allowed to enter into any interactions they find appealing, but they can also be restricted to just looking until they’ve worked through prerequisite learning events. Some parts of the application can be kept hidden, of course, and presented in context as appropriate.

As shown in Figures 11.1 and 11.2, ZebraZapps can deliver learning apps on mobile devices, laptops, and desktop machines using appropriate user gesture recognition on each platform. When using Sneak Peek, learners can just swipe the screen to preview all instructional events and reference materials the author makes available to preview. If allowed by the author, with just a simple tap of the screen or click of the mouse button learners can start or resume full interactivity anywhere within the e-learning program or at preceding author-specified points as may be appropriate.

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FIGURE 11.1

ZebraZapps’ Sneak Peek feature used here on a mobile device by k

International Dairy Queen to allow browsing through course contents.

Completion Time Estimates

Some e-learning applications provide time estimates to help learners plan their time. The estimates can only be approximate, because the actual time needed depends on the learner’s readiness, abilities, distractions, and many other factors. But learners can understand this and appreciate the estimates. Combined with a good browsing facility, time estimates can soothe many of the discomforts of e-learning and make adults feel more like adults.

Navigation Imperative 2: Let Learners

See How the Content Is Organized

Navigation, by definition, builds on content organization. This creates an opportunity to let learners review the organization of content, which can help them not only get their bearings but also learn something about the content itself. If the content is organized from easy to hard, learners will gain a sense of what should be easy for them and what may take Navigation

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FIGURE 11.2

ZebraZapps’ Sneak Peek feature used by Hilton allows browsing, k

quick learner preview and access to course content.

more effort; if content is ordered according to a process, the structure will impart knowledge of the proper sequence; if content is ordered chronolog-ically, learners can get a sense of precedents and consequences and so on.

There is often a necessary compromise between the efficiency of navigation and the information that navigational controls supply. A simple click to go to the next sequential topic doesn’t even require presentation of a list of topics, but omitting orienting information for the sake of streamlined navigation would be an unfortunate extreme of simplicity over being more helpful. However, requiring learners to open layer upon layer of hierarchical menus to access the next topic would err at the opposite extreme.

Excellent designs are both efficient, allowing quick and easy access to content, and informative, allowing users to see the content organization clearly. And they do more: They also present multiple points of view to the organization. They might, for example, provide the following views:

• Sequence of topics in the order of recommended study

• Structured listing of topics by discipline, such as accounting, management, and communications

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• List of topics by instructional activities provided, such as simulations, drill and practice, and problem solving

• List of topics by media, such as videos, animations, and narrated text All these views into course structure add value to the e-learning application by either providing learning support natural to some other media, or making use of technology to provide support not possible with other media. Of course, the navigation design should also provide the convenience and functionality of taking learners directly to any topic they want to investigate further, perhaps by tapping keywords found anywhere in the courseware.

Navigational Imperative 3: Let Learners

See Where They Are

Once you’ve launched yourself into an e-learning experience as a learner, it can be difficult to know where you are. Again, the typical indeterminate nature of e-learning creates uneasiness, so the design needs to compensate by providing a sense of orientation and position (see Figure 11.3).

There are many creative ways to help learners see where they are.

This may be a good place to have fun with the design, but even a sim-k

ple thermometer or a dot moving from one end of a line to another as a k

report of progress will become a meaningful display of information for learners who are anxious to know how much they’ve accomplished and what they have left. It’s not unusual for the learner’s vocabulary to reflect how important progress measures are: “My dot is halfway there!” “I’m in the last building!” “Only one more stone to complete my pyramid!” They even compare progress notes with each other: “How far did you get? Have you made it to the green level yet?”

Of course, we’d rather they were boasting about how much they have learned, but excited exclamations over their progress is almost as good.

Note: As desirable as a progress bar is, it shouldn’t dictate linear sequencing of content. Allowing learners to skip around, while perhaps unnerving some authors, is almost always a wise design. Learners will probably opt to move through the course linearly anyway, but letting Start

Finish

FIGURE 11.3

A simple, informative progress

indicator.

Navigation

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it be their choice helps overcome the victimizing nature of structured software. Even if content access isn’t linear, a progress bar can be based on accumulated mastery and indicate how much has been accomplished and how much remains. A menu or table of contents can provide more specific information by showing which items have been started, which have been completed, and which have not yet been touched (see Figure 11.4).

Navigation Imperative 4: Let Learners

Go Forward

“I don’t want to back up to go forward,” said Carl Philabaum, in one of his many profoundly insightful moments. Carl, one of my fellow cofounders of Authorware, Inc., often brought brilliant clarity to our discussions about user interface. Once you saw his vision, you couldn’t possibly be happy with it in any other form. As usual, he was right on this point about going forward.

Why would you want to back up to go forward? Yet learners often do have to return to a previous menu to pick the next topic. Learners don’t want to be forced to back up through a series of submenus to get to the next topic. They don’t want to have to return to the table of contents just to go on. Designers might justify such an annoying requirement by k

suggesting that it helps learners keep the structure in mind, and there is k

that advantage. But if learners want to see the structure, let them. If they want to go forward to the next item in their path, let them do that, too.

FIGURE 11.4

Helpful progress indication.

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Heeding Carl’s principle and also providing the value of a course menu to remind learners of what content is included, is the possibility of drawers, pop-ups, and other quick overlays to provide nearly instant access to navigation. While it may involve an extra click, I think Carl wouldn’t mind nor would our learners.

There’s no reason you can’t remind learners of the overall structure without forcing them to retreat first. You can do it with an overlay or slide-out graphical map, for example, showing learners where they are currently. If learners now want to be somewhere else, they can just click another point on the map. With a single click they’ve gone forward again.

Easy. Thanks, Carl.

The ZebraZapps template shown in Figure 11.5 depicts an always-present main menu with current place and progress reporting built in. One click in the course editor gives the author a complete and editable structure. Contemporary authoring tools remove any excuses for not providing effective navigation.

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FIGURE 11.5

Templates ease development of helpful navigation.

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Navigation Imperative 5: Let Learners

Back Up

It can be a programming challenge, especially if the learning experience is a complex simulation, but being able to back up is usually essential to providing an optimal learning experience. We often think we understand something, only to find out a bit later that we really don’t. Being able to back up at that moment of realization is very important, especially for adult learners who don’t want to be constrained and are responsible for their own learning.

Not being able to back up raises anxiety, creates a helpless, lack-of-control feeling, precludes potentially beneficial experiences, and suggests to learners that:

We’re in charge here, not you. If you had been paying attention, you wouldn’t need to back up. If we had thought people couldn’t understand this in one pass, then, of course, we would have let you back up. Because we must take responsibility for your learning, and you didn’t take the opportunity to get what you needed, here’s what’s going to happen to you next. . . .

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A bit dramatic, perhaps. But not providing a means for backing up is k

a regrettable constraint in many e-learning applications. It severely limits their potential.

In simple page-turning applications, it is not difficult to back up. But with highly interactive e-learning, backing up can become complex—so complex, in fact, that development teams sometimes abandon efforts to build powerful learning experiences because they cannot devise a backup function. This is a regrettable tradeoff. We need both immersive learning experiences and the ability to back up through them, perhaps changing answers to see different consequences.

If the design requirement to allow learners to back up is established early in the design of each application, the team will find it isn’t usually as difficult to build as it might seem, assuming the use of a powerful authoring tool. Programming the function is a bit harder, but making provisions for backing up isn’t an unreasonable effort as long as it is anticipated at the start. On the other hand, it’s almost impossible to retrofit a backup capability into a completed or nearly complete e-learning application, so it is essential to be clear about this early in the design process.

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Navigation Imperative 6: Let Learners

Correct Their Errors

The experience of privately discovering you have made a mistake, fixing it, and finding satisfaction in your work, describes the perfect learning experience. The outcome includes knowing what happens when you make the error and knowing what happens when you do the right thing. Instead of being told what to do, you find the effective path and appreciate it in all its nuances more than you ever could by simply following step-by-step instructions. The fidelity of your learning is at maximum. Why, then, don’t we design learning experiences that enable and encourage such events?

Perhaps it’s because some extra work is involved. It takes work to provide intrinsic feedback through which learners see the consequences of their choices directly, instead of hearing from you, “No, that’s not correct.

Try again.” It takes work to allow learners to manipulate objects, make decisions, and collect information before they make those decisions. It takes cleverness to construct challenges that reveal important truths or fully present opposing points of view.

The learner-interface control for backing up may be only a simple Back button. However, helping learners know where they are, what their previous decisions or actions were, and the state of a simulated process or k

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product exploration will also be essential interface components. These can range from simple to very complex.

Yes, it takes some effort to reap the value learning technology can provide. And it takes more creativity than does the simple presentation of information. But once you’ve done the right things, the costs stop and the benefits will continue to accrue for each learner and the organization.

If you don’t, the costs just continue to accrue without the benefits. Give learners the means to correct themselves. It’s powerful.

The Imperatives

There are always exceptions, but justifiable exceptions to the listed imperatives are rare. Implementing these imperatives pay off handsomely in the successful learning experiences they enable. Unless there are incontestable objections or restrictions, insist that your learning applications follow the imperatives. Write them into the specifications whether you are buying, building, or contracting for e-learning solutions.

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Additional Learner-Interface Ideas

Table 11.1 shows some additional learner-interface features you should consider. These aren’t imperatives, but you can expect them to pay back handsomely.

I have seen all these capabilities implemented at one time or another in various e-learning applications. They are much appreciated by learners, who, for example, like the ability to download and even print notes and selected content elements for later reference. Once you have developed the software for these features, the same functionality can be dropped into applications at an acceptable rate of expense. They resonate well with adult learners, many of whom remain skeptical that all this computer learning is really an improvement over more traditional methods of instruction. They recognize the learner’s desire for freedom and control and empower those who truly want to take responsibility for managing their own learning.

Navigation Examples

It always helps to see examples, so before we take up any other topic k

in navigation, let’s take a look at a couple of very different approaches k

to navigation.

TABLE 11.1

Handy Learner-Interface Features

Feature

Advantages

Bookmarking

Learners can mark and return to any marked point.

Personal index

An elaboration of bookmarking. Learners can essentially create a titled list of selected contents or interactions. They can use default titles provided by the application or use titles they find more meaningful. Each title is linked to a point of interaction, allowing learners to return to that point on demand.

Highlighting

Just as with a book and highlighting pen, learners can drag the cursor over items to mark them with a distinctive color.

Margin notes

Learners can type in the margins of screen displays. In some implementations, these notes are automatically assembled in an online notebook. Learners can then click any note to return to the screen and see the note in its original context.

Posted notes

Learner-created notes can be stuck anywhere on screen displays.

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Example

NYU Medical Center

Patient record-keeping software

http://www.alleninteractions.com/nym-medical

NYU Medical Center needed to train their staff on the new ICIS patient record-keeping software. Instead of a content-centric approach of teaching what to click and when to click it screen by screen and field by field, training was broken down into many specific job-related tasks. These tasks were then presented in a guided software simulation model, but only on a need-to-know basis. Learners started the program by choosing their role, and the program presented only the tasks required for proficiency in their job.

The navigation bar (see Figure 11.6) allows students to control learning events by asking for a hint a demonstration of the current gesture required (click or text entry), or a demonstration of the entire task from beginning k

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to end.

The navigation bar also provides a progress meter showing step-by-step completion of the software task. This navigation bar paired with the ability to judge whether the student requested a hint or a demo, and the tracking of any student mistakes during task completion allows the software to prevent student progress to the next task until mastery has been demonstrated.

In a small space, this design not only gives learners a great amount of control, but also communicates the instructional activities and learning FIGURE 11.6

ICIS navigation bar (split in two here for a better view) Navigation

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aids that are available. Once constructed, authors can turn all their efforts to content development.

Example

WorldTutor

Patient record-keeping software

http://www.alleninteractions.com/nyu.medical

Originally designed for American Airlines training covering a variety of topics, including such diverse performance domains as ticketing protocols and security procedures, this structure has proved valuable for many different content domains. It has been repeatedly reapplied without incurring costs for redevelopment.

WorldTutor provides a uniform navigation structure that presents all content in a consistent layout (see Figure 11.7).

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FIGURE 11.7

WorldTutor screen layout with bottom navigation bar.

The current section and the total number of sections in the current topic are displayed above the arrow buttons. Numbered tabs represent topics. The current topic is highlighted.

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The navigation controls are concentrated in a narrow band along the bottom of the screen, maximizing the screen real estate for instructional and content purposes.

Let’s look at this system in more detail in terms of the six imperatives.

NAVIGATION IMPERATIVE 1

Let Learners See What’s Here

The navigation system accommodates several levels of organization.

A course is divided into topics. Each topic is organized into sections.

Each section might be made up of one or more pages or challenges.

This structure is displayed at all times, no matter where learners are in course.

The navigation bar shows the course structure in a very compact space.

A numbered tab represents each topic in the course. These icons are arranged in order from left to right. For each course, only the appropriate number of icons is displayed—there are no placeholder blank images. In addition to showing the number of topics clearly, the navigation bar is also effective as a more general indicator of scope. For a learner who will be completing even just a few sections in this navigation framework, a fleeting glance provides an immediate sense of whether it is a long or short course, k

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and how much time to allocate accordingly.

NAVIGATION IMPERATIVE 2

Let Learners See How the Content

Is Organized

The topic tabs give a visual indicator of the skeleton of the course but do not convey anything about the content except to indicate the recommended order of study. More details about topics and sections are available in two ways. First, the learner can move the mouse over any tab to view the name of the topic, which appears above the tabs (see Figure 11.8).

And, for even more detail, the learner can select the Topics & Objectives button (second button from the left) to view topics and sections as a list (see Figure 11.9).

FIGURE 11.8

Topic titles appear on tab rollover. As shown, Topic 1 is the

“Introduction.”

Navigation

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FIGURE 11.9

Topics listed along with content sections each contains.

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Learners can view the topics and sections list without losing their place in k

the course. Detailed learning objectives for the course are also available here.

NAVIGATION IMPERATIVE 3

Let Learners See Where They Are

The topic icons change status as the learner

moves through the course. The current topic is

highlighted and completed topics are marked

FIGURE 11.10

Topic tabs

with a colored bar (see Figure 11.10).

show status and progress.

Topic 5 is the current topic.

Topics 1, 2, and 4 have been

completed. Topics 2 and 4

are earmarked for review.

NAVIGATION IMPERATIVE 4

Let Learners Go Forward

This navigation allows users to go forward in several ways. At the most basic level, the Continue button takes the learner through the entire course in the established order (see Figure 11.11). The continue function is disabled only 230

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during challenges when the learner must successfully complete an activity before being allowed to proceed within the topic.

FIGURE 11.11

Handy navigation buttons.

The arrow buttons allow learners to move forward (and backward) on a section basis rather than just one page at a time. The notation above the arrow buttons provides useful orienting information regarding the number of sections in the current topic and where the learner currently is working.

The learner can also skip forward to any topic simply by clicking the corresponding tab, if the author allows it.

NAVIGATION IMPERATIVE 5

Let Learners Back Up

Of particular interest in this navigation scheme is the bookmarking feature. Learners earmark pages for later review by clicking in the upper left corner of the screen. Earmarked pages are indicated at the upper left of k

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the screen as well as on the topic tabs.

Conveniently, the learner can move backward in nearly all the same ways as forward. Clicking the left arrow button takes the learner to previous sections (see Figure 11.11). Clicking the up arrow button restarts the section. Clicking the icon for a topic that has been studied previously takes the learner back to that topic.

NAVIGATION IMPERATIVE 6

Let Learners Correct Their Errors

This navigation model is somewhat neutral in regard to making mistakes. However, it does allow corrections in that learners are generally one or two clicks away from any part of the content, so an unintended click can be corrected quickly and easily. The Restart button (up arrow in Figure 11.11) is available in case the learner missed or did not attend to the audio narration.

Extended Features

In addition to illustrating the imperatives, the WorldTutor structure provides some additional and handy learning support features. An Options button reveals a set of buttons for these features (see Figure 11.12).

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The buttons include:

A glossary of definitions for specialized vocabulary A help function to describe lesson features

A word finder that enables learners to search the course for keywords A volume control

A flash card system that allows learners to tag interactions and review them as a drill later

A comments section where the learners can write notes for themselves, their instructor, or the system administrator

FIGURE 11.12

More handy navigation services.

All these features are handy, and many learners have come to expect them today, except perhaps the flash card system, which I find quite k

inventive and valuable. The WorldTutor model goes even beyond its ear-k

marking feature that’s very handy for review, to allow learners to build a flash card deck on topics they feel they need to rehearse. At any time, learners can call up their flashcards and work through them, rehearsing to the point of confident mastery.

Navigational Metaphors

Metaphors are often used to impart instant appeal to navigational structures, playing on the familiar function of things. A building, for example, has analogies to the usual components of an interactive course of instruction: the building as a whole (the course of instruction), the reception area (a place to register or log on), the building directory (list of main topics), floors of the building (levels of skill and challenge advancing to the top), rooms (modules or subtopics), labs (places for experimentation), gym (place for practice), and so on.

Any structure with multiple parts can be used as an organizational and therefore navigational metaphor, such as a book, a car, a city, a train, 232

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or a camp. Consider also a road map, a treasure map, or a pyramid with all its hallways and vestibules.

Metaphors can be powerful, providing terminology, a familiar structure, and even visual representation. For a complex structure or for a very large application, they can provide welcome orientation.

Some Concerns

Although metaphors for navigation—or for any interactive controls for that matter—can be powerful, they’re sometimes used to mask a lack of good instructional interactivity. It’s very disappointing to begin an e-learning application with an extravagant rendering of a metaphor, only to find that once you’ve selected your topic of instruction, the metaphor has no further utility. Even worse is to find that the interactions are shallow and lacking in imagination because too much effort was spent devising the navigational window dressing.

To make it even worse yet, metaphors are sometimes forced into every nook and cranny of interactions, where they provide no benefit, become wearisome, and may actually distract or confuse learners.

Compounding all these problems, metaphors sometimes feel childish and demeaning. There’s a fine line between gamelike metaphors—those k

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that can provide energy and a helpful lightheartedness to otherwise taxing learning events—and silly and juvenile metaphorical contexts that add little value and may impede learning. From my perspective, it’s usually best to find interest and energy in the content and skills being taught and build directly on those. Adding a lot of ornamentation suggests you don’t know how to make your content truly interesting and relevant.

Simplicity Is Best

In general, the simplest way to represent the structure and content of a course of instruction may be the best. Selecting a segment of content to study shouldn’t involve learning the controls of a starship to fly through an alien sector to the next solar system. As fun as that might be, it seems more beneficial to put such authoring talents and resources to work building meaningful learning experiences.

So, if you can’t come up with something elegant, simple, and relevant to the learning, consider giving navigational metaphors the metaphorical boot!

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The Takeaways

Navigation capabilities provide the backbone and many of the instructional services learners need for a successful learning experience. This chapter described a number of very important but too seldom found navigational features. Because they are so valuable, they were dubbed imperatives herein to suggest that there should be irrefutable objections before any project team decides to omit them.

The navigation imperatives require letting learners: 1. See what’s here

2. See how the content is organized

3. See where they are

4. Go forward

5. Back up

6. Correct their errors

Finally, a few comments were offered on navigational metaphors.

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Although metaphors can help learners understand application structures k

more quickly, they can easily become overworked, too cute, intrusive, and annoying. If structures need a metaphor to be readily understood, they may be overly complex. However, metaphors are too often used to explain structures that are easily understood without them. My recommendation is that metaphors be kept to a minimum and navigational structures be kept clean so that maximum attention can be given to what really counts: the development of effective learning experiences.

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Chapter 12

CCAF and Interactive

Instruction

We come now to the truly fun and exciting point at which everything comes together as a creative blend of instructional design, subject matter, management vision and objectives, multimedia treatments, and technology. It comes together for the purpose of enabling specified behavioral changes to happen—the changes needed for performance k

success.

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In this chapter, I have attempted to get at the heart of instructional interactivity. I’ve tried to separate the wheat from the chaff, as they say:

• To explore the differences between mechanical interactivity and instructional interactivity

• To provide a framework for thinking about instructional interactivity

• To help designers create the kind of interactivity that works to engage learners, builds needed competencies, and provides value in e-learning that fully justifies the investment.

Throughout this book, I’ve minimized theoretical discourse in favor of plain talk and practical prescriptions. It is especially appropriate to continue this approach here, as it seems to me that theory-based approaches, as much as I respect them and find them valuable, have not resonated effectively with many designers. My attempt here is to clearly identify the essential components of instructional interactivity, flag some frequent misconceptions, and provide a number of successful models—all in a way that you will find meaningful and useful, whatever your goals for e-learning may be.

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Supernatural Powers

Interactivity is the supernatural power of e-learning. It has dual powers that together are capable of achieving the ultimate goal of success through performance improvement:

• Instructional interactivity invokes thinking. Designed and used properly, interactivity makes us think. Thinking can lead to understanding, and understanding can lead to increased capabilities and a readiness for better performance.

• Instructional interactivity requires doing—to perform. Rehearsed performance leads to skill development. Improved skills permit better performance.

Natural Learning Environments

From the moment we are born, we are learners. As infants, we love learning because almost everything we learn gives us a bit more power or comfort. Even before we can actually do anything to improve our lot, we gain satisfaction from recognizing signs and predicting. We predict k

that food is coming, that we are going to be picked up, or that we are k

about to hear an amusing sound. And we are happy to be right.

Effective learning environments employ interactivity. Just as we have done from infancy on, we acquire knowledge and skills from attempting various solutions and observing their results. It’s evident in children as they undertake the myriad skills they must conquer, from communicating differentially the needs of nourishment and a diaper change to holding up their heads and figuring out how to roll over. As we grow older and acquire the ability to understand language, we can be told how to do things and when to do them.

But verbal learning dissipates quickly and easily until we’ve actually performed successful behaviors ourselves and seen the results. Even then, effective rehearsal is important to integrate new behaviors fully into our repertoire of abilities.

e-Learning Environments and Rehearsal

Interactivity in e-learning provides an important opportunity for rehearsal without the risk of damaging equipment, hurting people’s feelings, running up waste costs, or burning down buildings. Behaviors that help the learner avoid danger cannot be learned safely 236

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through experimental means except through very close mentoring or in simulated environments, such as those made possible in e-learning. And even if they could be learned in some kind of real-world environment, setup time and costs would prevent needed repetition. And, instruction of a number of people, who might be in many different locations, would present onerous problems.

Whether we are guided by a mentor or prompted by e-learning, interactivity is vital to effective learning events. As important as interactivity is for learning, however, instructional interactivity is an easily and often misunderstood concept.

Instructional Interactivity

Defined

It is difficult to define and distinguish the salient attributes of instructional interactivity. Perhaps because of this, instructional interactivity is often thought to be present when, in reality, it is not. We can be deluded by all k

the buttons, graphics, and animated effects of today’s multimedia or dis-k

tracted by visual design and presentation technologies. Based on believing instructional interactivity is present when it is not, people expect more impact from an application than it can deliver. The confusion is damaging not only because minimal learning occurs, but also because people may conclude instructional interactivity isn’t effective (even though there wasn’t any).

Instructional interactivity is much more than a multimedia response to a learner’s gesture. Playing a sound or displaying more information when the mouse button is pressed is just plan old interactivity. To be sure however, instructional interactivity in e-learning definitely does involve multimedia responses to learner gestures. Here’s a working definition: instructional interactivity Interaction that actively stimulates the learner’s mind to do those things that improve ability and readiness to perform effectively.

This is a functional and useful definition, but we need to articulate further what instructional interactivity is—of what it is composed and how to create it.

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CCAF

Thinking about all the e-learning

we may have seen, we soon realize

there are many varieties of instruc-

tional interactivity. Sometimes

Context

Challenge

interactivity simply entreats us to

rehearse fledgling skills. At other

times, it puts forth a perplexity for

us to untangle. It may even lead

us to new levels of curiosity and

to profound and original discover-

ies, not just to the identification of

Feedback

Activity

“correct” answers.

The many types and purposes

of instructional interactivity com-

pound the problem of definition,

FIGURE 12.1

Components of

but in each case, there are four

instructional interactivity.

essential components, integrated

and interlocked like a jigsaw puzzle in instructionally purposeful ways (see Figure 12.1):

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• Context—the framework and conditions

• Challenge—a stimulus to action within the context

• Activity—a physical response to the challenge

• Feedback—reflection of the effectiveness of the learner’s action Examples

Let’s look at a couple of e-learning designs, identify the components of instructional interactivity, and observe how they create effective instruction.

Example

Supervisor Effectiveness

https://sales.alleni.com/MISC/CorningSE/training1.html

username: tourbypass; password: 123456

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Context

An aerial view of a populated office work area

The depiction immediately provides an interesting visual context and creates an identifiable, real-world setting (see Figure 12.2). It gives both visual and cognitive perspective to the subject, saying, in effect, “Let’s step back and look at a typical work environment without being too involved in everyday business operations to think about what’s really happening.”

The context provides both an immediate sense of situational familiarity for the supervisors being trained and a vantage point for objective and thoughtful decision making. No large blocks of text are needed to build this valuable rapport with the learner.

This is a permissive context. Learners can jump right into the activity without any guidance or background information, or they can first request information on assessing threats.

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FIGURE 12.2

Office context in Supervisor Effectiveness training for employee security.

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Challenge

Identify the most immediate safety threat.

Employees make many comments during the day that reflect their frustra-tions, both trivial and serious, and they imagine remedies of all sorts (see Figure 12.3). The solutions they contemplate may range from silly pranks to devastating violence. Most such expressions of frustration are harmless hyperbole. They provide a means of blowing off steam. But some reflect building hostility and forewarn the person’s aggression and willingness to do harm to self or others.

The challenge for learners is to recognize potentially serious concerns among harmless exasperations.

Activity

Listen to conversations, and decide who’s making the most concerning comments. Then move (drag) that employee into your office.

Learners roll the mouse pointer over the image of each person appearing in the office complex to listen to what employees are saying to each other.

As the learner moves the pointer over speaking employees (indicated by waves animating around them), their comments appear in caption bubbles.

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Learners, all supervisors in training, select the employee making the most k

concerning comments by dragging the person’s image to the area labeled

“Your Office” (see Figure 12.4).

FIGURE 12.3

Viewing thoughts of employees.

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FIGURE 12.4

Learners drag the selected employee’s icon

into their office.

Feedback

At the gesture level, pop-up captions reward pointer placement by providing needed information. At the decision level, correct/

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incorrect judgment is augmented with action-consequence k

information.

Selecting and placing an employee in “your office” represents a decision made by the learner. In this application, feedback at this point also includes an instructive evaluation (see Figure 12.5).

When the person who is the highest-level concern is identified, confirming feedback is given (see Figure 12.6).

FIGURE 12.5

Feedback with instruction.

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FIGURE 12.6

Feedback after correct threat identification.

Identifying high-risk comments is only the first step of this learning sequence, of course. Learners are then asked what steps they would take next, such as talk to Security or EAP, and then to question the distressed employee to further determine the probability of risk and finally decide what to do about it (see Figure 12.7).

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FIGURE 12.7

Multistep activity continues with questioning the employee to gather more information.

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Analysis of Example 1

There is a lot to learn in this application, and it is fun and engaging to learn this way. In contrast, imagine a typical e-learning design instead of the one being used here: Lists of danger signs would be presented.

After reading them, learners would be given a list and an explanation of appropriate preventative actions to read. Then learners would be given scenario questions that would require them to select the right action from a multiple-choice list. No context, weak challenge, abstract activity, extrinsic feedback— boring.

Look again at how well the components in the preceding example integrate to make the learning experience effective:

• Learners not only go through comparative steps to rank the levels of concern but also symbolically move around the office listening to employees. Good supervisors are good, active listeners. They must circulate through work areas, and they must spend time listening to their employees. The interaction leads learners to envision gathering information that is critical to their responsibility for ensuring safety.

• When a security problem is identified, face-to-face encounters k

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with employees are necessary in order to probe further.

Symbolically moving the image of an employee into the learner’s office helps supervisors to imagine this encounter and to realize that preparation for it will make the task less daunting and more productive.

• When the supervisor asks probing questions, troubled employees may feel relieved by the attention and therefore speak freely, but they may just as well feel uneasy, embarrassed, and defensive. It may be difficult to get information from them. The interactions in this example are designed so that employees will sometimes answer only a few questions and then get worried and stop.

Experiencing this likely occurrence not only makes the learning more engaging but also continues to reveal the value of the learning experience to participants in preparing them to handle real-world situations.

• The focus is on actions and consequences. Although factual and conceptual information must be learned, it is offered within the context of task performance, stressing its relevance and making it more interesting, easier to learn, and easier to remember.

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No Design Is Perfect

The feedback could be more intrinsic and possibly more effective. For example, if the learner mistakenly identified a lower-risk comment and took that individual to the office for investigation, the person representing a greater safety threat might actually carry out a violent act. Such a design might increase the learning impact and make it easier for supervisors to remember the consequences of certain decisions, but the design would have to be effected carefully so as not to trivialize an important responsibility and concern.

Example 2

Railroad Safety for

Professional Drivers

E

http://www.alleninteractions.com/oli

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Operation Lifesaver, Inc., is a national, nonprofit safety education group whose goal is to eliminate deaths and injuries at railroad crossings and along railroad rights-of-way. It has programs in all 50 states with trained and certified presenters who provide free safety talks to raise alertness around tracks and trains.

Performance Goal

Operation Lifesaver wanted to address the unique challenges in training drivers of all types of trucks to apply safety procedures around railroad tracks and to help them make sound decisions at railroad crossings. They wanted to maximize learner participation by building an appealing online learning experience because statistics show approximately one out of four railroad-crossing crashes involves vehicles that require a Commercial Driver’s License (CDL) to operate; this includes all sizes of trucks from large over-the-road vehicles to local delivery trucks.

Target Audience

Drivers of all types of trucks with a CDL.

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Training Solution

The solution for Operation Lifesaver consisted of multiple instructional modalities, including a promotional video trailer, the interactive e-learning course, a traffic signs gamelette, and an integrated marketing plan incorporating various tactics across social and traditional media.

The e-learning course focuses on truck driver safety and employs a simulation with a game-like driving environment in which drivers are exposed to worst-case scenarios that require quick thinking and critical decision making. Drivers work independently, so that they can freely make mistakes and witness the (dire) consequences. The game-like characteristics push almost everyone who tries the e-learning to achieve successful excursions, through repetitive tries if necessary (see Figure 12.8). More than 15,000 truck drivers have taken the e-learning course.

Let’s take a look.

Context

On a road, in the cab of several different trucks The student is put into a driver simulation going down a road with signs and hazards related to railroads that must be dealt with as they are encountered. (See Figure 12.9).

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FIGURE 12.8

The setup for OLI’s Railroad Safety for Professional Drivers CCAF and Interactive Instruction

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Challenge

Take the appropriate action for each hazard as it is encountered, following applicable laws, maximizing safety and minimizing risk (see Figure 12.9).

Activity

Given accelerator and braking controls, and the ability to interact with distracters, such as a radio, a cell phone, and so forth, the student must use the proper approach techniques for each hazard (see Figure 12.10).

Every time a truck driver approaches a railroad crossing in the e-learning course, he or she must:

• Slow down and/or stop immediately as directed by the signs and signals

• Eliminate distractions

• Roll down the window and listen

• Look both ways, using what truck drivers calls “rock and roll” to k

look around the large side mirrors

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The user interface makes these actions easy to perform so learner focus remains on making good decisions and performing procedures rather than learning an artificial interface (see Figure 12.11).

Feedback

Because drivers have opportunities to correct some problems and perform some tasks in slightly different sequences, feedback is shown as the consequence of the performance (see Figure 12.12).

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FIGURE 12.9

Animation provides an authentic context by making learners feel as though they are moving down the road.

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FIGURE 12.10

Distractions, such as a helpful bystander, tempt drivers to abandon safety procedures.

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FIGURE 12.11

Running a stop sign and other driving transgressions require, as in many games, the learner/player to start over.

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FIGURE 12.12

As happens far too often on the road, learners in this simulation are reminded of severe consequences possible for poor performance.

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Anatomy of Good Interactions

Let’s now reexamine each component of instructional interactivity.

Context

Context provides the framework and conditions that make the interaction relevant and meaningful to the learner. The media Context

available in e-learning provide an important opportunity to make interactions much more than rhetorical or abstract events. Because we are often working to maximize transfer of learning to performance on the job, the more realistic the context can be, the more likely the learner will be to imagine the proposed situation actually occurring. With a context in mind, the learner is more likely to visualize taking alternative actions as well as the outcomes—a mental exercise that will increase the probability of transferring learning to real behavior.

Some researchers believe humans do much, if not all, of their reasoning through the use of mental images. Images can communicate to us more rapidly and with more fidelity than verbal descriptions, while animations can impart a sense of urgency with unequaled force. Presenting traditional k

academic questions, such as multiple choice, fill-in the blank, true/false, k

and matching questions without illustrations, takes little advantage of the instructional capabilities present in e-learning and are quite the opposite of working within a truly instructional context.

Challenge

Challenge is a stimulus to exhibit effective behavior.

Challenge focuses learners on specific aspects

Context

Challenge

of the instructional context and calls learners to

action.

In its simplest (and often least effective)

form, the challenge is a question the learner

is to answer. In more complex and usually more effective settings, the stimulus may be such things as:

• Indications of a problem on a control panel

• Customer service complaints

• A spreadsheet showing an unreconciled difference

• An animated production line producing poor quality CCAF and Interactive Instruction

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• Increasing business losses

• A simulated customer call (via audio delivery)

• A medical prescription to be filled

• A simulated electrical fault

• A client record to be updated

“Click Next to go on” is not a stimulus for instructional interactivity unless you are trying to teach people how to advance to the next screen.

But “You have 10 minutes before the patient’s heart will give out” can be quite an effective stimulus.

Activity

Activity is the physical gesture and learner response to the context and challenge.

Context

Challenge

Whether learning physical skills (such as

typing) or mental skills (such as sentence con-

struction), learners need ways to communicate

decisions, demonstrate abilities, ask for assis-

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tance, test solutions, and state answers. The

Activity

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gestures learners can use for input to the com-

puter are often physically quite different from

the actions learners are being trained to per-

form, but they should correspond and be natural and easy to use; they should readily and quickly represent the learner’s intentions. The mechanisms with which learners express their questions, decisions, answers, and so on should not impede or bias the learner’s ability to communicate nor be so complex as to defocus learners by asking them to deal with user interface artifacts.

Just making the learner do something, however, doesn’t comprise an instructional interaction. Even if the computer responds specifically to what the learner does, a sequence of input and response doesn’t necessarily constitute an instructional event.

The structure of the input tools (i.e., the recognized learner gestures) is a major design consideration. In many cases, they determine the extent of the cognitive processing the learner must perform. They may determine, for example, whether the learner needs to recognize an appropriate solution, recall it, or apply it. These are all very different cognitive processes.

Poorly constructed interactions require learners to translate what they know or can do into complex, artificial gestures. The task may be 250

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so difficult that fully proficient learners fail to respond “correctly,” not because they are unable to perform the targeted tasks but because they have trouble communicating their knowledge within the imposed constraints of the interface. For example, learners may be able to perform long division on a notepad but be unable to do it via keyboard input.

Very good interfaces are themselves a delight to use; their value to the learning process goes beyond just efficiency and machine-recognized gestures. Not only can they create a more memorable experience, perhaps just by providing a happily recalled event; they also help learners see and understand more fully many kinds of relationships, such as “a part of,” “an example of,” or “a complement to.”

Assembling glassware for a chemistry experiment and sorting fruits, vegetables, dairy products, grains, and meats into appropriate storage containers involve procedures and concepts. Learners might very well remember the process of moving displayed objects as a cognitive handle for recalling underlying relationships and concepts needed in on-the-job performance. Such kinesthetic association can enrich both understanding and recall, whereas having answered multiple-choice questions would give few lasting clues as to the correct on the job actions to take.

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Feedback

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Feedback acknowledges learner activity and pro-

Context

Challenge

vides information about the effectiveness of learner decisions and actions.

When learning, we seek to make

cognitive connections and construct

relationships—a neurological cognitive map,

Feedback

Activity

if you will, that might be represented like

the one in Figure 12.13. The formation of

meaning—creating understanding—is this very

process of drawing relationships. The process

of learning uses rehearsal to strengthen the forming relationships for later recall and application.

Feedback is essential in these processes to make sure learners construct effective relationships and deconstruct erroneous relationships.

The instructional designer’s challenge is therefore to devise feedback that will prove the most helpful to learners in their efforts to identify, to clarify, and to strengthen functional relationships.

It is often easier for learners to link specific actions and consequences than it is to associate two objects with each other, which might seem the CCAF and Interactive Instruction

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FIGURE 12.13

A cognitive map.

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simpler task. For example, it’s quite easy to recall that sticking your finger in a live electrical outlet is likely to result in a shock, even though you may never have done it. But it is harder to recall the capital city of Maine (Augusta) or the name of an enclosed object with seven equal sides (heptagon) unless you have already created a cognitive structure to aid recall, such as from frequent travel to Augusta or doing design work with heptagons. Why? Well, in part because of repeatedly hearing the names and also because it’s likely you would associate those names with actions and consequences. You like to go to Augusta perhaps because you enjoy the views of the Kennebec River and the shops in the Water Street area.

Positive emotional responses arise from experiencing actions that produce pleasant consequences, and they strengthen associations that would otherwise be just learning a name.

It is extremely fortunate for us in training that action-consequence learning is easiest, because the objective of training is to improve performance. Whereas performance is based on factual, conceptual, and procedural knowledge, learning the necessary facts, concepts, and procedures is easier if done in the context of building relationships between actions and their consequences (not the other way around, as is more traditional).

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High-impact feedback allows learners to determine the effectiveness of their actions, not just whether an answer was right or wrong. In fact, good feedback doesn’t necessarily tell learners directly whether their actions are correct or incorrect; rather, it helps learners determine this for themselves.

Good feedback, therefore, is not necessarily judgment or evaluation, as most people think of it (although at times offering such judgment is critical).

Rather, good feedback reflects the different outcomes of specific actions.

Strong and Weak Interactivity

Components

Perhaps the primary challenge of creating effective learning experiences is designing great interactions. The simple presence of the four essential components—context, stimulus, activity, and feedback—doesn’t create effective learning interactions. It is the specific nuances of each component individually and the way that they integrate with and support the effectiveness of the other components that leads to success.

Table 12.1 contrasts the characteristics of strong and weak interaction components.

TABLE 12.1

Characteristics of Good and Poor Interaction

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Components

Component

Strong

Weak

Context

Focuses on applicable

Focuses on learning abstract

action/performance relationships

bodies of knowledge

Reinforces the relationship of

Uses a generalized,

subtasks to target outcomes

content-independent screen

layout

Simulates performance

Simulates a traditional

environments

classroom environment or no

identifiable environment at all

Challenge

Requires learner to apply

Presents traditional questions

information and skills to

(multiple choice, true/false,

meaningful and interesting

matching), which at best require

problems

cognitive processing but not in

an applied setting, and typically

require little cognitive processing

beyond simple recall

Progresses from single-step

Requires (and allows) separate,

performance to requiring

single-step performance only

learners to perform multiple

steps

( continued)

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TABLE 12.1

( Continued)

Component

Strong

Weak

Puts learners at some risk, such

Presents little or no risk by either

as having to start over if they

revealing the correct answer

make too many mistakes

after a mistake is made or using

such structures as, “No. Try

again.”

Activity

Builds on the context to

Uses artificial,

stimulate meaningful

question-answering activities,

performance

such as choosing a, b, c, none

of the above, all of the above

Provides an opportunity to back

Allows only one chance to

up and correct suspected

answer

mistakes or explore alternatives

Asks learners to justify their

Facilitates lucky guesses (and

decisions before feedback is

makes no effort to differentiate

given; learners are allowed to

between lucky guesses and

back up and change responses

well-reasoned decisions)

at any point

Feedback

Provides instructive information

Relies on content presentations

in response to either learner

(given prior to performance

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requests for it or repeated

opportunities)

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learner errors

Helps learner see the negative

Immediately judges every

consequences of poor

response as correct or incorrect

performance and the positive

consequences of good

performance

Delays judgment, giving learners

Focuses learners on earning

information needed to determine

points or passing tests, rather

for themselves whether they are

than on building proficiencies

performing well

Provides frank and honest

Babies learners; always

assessments; says so if and

assumes learners are doing

when learners begin making

their best

thoughtless errors

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The Elusive Essence of Good

Interactivity

It’s clear that not all interactions are of equal value. Nobody wants bad interactions; they’re boring, ineffective, and wasteful of everyone’s time, interest, and energy. Unfortunately, they’re quite easy to build. Good interactions are, of course, just the opposite. They intrigue, involve, challenge, inform, reward, and provide recognizable value to the learner. And they require more planning and instructional design effort.

The essence of good interactivity seems quite elusive. It would be helpful if all the necessary attributes of good interactions could be boiled down to a single guiding principle, or even a single checklist. Even if imperfect, if the essence were easily communicated and widely understood, e-learning would be far better than it is today. For this reason, I have kept searching for that kind of guidance for quite some time. I offer the checklist in Table 12.2 as a basic tool that’s surely better than nothing.

TABLE 12.2

Good Instructional Interactions—A Three-Point

Checklist

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Good interactions

Learners understand what they can accomplish

are purposeful in the

through participation in the interaction. To be of

mind of the learner.

greatest value for an individual, the learner needs to see value in the potential accomplishment and

each learning step.

The learner must

It should not be possible to feign proficiency

apply genuine,

through good guesses. Challenges must be

authentic skills and

appropriately calibrated to the learner’s abilities, knowledge.

readiness, and needs. Activities should become as

similar to needed on-the-job performance as

possible.

Feedback is

The feedback demonstrates to learners the

intrinsic.

ineffectiveness (even risks) of poor responses and

the value of good responses.

Pseudo Interactivity

Misconceptions abound in e-learning. They derive from the many experiences we’ve had as students. And they have been exacerbated by the great enthusiasm for e-learning and fanaticism about all things related CCAF and Interactive Instruction

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to the Internet, with the result that form is often prized over function.

Identified delivery technologies, such as which development tools and learning management systems to use, are often mandated, whereas instructional effectiveness is not defined, required, or even measured. Although there are signs of a backlash effect, there has been a tendency to believe that instruction delivered via technology has credibility just because of the delivery medium. This surely is as wrong as believing that all things in print are true or that because a course of instruction is delivered by a living, breathing instructor, it is better than the alternatives.

Nothing in e-learning has been more confused than the design and application of interactivity. Its nature, is sufficiently multifaceted to be inherently confusing; yet, we’ve been investigating technology-supported instructional interactivity far too long to continue such confusion without embarrassment and impatience.

People confuse instructional interactivity with various multimedia components at both the detail and aggregate levels. At the detail level, very important design nuances separate highly effective interactivity from that which just goes through the motions. At the aggregate level, presentations, navigation, and questioning are wholly mistaken for instructional interactivity. To be clear that these are quite different entities with very different k

applications and outcomes, let’s round out our examination of instruc-k

tional interactivity with some final differentiations—that is, classifications of what is not instructional interactivity.

Presentation versus Instruction

It’s easy to be deceived by appealing design. From book covers to auto-mobile fenders, designers work endlessly to attract our attention, provide appeal, and paint a fantasy. The appeal they strive for is one that will create enthusiasm and a desire to buy, regardless of other factors that should be taken into account. They are often successful in getting us to disregard practicality, quality, and expense and to blindly pursue a desire, to buy into a dream. Just because it’s attractive, of course, doesn’t mean it is a quality product, good for us, or a smart buy.

A beautiful presentation is certainly worth more than an ugly one, but even superb presentation aesthetics don’t convert a presentation into instruction or pronouncements into interactivity. These very different solutions should not be confused, just as the differing needs they address should not be confused.

Sometimes merely the presentation of needed information is sufficient.

Those who are capable of the desired performance with only guiding 256

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TABLE 12.3

Presentations versus Interactivity

Choose Presentations

Choose Interactivity

When …

When …

Content is readily understood by targeted

Content is complex and takes

learners.

considerable thought to comprehend.

Learner differences are minimal.

Learners are diverse in their ability to

understand the content.

Errors are harmless.

Errors are injurious, costly, or difficult to

remedy.

Information is readily available for later

Information needs to be internalized.

retrieval and reference.

Desired change to existing skill is minor

Behavioral changes will require practice.

and can be achieved without practice.

Learners can easily differentiate between

Learners need guidance to differentiate

good and inadequate performance.

between good and poor performance.

Mentorship is inexpensive and will follow.

Mentorship is costly, limited, or

unavailable.

information neither need nor benefit from instruction. They need only k

the information. Because instruction takes time and is much more expen-k

sive to prepare and deliver, it is important not to confuse a need for information with a need for instruction. (See Table 12.3.) Navigation versus Interactivity

Navigation is the means learners have of getting from place to place—of getting to information. It includes such simple things as controls to back up, go forward, replay, pause, quit, and bring up tools such as a glossary, help function, calculator, hints, and progress records.

Because navigation requires input from the learner and provides a response from the computer, people frequently confuse navigation with interactivity. Further, interactive systems need good navigation capabilities. They depend on well-executed, supportive, integrated navigation and suffer when it’s weak. But navigation and instructional interactivity are very different in terms of what they are, the learning support each provides, and where they are appropriate. As before, good navigation doesn’t turn presentations into interactivity, although it can certainly improve the ability of learners to retrieve and review information.

Good navigation systems are valuable. They are neither easy to design nor easy to build. To be highly responsive to user requests and to provide CCAF and Interactive Instruction

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intuitive controls is much more difficult than it would seem and failed attempts repeatedly attest to the level of challenge involved.

Nevertheless, with good navigation, content, and presentation components, performers can be aided such that their performance is hard to differentiate from that of an expert.

Electronic Performance Support

Systems (EPSSs) versus Instructional

Interactivity

Closely related to navigation are applications that provide prompts, guidelines, questions, and information in real time. They depend on very responsive navigation to keep in step with people throughout the performance of their tasks.

Electronic performance support systems (EPSSs) attempt to skip over the expensive, time-consuming efforts of taking people to high levels of proficiency. The EPSS takes advantage of circumstances in which computers can communicate with people as they perform, prompting many tasks in real time without the need of prior or extensive training. There are many benefits, even beyond the obvious benefit of avoided training k

costs:

k

• People can rotate into different positions on demand as workloads change from season to season, day to day, or even hour to hour.

• New hires can become productive very quickly.

• Errors caused by memory lapses, poor habits, and distractions can be greatly reduced, possibly even eliminated.

• Infrequently performed tasks can be performed with the same level of thoroughness and competency as those preformed frequently.

In short, an EPSS is an economical solution when training is not needed. It is an inappropriate and ineffective solution, however, when training is needed. We need to be careful to be clear about both the need and the fitting solution.

The navigational components of an EPSS can look much like instructional interactivity when they are designed to respond to observations made by users. If, for example, in making a payment-collection call to a person leasing a sports car, it is discovered that the payments have ceased because the car has been stolen, the EPSS’s prompts on what to say will 258

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instantly change to address the unexpected context appropriately. The caller might not have learned how to handle such situations and might not have any background in stolen property circumstances, but the caller can still work through an instance successfully. The caller doesn’t know—and doesn’t need to know—what different behaviors might have been appropriate if the leased vehicle had been stolen before the payments fell behind rather than afterward. With the computer’s support present, it doesn’t matter. The employee isn’t really a learner, just a performer successfully carrying out on-screen instructions.

Although the conditional programming necessary to help performers in real time can range from quite simple to extremely complex, even including components of artificial intelligence, the interactions built into these applications serve navigational needs more than instructional ones.

Repetitive performance with EPSS aid should impart some useful internalized knowledge and skills, but EPSS applications are designed to optimize the effectiveness of the supported transactions rather than building new cognitive and performance skills (see Table 12.4).

k

TABLE 12.4

EPSS versus Interactivity

k

Choose EPSS When …

Choose Interactivity When …

The task or job changes often.

The tasks are relatively stable.

Staff turnover is high.

Workers hold same responsibilities for a

long time.

Performers do not need to know why

Performers need to evaluate the

each task step is important and whether it

appropriateness of each step and

is appropriate in a specific circumstance.

vigilantly monitor whether the process as

a whole continues to be appropriate.

Tasks are systematic but complex and

Tasks may require unique, resourceful,

difficult to learn or remember.

and imaginative approaches.

Tasks are performed infrequently.

Tasks are performed frequently.

Tasks allow time for performance support.

Tasks are time critical and prohibit

consulting a performance guide.

Supervision of employees on the job is

Supervision is expensive or impractical.

limited or unavailable.

Mistakes in performance are costly.

Mistakes are easily rectified.

Learners are motivated to seek a solution.

Learners don’t appreciate the value of

good performance.

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Hybrid Applications: Using an EPSS

for Instruction

Some applications both assist new learners to perform well immediately and teach operations so that they can be done either without computer support or more quickly with reduced support. That is, the techniques used for teaching and those that support performance are not mutually exclusive.

In fact, the early work of B. F. Skinner (1968) used a technique of fading. After learners read a poem to be memorized, some words were deleted from the text of the poem. Learners were generally able to continue reciting the poem, filling in the missing words as they read. Successively, more and more words were deleted until the whole poem could be recited with no assistance.

A similar approach can be used with EPSS applications, although considerably more learning support can be provided to learners than simply removing support steps. Instructive feedback, for example, can show learners the potential consequences of an error, while the EPSS application intervenes to prevent that error from actually occurring.

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Questioning versus Interactivity

Question-answering activity is just question-answering activity, regardless of whether it is done with paper and pencil or a computer. If the learner doesn’t have to apply higher-order mental processes, the learning impact is the same, regardless of whether learners drag objects, type letters, or click numbers. Just because some gestures are more sophisticated in terms of user interface, it doesn’t mean that more learning is going on when they’re employed.

The screens in Figures 12.14 to 12.18 show five interaction styles, but the differences among the instructional impact of each style are insignificant.

There’s no doubt that some learning can occur from repeatedly answering questions and checking the answers. A big advantage of e-learning delivery is that it can require learners to commit to answers before checking them. Conversely, learners can easily look at a question at the end of a book chapter, such as one on identifying trees, and think to themselves, “That willow leaf must be from a conifer.” But then, on seeing from listed correct answers that it was actually from a deciduous broadleaf, 260

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FIGURE 12.14

Binary choice via key press.

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FIGURE 12.15

The same binary choice via drag and drop.

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FIGURE 12.16

The same binary choice via text entry.

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FIGURE 12.17

The same binary choice via buttons.

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FIGURE 12.18

Again, the same binary choice via

clickable objects.

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they’ll think “Oh right. I knew that. Should be more careful,” and go on without adequate practice.

Questioning can build some skills—at least the skills needed to answer questions correctly, but it isn’t an efficient means of doing so, and it unfortunately takes minimal advantage of the more effective instructional capabilities available in e-learning.

At the very low end of the interactivity scale, e-learning relies on questioning. If learners casually guess at answers just to reveal correct answers the application readily yields, the learning event is no more effective than the book’s end-of-chapter questions with upside-down answers. This structure does not create memorable events and is most likely to result in test learning, which is quickly forgotten after the examination.

Of course, a continuum of questioning paradigms builds from this low-end base toward true instructional interactivity. Some enhancements on basic questioning include:

• Not providing correct answers

• Not providing correct answers until after several tries CCAF and Interactive Instruction

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• Not providing correct answers right away, but providing hints first

• Not providing correct answers right away, but describing the fault with the learner’s answer, then providing hints if necessary

• Giving credit only if the question is answered correctly on the first try

• Drawing randomly from a pool of questions to be sure learners aren’t just memorizing answers to specific questions

• Selecting questions based on previous faults

And so on. There’s no doubt that these techniques improve the value of questioning for instruction to a degree, but CCAF structures and instructional interactivity are much more effective.

Remember, to hit an instructional home run we need to create meaningful and memorable experiences. Unless the training is specifically designed just to teach learners to pass a test, there are much more efficient and effective methods than drilling through sample questions.

The Takeaways

k

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Instructional interactivity and mechanical interactivity are two very different things. While mechanical interactivity involves input gestures, such as clicking the mouse button or pressing Enter, and a computer response, such as displaying the next page or playing a video, instructional interactivity can be defined as follows:

instructional interactivity Interaction that actively stimulates the learner’s mind to do those things that improve ability and readiness to perform effectively.

Although instructional designs that elicit effective instructional interactivity involve successful integration of a great many factors, all build on just four elements:

• Context— the framework or situation and conditions which make content relevant and interesting to the learner

• Challenge— a stimulus to action within the context, such as a problem to solve

• Activity— a physical response to the challenge that represents a real-world action a person might really take

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• Feedback— reflection of the effectiveness of the learner’s action most often best presented as consequences to the action the learner took When these components are used effectively, instructional interactions are characterized by:

1. Being purposeful in the mind of learner. Learners can see value in what they’re doing.

2. Requiring the learner to perform authentic skills as they would expect to do after training is complete.

3. Intrinsic feedback, often in the form of consequences to actions taken.

Presentations, navigation, EPSS, and more complex user interfaces can appear to suffice for well-designed instructional interactions but are quite different things and insufficient on their own when learners are building most performance skills.

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Chapter 13

Interactivity Paradigms

That Work

Let’s look at a few specific models that have been very successful in multiple applications. They range from easy and very inexpensive to build, to sophisticated work requiring substantial investment. All of them, however, have been very successful (as in getting people to do the right thing at the right time) and have been used with a wide variety of content. Once built, their repeated use has made them very affordable.

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Trapdoor Hints

Sometimes complex tasks have to be overlearned so as to become almost automatic—such that they can be performed accurately with little thought even under stressful or distracting circumstances. Airline ticket agents, for example, often have to work their computers to locate and enter information while people are talking to them, reciting numbers and information not yet part of the transaction or making friendly but nevertheless distracting conversation.

Reservation and ticketing operations can be complex, requiring multiple steps, interpreting codes, responding to restrictions, looking for options, and so forth. Interfaces vary from more prompted and helpful designs to those that originated years ago, when a coded, invariant syntax was used. An acceptable entry, such as the one below for simply retrieving a reservation record, had to be keyed exactly as shown or it was completely rejected:

*122/17SEP-THAYER

* indicates a display operation, 122 is the flight number, 17SEP is the date (September 17), and the passenger is THAYER. Ticket agents needed k

to be able to make these entries quickly and without error.

k

A successful and innovating instructional design called for extensive learner practice using a simulated trapdoor to provide hints when learners asked for them. Hints were hidden beneath a spring-loaded trapdoor simulation. Learners had to request hints by sliding a trapdoor open (see Figure 13.1). To do this, they would click the mouse pointer on the closed door and drag it to the side. As they held the door open, they could read the hint, but the moment they released the mouse button to type their answer, the door slid shut.

The first hint would be the most generic hint—a basic reminder of the appropriate format for the entry. Each time the learner reopened the door, a different hint more specific to the required entry would appear. The final hint revealed the complete correct entry.

Learners quickly realized they should concentrate carefully on each hint, because the moment they released it, it was gone. Further, even though the last and final hint would actually reveal the correct command verbatim, it really took more time and effort to obtain hints over and over again than it did simply to learn the principles of entry syntax. Learners, as with all of us, are often interested in the shortest, easiest path. If it’s easier to learn than to get help, they’ll try harder to succeed without asking for help. Hey!

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FIGURE 13.1

Trapdoor hints.

Context

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Learners were given a simulated view of a crowded ticket counter complete with distracting ambient noise. As learner proficiency grew, travel requests were made through recorded audio so that learners had to listen carefully through distracting racket and manage disruptions.

Challenge

Beginning learners were given a basic overview of command structures and rules. Then, in drills with trapdoor hints, they were given information about a customer and asked to retrieve records related to the customer’s travel and eventually make changes to them.

This is a case in which repetition is important. Many commands can be formed from the syntax, but with few exceptions, if elements are out of order or missing, the command will have to be reentered, costing precious time. Command complexity advanced as learners demonstrated mastery of the basics.

Activity

Learners had to type a syntactically correct command to complete each exercise, just as they would have to do on the job.

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Feedback

Parsing software analyzed each command entered and detected specific faults. It was possible to tell learners exactly what was wrong with each command they entered, both in the general sense of format and in the specific sense of whether they had entered the correct command and data for the exercise at hand.

Two levels of feedback were given to learners:

1. A general statement of the error (or of the first error in their entry) was given.

2. To require learners to think and internalize information, rather than letting learners flounder around guessing or simply parroting back correct commands that had been revealed, hints were written to help learners make corrections. A succession of hints was devised, beginning with general principles and eventually revealing the correct command using information specific to the exercise. But learners had to work through the entire succession to reveal the correct answer, making it easier to think and correct an entry than just to look up the answer.

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Reusability

Trapdoor hints is a model that has been used by our studios repeatedly over decades now. It was useful, for example, in training call center operators and medical records workers to format data acceptable to online forms. The trapdoor hints mechanism is very easy to program and is widely applicable in instances where repetition of moderately varying exercises is appropriate. Although it can be embellished with scoring systems, such that each retrieval of a hint costs some penalty points, the design is amazingly effective even in its simplest form. Perhaps asking for help, even from a machine, is enough of a psychological expense to motivate concentration and learning. Perhaps we unacceptably disappoint ourselves if we need to ask repeatedly for the same help. I’m sure there are explanations and many opportunities for research here. What we can see from simple observation, however, is that this is a simple interactivity design that works and has many applications.

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Task Model

Much training is developed to teach people to follow procedures. As many tasks become more information-based and systems become more complex, the number of procedures to be learned increases dramatically. When there are many procedures to be learned, learners can be overwhelmed if we try to teach all procedures individually and specifically.

Having learners follow along with an instructor’s “Do what I do”

focuses learners on following instructions and gives them a false impression they can do it on their own. Successfully mimicking an instructor or software simulation imparts a feeling of confidence that the procedure has been learned. But once the demonstration is removed, learners often find they can only get a small way into a procedure before hitting a wall.

Further, when people are taught only as many selected procedures as fit into a class of reasonable length, there is often much left untaught and unlearned. We are often better served by learning how to master new tasks on our own. To become sufficient, we need to learn some general skills, become familiar with the logic, practice learning specific skills, do some analysis, and experiment.

k

Learners need to have confidence they can figure out new processes k

with reasonable efficiency. They need to know whether there are risks of making dangerous errors and how to avoid them, especially when they must perform a task never specifically taught to them. They need to know what kinds of errors can be corrected and what kinds can’t.

All in all, this is quite different from the approaches typically used to teach new procedures, such as using a new software application. Yet when people are taught only as many selected procedures as fit into a class of reasonable length, there is often much left untaught and unlearned. A different approach truly is needed. The task model is an effective approach to learning procedures that lets users “learn by doing” rather than by simply watching.

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Example

NYU Medical

Integrated Clinical Information System

http://www.alleninteractions.com/nyu-medical

NYU Medical required employees to complete training on a new software application, the Integrated Clinical Information System (ICIS), which is used to maintain records for patient orders and documentation.

They used this course to assist in the transition from paper documentation to the new software. The heart of this e-learning solution is a simulated environment of the ICIS software application where learners (New York University Medical employees) are presented with real-world patient scenarios and need to complete orders and tasks within the software application. This course contains 11 modules with scenarios customized for five user roles.

Allen Interactions used the task model as an interactive approach in k

k

which users are able to interact with a representation of the system to complete various tasks—tasks in this case associated with customer management and updating contact history. The task model uses screenshots and active hot spots to simulate many functions of the actual system.

Rather than being passive observers of someone else using the software, the task model lets users learn by practicing to mastery. To facilitate the learning, the model breaks each task into a series of logical steps composed of unique gestures (field inputs and clicks). Learners complete each step and are given feedback on their progress.

Context

The simulated NYU Medical ICIS—a system used to maintain records for patient orders and documentation.

Challenge

From the very beginning, learners are asked to perform tasks in the software without having been told how to do so. Eventually, they must accurately complete those tasks without making mistakes or needing help (see Figure 13.2).

Although various forms of help are available, learners are encouraged to see if they can meet the challenge on their own.

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FIGURE 13.2

A task model challenge starts the interaction.

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FIGURE 13.3

Learners are encouraged to see whether they can meet challenges without help, although plenty of help is available.

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Activity

Learners operate the simulated software application exactly as they would the real application, performing the appropriate mouse and keyboard gestures to complete each required step of each provided task.

As in this example application, if there are multiple methods or sequences that can be used to complete a task, then, if possible, all paths should be active in the simulation to avoid artificial constraints. Dead-end paths may also be active, if budget allows; if the cost of simulating all dead-end paths is high, you might simulate just the most common ones.

A variety of learning aids are provided (see Figure 13.4).

• Task Demo: At any time, the learner can watch a demonstration of the entire task they are working on from start to finish.

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FIGURE 13.4

Learners can request the form of help they prefer.

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• Step Demo: The learner can watch a demonstration of a specific step.

• Hints: The learner can review a detailed description of the actions needed to complete an individual step. However, he or she must close this list before going back to the course and actually completing the step.

Notes: As the learner progresses through steps for a task, pop-up notes can provide feedback and highlight the benefits of each option, suggest tips, and reference other resources. It is important, however, that learners actually perform tasks themselves.

Although demonstrations are constantly available, each demonstration resets the simulation at the point of the learner’s last activity. Learners must perform each step themselves in order to be given credit for task completion.

Feedback

New users need feedback to see if and where errors were made. The simulation itself provides intrinsic feedback—the most valuable feedback for k

learning—in the form of consequences. That is, the system simulation k

does exactly what the real system would do in response to the actions taken by the learner. Delayed feedback provides a performance summary and informs the learner whether a retry is required based on mistakes or the number of requested hints and demos.

Progress information is also shown. As the simulation progresses, the step numbers change color to highlight mastery at each step. Mastery occurs only when a correct action is taken without a mistake or a request for a hint or demo.

Reusability

This very successful interactive model has been used to teach a wide range of procedural tasks. It is applicable to almost any process-oriented environment, such as electrical and mechanical systems, in addition to the obvious computer and information systems, in which a number of specific operations will be carried out to perform tasks. The operations taught might include operation of a system, problem diagnosis, maintenance, or repair.

The capabilities of this design not only teach defined operations but also build a general competency with the software application and its Interactivity Paradigms That Work

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conventions. Learners finish with a heightened probability of being able to complete untaught operations, as well. They practice thinking about the logical location of options. They have a sense of what is possible—of what features are likely to be discovered with sufficient effort. They know how to reverse actions, if possible. They have a sense of what may be dangerous and what is probably open for exploration.

The model can be adapted in a number of ways, depending on the level of mastery required and the complexity of procedures being taught.

Adaptation possibilities include:

• Requiring completion of an entire task from beginning to end without viewing a demonstration along the way

• Requiring completion of an entire task without demonstrations or using other aids such as hints or step outlines

• Requiring completion of each step without any errors or help

• Using scoring systems to reward good performance

• Setting speed criteria

Once again, the wide applicability of the general model makes it worth k

the programming effort to create a shell that will later accept whatever k

content is provided, usually in external files or a database.

This approach allows the designer to edit, maintain, and expand the content without additional programming. Happily, each new application can be built rapidly and at low cost.

Enhanced Drill and Practice

The drill-and-practice method was once thought to be appropriate only for rehearsing and strengthening acquired skills. As such, it was thought to be of less value than other forms of instruction designed to teach new skills and considered to be a less-sophisticated approach overall.

Today, however, we see that enhanced drill and practice can be one of the most effective instructional techniques, even for teaching new concepts.

With performance-sensitive algorithms, it becomes quite sophisticated in its ability to adapt to the learner’s skill and readiness levels, adjusting both practice repetitions and new content introduction in the process.

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Corrective Feedback Paradigm

One very effective drill-and-practice approach introduced by Siegel and Misselt (1984), is called the Corrective Feedback Paradigm (CFP). This approach provides an effective pattern to learn and rehearse problem sets.

When the learner fails to complete a problem correctly, it is presented again after one or two other problems are worked. If the learner succeeds, the problem will be presented again a bit later, perhaps after four to six other problems. The technique works to keep learners reworking problem areas until their performance reliability strengthens. Rehearsal is then gradually distributed more broadly over time until problems no longer need practice.

In Figure 13.5, exercises a through f represent a list of items to practice. Items can provide any type of challenge to learners, from simple, single-answer questions to complex tasks. When an item is missed, it is reinserted in the list a few items back. A missed item is usually presented again after just one or two intervening items. After a correct response is given, increasing numbers of intervening items space practice. After an item has been answered correctly several times in a row, it is removed from the list.

This is precisely the review schedule that will best facilitate establishing k

new information in long-term memory. When additional items are missed, k

it is easy to see how complicated the review schedule for items can become.

Complicated, that is, for a human to track. It’s not at all difficult for a computer program to track such information. The power of this technique in achieving lasting results has been demonstrated many times.

f

a

e

2

d

c

+2

a

Correct Answers

6b

(get delayed rehearsal)

2

a

+2

2

+2

6

6

Incorrect Answers

(get early rehearsal)

FIGURE 13.5

Spaced practice using the Corrective

Feedback Paradigm.

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Example

Who Wants to Be

a Miller?

E

National Food Services Management Institute.

A fascinating illustration is found in a project undertaken by the National Food Services Management Institute to teach school food service workers the differences between types of flour. While the final objective was to help cooks understand the appropriateness of different types of flour for various recipes, an intermediate step required learners to know what is in each type of flour.

An invented subtask took the form of a game, Who Wants to Be a Miller?

that demonstrates interactivity and corrective feedback to build engaging interactivity in the style of a serious learning game.

Context

A conveyor belt presents empty flour sacks to be filled with the ingredients k

necessary to match the sack label, such as all-purpose flour, cake flour, and k

bread flour. The milling plant has wheat supply hoppers, supplies of other ingredients necessary to make a variety of flour products, and, of course, a wheat-grinding mill (see Figure 13.6).

Challenge

Learners must fill each bag with exactly the right ingredients for each type of flour and demonstrate the ability to do so reliably. The CFP design integrates multiple instructional functions:

• Sequencing

• Building on guesses and good thinking

• Assessment

• Practice

• Feedback and reinforcement

A short list of only three types of grain begins the challenge. For learners who have little background and may have decided to jump into the activity without any prior study (which is fine), differentiating the ingredients of three different products provides enough of a challenge.

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FIGURE 13.6

Context screen of Who Wants to Be a Miller?

k

If the learner correctly identifies the ingredients for the first sack, k

either by knowledge or by luck, the learner will have to repeat this performance a bit later to confirm the knowledge. However, the learner will be directed to a few different tasks before being challenged to repeat this initial success. If the learner succeeds three times without error, the challenge is retired.

If the learner makes an error, the same type of flour sack will reappear at the left of the conveyor belt, behind any sacks currently there. Learners see that they will have to compose the correct mixture after a delay of filling intermediate sacks, so they are motivated to rehearse mentally the correct ingredients specified in the feedback.

Failed challenges repeat frequently, generally after two intervening exercises, until a correct answer is given. The challenge continues to repeat, but if the learner continues to respond correctly, spac-ing increases—that is, increasing numbers of intervening exercises appear—until the learner has satisfied the mastery criterion, often set at three consecutive perfect performances.

Activity

An intuitive interface allows learners to control the feed from supply hoppers that contain such things as hard winter wheat, soft winter wheat, Interactivity Paradigms That Work

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Closed bin

Open bin

FIGURE 13.7

Learners click to open and close wheat

supply chutes.

salt, and baking powder through very simple interfaces (see Figure 13.7).

Clicking the supply bins once opens them. Clicking again closes them.

Similarly, learners click filters for bran and germ to deactivate or to k

reactivate them and then click the Grind lever (see Figure 13.6) to begin k

the process of grinding the wheat and mixing the ingredients. Note the use of delayed judgment here—the learner can adjust the ingredients any number of times with no penalty when considering the correct choices. It isn’t until the Grind lever is pressed that any judging begins.

As they wish, learners can access information describing the composition of various special-purpose and general-purpose flours (see Figure 13.8). Those learners who want to avoid all risk of making an error may prefer to study first, rather than guess. However, to confirm mastery, learners must eventually complete the exercise on their own, without having reference information displayed.

Feedback

Animation and sounds confirm every gesture, making the interaction pleasant and building anticipation as learners watch to see whether their selected ingredients are correct. When the process is complete, each bag is sealed, and the conveyor belt advances the sacks, bringing the next item to the filling hopper. A correct sack closes and moves along the belt; an improperly filled sack is rejected (see Figure 13.9). (CFP aside, this animation makes for a remarkably entertaining activity.) 280

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Learners can review

the composition of

the types of flour.

k

FIGURE 13.8

Reviewing the types of flour.

k

The cake flour item was correct and is sealed and moving out of the list.

The bread flour was filled incorrectly and has been stamped Rejected.

Moving the cursor over the rejected bags gives information about the correct ingredients. Notice that, since the learner missed bread flour, that same item is coming along on the conveyor belt two items later.

FIGURE 13.9

Learner errors trigger corrective feedback.

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To learn what went wrong, learners can move the cursor over rejected bags to see the proper ingredients. They must do this, of course, before they have filled enough sacks to move the rejected ones out of sight on the conveyor belt.

After filling all bags of all types correctly and repeatedly, the conveyor belt stops. Learners are told what percentage of sacks they filled correctly.

Almost without exception, learners scoring less than 100 percent opt to try all over again, with the full expectation of making no errors. Their expectations are usually met.

Reusability

CFP, based on research by Siegel and Misselt (1984), and its interactivity have been shown to be effective across a wide array of tasks, content areas, and learner populations. CFP keeps interest and involvement high for learners of all ages. Learners who have already developed strong skills merely have those skills confirmed and exit the sequence quickly. Those who are completely new to the content see its breadth unveiled slowly and at varying speeds, commensurate with their growing abilities.

Because of the paradigm’s many positive attributes, it is very much worth programming the central logic in a generalized way so that a variety k

of user interfaces and content can be supported. As always, once this is k

done, this outstanding learning experience becomes very quick and inexpensive to implement.

Not for All Instructional Needs

As energizing and popular as CFP is with learners, it is tempting to use it quite frequently. It would be a mistake to apply it to all learning needs, of course, at least without careful adaptation. Although other situations would warrant caution, CFP is particularly appropriate for:

• Paired-associate learning, such as the names, sizes, colors, purpose, or locations of things

• Learning foreign-language vocabulary (a form of paired-associate learning)

• Concept classification activities

• Short-process practice, such as arithmetic skills When helping my children study for school, I often used the CFP

approach, even without computer involvement. It works for so many 282

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school learning tasks. When my kids got a question right, I’d ask it again later for verification and then retire it if they answered correctly. If they got it wrong, I’d ask it again one or two items later, then four or five items later, and then once more for verification before retiring it. If a question were missed anywhere along the line, we’d start its cycle all over again, beginning after the next question or two.

CFP is extremely effective and fun. Learners quickly understand the paradigm even without explanation and know that if they miss an item, it’s going to come back again after one or two other exercises. Sometimes my kids would recite both the problem and the answer, knowing exactly what I was about to ask them. Knowing how the paradigm works doesn’t inhibit its effectiveness at all; it probably enhances it. Learners seem to delight in anticipating the repetition.

You may be wondering how to determine the appropriate parameters.

Luckily, experience has proved that the paradigm is extremely resilient across minor differences in the review schedule. The retirement criterion (how many consecutive corrects indicate mastery) is responsible for the degree of overlearning that takes place. A 3-6-10 review schedule for correct items will have similar results to a 2-4-10 or similar schedule. As long as the increasing ratio of the review pattern is maintained, learning k

gains will be significant.

k

Problem-Solving Investigation

Everyone loves a mystery. Storytelling is a wonderful way to establish a context for communication and learning, and mystery stories hold special interest. As luck would have it, mysteries provide just the right context for learning.

We’ve previously discussed the value of challenging learners before we start telling them all we want them to know. We put the challenge first because, among other things, there’s a good chance learners will ask for the very information we wanted to tell them. When learners ask for help in the face of a challenge they can’t meet, there’s a specific and meaningful context for the information. They attend to and value the help being provided in a very concrete way.

Mysteries, a.k.a., problem-solving exercises, provide a natural context for putting the challenge up front. In this context, learners don’t feel ill at ease, as they might from being tested. Rather, learners realize it’s part of the game, and they get into it easily. They know they’ll have to be on their Interactivity Paradigms That Work

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toes to figure things out—not a bad thing. And they even expect delayed judgment! Can’t beat that.

Example

Substance Abuse

(https://sales.alleni.com/MISC/CorningSE/training1.html)

Username: tourbypass Password: 123456

When I was looking for an example of a problem-solving investigation in an e-learning course, I had a broad collection of courses to choose from, including several done as part of a terrific supervisor effectiveness training program.

In this interaction, students are asked to identify the culprit based on evidence of substance abuse. To identify the individual of concern, the supervisor must research observed behavior patterns for each potential k

offender and then choose a suspect without offending innocent individuals, k

invading privacy, or violating the company’s policies.

Once a suspect has been chosen, the student must follow a prescribed process for first confirming the suspicion with another supervisor (company policy) and then determine the appropriate course of action based on the observations collected. This method allows for a much deeper level of learning through analysis, processing, decision making, and justification for each action.

It’s done as a simulated investigation, because solving problems in real life isn’t just answering some test questions correctly. It’s asking around, searching for information, and putting two and two together. It is likely the problem you are facing isn’t exactly like one in any textbook. It will be an adventure rather than a class.

Context

As a team manager with six direct reports, you are responsible for the safety and well-being of your team in the workplace. Evidence suggests you may have an individual with a substance abuse problem.

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Challenge

Follow proper procedures to determine who you think was drinking on the job.

Activity

This is a multistep activity requiring learners first to review daily notes on each individual (see Figure 13.10) and then identify the person most likely having a substance abuse problem.

Once the individual has been identified, learners have a variety of investigative and referral steps they can take. The learner selects the steps to take and drags them in order to the right panel see Figure 13.11).

Feedback

As we prefer to do, the application presents consequences and uses feedback guidance to present much of the instructional content. This allows learners to dive right in and show what they already know.

Many learners will instinctively feel they should immediately engage with the person they suspect. In Corning’s policies and procedures, it’s pointed out that this can have problematic consequences.

(See Figure 13.12.)

k

k

Reusability

This investigation model provides an excellent design for any situation in which the learner must analyze a problem by observation and research and then identify a solution. This design can be generalized to other situations quite directly, but the actual implementation may require some effort, simply because the data representations and learner gestures should match the context and desired learning outcomes.

Facing learners with a problem of specific meaning and personal concern rarely fails to enhance learner motivation and the value of the e-learning experience. Success in these interactions usually does two things for the learner: (1) it encourages exploration and a deeper understanding of the resources that lead to a solution, and (2) it instills enthusiasm to solve more problems—both in the e-learning context and in the real work environment.

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FIGURE 13.10

Problem-solving investigation in which learners first check k

behavioral notes on team members and identify a suspect.

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FIGURE 13.11

Learner is asked to select and order actions to take.

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FIGURE 13.12

Feedback reveals important

information in context.

Discovery

k

k

Discovery learning, controversial as it may be, is one of the most interesting and motivating of all learning models, and effective when done right. Ideally, the learner experiences a problem or phenomenon, then, through self-directed study and investigation, identifies and assimilates the underlying facts, rules, and concepts that describe the problem or phenomenon. Discovery may require the mastery of many facts and concepts and motivates learners to develop higher-level thinking skills and understand relationships.

Much has been said for and against discovery in the context of e-learning (Bruyckere et al., 2015, pp. 48–53). When it works, discovery works very well. Learners who take responsibility for their own learning are generally motivated to discover everything they can about a problem, usually doing research that goes far beyond the specific needs of the moment. However, it can be slow and unreliable. Some learners may never realize the importance of experimenting with some key factor, for example.

In the training context, discovery models usually veer toward a guided discovery approach (Mayer, 2004). This combines the richness of a discovery environment and its attendant outcomes with the deliberate nature Interactivity Paradigms That Work

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of more traditional task-based training. Goals are made clear, which helps direct learners in fruitful directions and time is used efficiently, but learners are still given considerable flexibility in manipulating and exploring the environment. The intent is to develop a thorough, high-level understanding through learner-directed exploration.

Example

POST LERT—Recognizing

and Reporting

https://sales.alleni.com/client/POST/

In this course, students respond to reported suspicious activity. They must then “research” the situation and determine whether the facts justify an escalation to Homeland Security. Exciting, huh? It really is.

In this context, there are many subjective decisions folded into making judgments, so the student is encouraged to notate all items of interest before making an escalation decision. Once a decision has been made, the k

k

student must justify that decision by selecting key observations that lead to the decision. By supporting free investigation, the student can collect and select noted items of any combination until the case is made. Then they can choose the proper escalation and support for that decision.

Context

Upon a call regarding potential terrorist activity, learners take the role of a responding officer to select and go to various locations to investigate.

(See Figure 13.13.)

Challenge

Collect information to determine whether to escalate the situation to Homeland Security, and then defend your decision. (See Figure 13.14.) Activity

By selecting from presented choices, determine what actions to take during an investigation; take notes regarding people, places, things, and actions that could be relevant; choose notable results of that investigation; and then determine whether to escalate the situation to Homeland Security. (See Figures 13.15 and 13.16.)

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k

k

FIGURE 13.13

One of the situations learners assess

while playing the role of an antiterrorism officer.

Feedback

Feedback is delayed until the learner makes his or her case. Detailed appraisal is then given on the decision to escalate or not as well as on each of the recorded items the learner feels justifies the decision. (See Figure 13.17.)

Reusability

The effectiveness of discovery learning depends on the specificity of the behavioral objectives and the ability of the e-learning to represent all parameters related to the target content effectively. If the desired behavior is a sophisticated but general understanding of an environment in which learners must deal with unpredictable problems and challenges, discovery learning is unsurpassed, provided the parameters of the e-learning are reasonably true to the target environment. Unfortunately, in some cases when an attempt is made to design a discovery-based e-learning module, Interactivity Paradigms That Work

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FIGURE 13.14

At a location of interest to the learner, there are many actions to k

chose from and a notepad to collect information on which to base later decisions.

k

FIGURE 13.15

Student must select prudent questions to ask.

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FIGURE 13.16

Identifying evidence.

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FIGURE 13.17

Final delayed feedback.

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technical, budget, or other constraints compromise the value of the invented learning situation by making it too shallow. Extended discovery learning in an inauthentic environment can actually be far worse than a simple, more traditional approach. If the behavioral objectives for an e-learning project call for specific mastery of a body of knowledge or skills, discovery will probably not be terribly successful. It can often be a slower (but richer) process and unless exploration is carefully guided, it is difficult to guarantee that any specific content-based objective will be met.

Storytelling

Another effective strategy for teaching a wide range of content is through the use of stories or scenarios. Stories provide an organizing structure that makes the subject matter more relevant to learners and can maintain learners’ interest. Perhaps most important, stories lend personal perspectives that can be lost when dealing with abstract facts and rules.

This approach has two major strengths:

• The subject matter is embedded in a realistic context that learners k

find authentic and credible, making it easier for them to see the k

relevance of the instructional content and how they might use it on the job. This promotes transfer of learning.

• Learners remember the facts and concepts they have learned in terms of the stories and characters they encounter during the learning activities. They don’t have to re-create abstract constructs; they can simply recall what specific people did in specific situations.

This promotes retention of the new knowledge and skills.

A moving and engaging example of scenario-driven instruction can be found in an e-learning project done for the Washington State Coalition Against Domestic Violence.

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Example

In Their Virtual Shoes

Washington State Coalition Against Domestic Violence

https://www.zebrazapps.com/embed/#/985f8f93a6c6422a

971643a2713537a6

In Their Virtual Shoes is a simulation activity that helps participants empathize with the ups and downs a victim of domestic violence experiences. The scenarios are based on true stories—the experiences of individuals with abusive partners as told by themselves. The stories typify the complex and dynamic nature of domestic violence, while also calling out the more specific barriers that victims face.

Goals:

• To increase awareness of the struggles that victims of domestic violence face

• To illustrate that domestic violence is a community problem and not k

just a personal responsibility

k

• To show that we all have a role to embrace in order to end domestic violence

• To encourage everyone to think creatively and act intentionally to assist victims

Students choose a story by selecting a person from a photo roster. They then read the scenario and make decisions about what to do next based on the choices listed. Depending on their choices, their story will have an ending appropriate to their choices.

The simulated experience is fully interactive and students are able to go through multiple scenarios that include case files to be read. Each scenario allows students to make decisions, interview people, and so forth.

Context

From a photographic roster (see Figure 13.18), learners can select an individual’s story to walk through. Although models are used for the photos and names have been changed, the heart-wrenching stories are based on real events.

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FIGURE 13.18

Photographic roster.

Challenge

This is a unique and powerful application. As each story unfolds, the victim’s choices are presented. The challenge is to face decisions that each victim had to make and make your own choice. The choices are difficult k

and involve consequential trade-offs.

k

Activity

As you read each story segment, choices such as those in Figure 13.19

appear.

Feedback

As shown in Figure 13.20, this creative piece asks students to reflect on their experience, feelings, and thoughts. Students respond to questions presented at the end of each scenario and then, by clicking a button, e-mail their responses to their instructor. Feedback comes through personal communications.

Reusability

Story structures can be very useful in providing meaningful contexts. They can add affection, humor, suspense, or other emotions to a topic that may otherwise seem distant from the learner. The more fully the learner is involved in an instructional episode, the more meaningful and memorable it will be. Continuing storylines, when done well, carry meaning and bring an established and automatic interest and motivation to each new topic.

Unfortunately, this storytelling technique is really difficult to achieve; it takes a lot of creative development work. Learners see through inauthentic 294

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k

k

FIGURE 13.19

Unfolding stories present options.

FIGURE 13.20

Personal feedback is provided to learners after

they draw personal conclusions and click to e-mail them to their instructor.

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stories quickly, so depth and detail are important. If at every turn of a story, learners realize there is really only one correct choice, the experience can feel like a sham. Such stories may seem contrived, which is more of an irritation than an aid to learning. But when storytelling is done well, the continuity and personal meaning that it can add to enhance content are exceptionally effective. Learners are motivated throughout the experience—an experience that is likely to be remembered well.

The Takeaways

The extraordinary power of interactivity is to get people thinking through doing and doing well by thinking. That power is not realized without careful and purposeful design. Instructional interactivity does not happen every time a learner clicks a button and the screen changes. Instructional interactivity provides a meaningful context, a challenge that requires thinking, activities that give evidence of the learner’s abilities, and feedback that reveals the effectiveness of the learner’s actions. All of these components must be integrated in a way that provides a beneficial experience for learners, enabling them to do valuable things they were not able to do before.

k

k

Otherwise, whatever we have, it is not instructional interactivity.

Good instructional interactivity is not only affordable but also considerably less expensive than interactivity that doesn’t work. While presentations, information navigators, and questioning applications may be easier to design and less expensive to build, they serve different purposes and are poor substitutes for effective interactivity when performance improvement is really needed.

Good instructional interactions have three essential characteristics: 1. They are purposeful in the mind of the learner.

2. The learner must apply genuine skills and knowledge.

3. Feedback is intrinsic.

A number of strong instructional paradigms have broad applicability, such as the trapdoor hint, task model, Corrective Feedback Paradigm, problem-solving investigation, and discovery designs presented in this chapter. If developed with externalized content and appropriate user interface independence, these sophisticated models can be reused and deployed very quickly and at reasonable cost.

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Chapter 14

Successive

Approximation

and SAM

“With adequate funding, we will have the cure for cancer six months from Thursday.”

k

k

“In my administration, taxes will drop 50 percent while lifelong full-coverage health benefits will be extended to all citizens.”

“We will deliver a strongly motivating, high-impact e-learning application as soon as you need it within whatever budget you happen to have set aside.”

Some challenges are truly tough challenges. Although it might get a program launched, setting expectations unrealistically high doesn’t help solve the real challenges at hand.

Designing effective e-learning applications is one of those truly tough challenges if you don’t have the benefit of an effective process. This chapter describes what I consider to be the most effective of the design processes. Among its strengths is its systematic involvement of all stakeholders to assure their values and expectations can be an ally for your success rather than a stumbling block. It also allows you to take small iterative steps to deal most effectively with considerations of quality, budget, and schedule.

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A Multifaceted Challenge

Developing learning experiences that change behavior is a tough, multifaceted challenge, no matter how few constraints are in place and how generous the funding. Just as in designing modern buildings, setting up a new business operation, or manufacturing an aircraft, in e-learning design there are multifarious complexities requiring a tremendous breadth of knowledge and skill. It’s easy for newcomers to be unaware of this until they see their dreams dashed with projects that struggle for completion and fail to achieve the needed results.

Constraints

As if the inherent challenges of good training weren’t enough, constraints always exist. Typical constraints include one or more of the following:

• Too little budget for the magnitude of behavioral changes needed

• Conflicting opinions of what outcome behaviors are important

• Unrealistically high expectations of solving deeply rooted organizational problems only through training

k

k

• Incorrect preconceptions about what constitutes good instruction or good interactivity

• Short deadlines; too much content

• Inadequate content resources and sporadic availability of subject-matter experts

• Unavailability of typical learners when needed

• Beliefs about applicability of specific media

• Undocumented variances in delivery platforms

• Restrictions on distribution or installation of workstation software Further, regardless of how forward thinking and flexible an organization may be, typical challenges are always exacerbated by additional constraints loaded on in the middle of the project. Who expects to find that the critical subject-matter expert has been reassigned midstream and responsibilities given to a person with very different views? Who expects the procedures being taught to be changed just as simulation software is receiving its final touches? Who expects information systems policies to change, no longer allowing access to essential databases for training purposes?

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No one succeeds in e-learning design and development who hates a challenge or who can’t be flexible in the face of those challenges. Complexity abounds from the primary task of structuring effective learning tasks and from the constantly changing tool sets and technologies. Challenges emanate from within the content, the learners, the client, the learning environment and culture, the technology, and so on. Each project is unique, and if one fully engages the challenge, construction of an effective solution can be neither simple nor routine.

Dealing with Design Challenges

Is there a viable solution to e-learning development? The question is really how to approach the inevitable challenges in a manner that ensures success, or at least promises an acceptable probability of it, and allows you to hold on to your sanity. What can we turn to for reliable and cost-effective production of timely, first-rate e-learning applications? Many approaches have been tried.

What Should Have Worked, but Didn’t (Very Well): ISD

Instructional systems design (ISD) is sometimes referred to as the ADDIE

k

method for its five phases of analysis, design, development, implemen-k

tation, and evaluation. Actually having its roots in engineering design approaches, some may recognize the similarity of ISD to the information system development life cycle.

ISD is classified as a waterfall methodology, so called because in its initial conception there was no backing up through its five sequential phases or steps (see Figure 14.1). Each phase elaborates on the output of the previous phase, without any expectation or plan of going back upstream to reconsider decisions.

Analysis

Design

Development

Implementation

Evaluation

FIGURE 14.1

The ADDIE method.

Successive Approximation and SAM

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Checks were made within each phase to be sure it had been completed thoroughly and accurately. If errors were found, work could not move on to the next phase, because that next phase would be based on faulty information, which would amplify errors and waste precious resources.

In many ways, this approach seems quite rational. It has been articulated to great depth by many organizations. But the results have been far from satisfactory in many instances. A few of the frequent problems we experienced in my application of ADDIE over a couple of decades in the development of thousands of hours of instructional software, included:

• Considerable rework and overruns because subject-matter experts couldn’t see the instructional application in any meaningful way until after implementation (i.e., programming) had been completed.

Then, errors and omissions were found that had to be corrected, with additional costs and schedule delays.

• Contention among team members because each would be visualizing something different as the process moved along, only to discover these discrepancies when it was too late to make any changes without blame and additional time and budget.

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• Boring applications caused by a variety of factors. One was that we k

couldn’t explore alternative designs, because that required execution of all five ADDIE steps to some degree without finalization of any.

Another was that we focused on content and documentation rather than on learners and their experiences. Also, we lacked helpful learner involvement (because learners had no prototypes to evaluate and couldn’t react meaningfully to a sea of highly structured documentation that made no sense to them).

A Fatally Flawed Process

By attempting to be fully complete and totally accurate in the output of each phase, the ISD or ADDIE waterfall method assumes that perfection, or near perfection, is possible. It requires a high degree of perfection as a safeguard against building on false premises promoted in previous phases.

Over the years, attempts to refine the process have tried to tighten it up through clearer definitions, more detailed documentation, more sign-offs, and the like. They have tried to make sure analyses were deep and accurate, content was clarified in full, and screen designs were sketched out in detail almost to the pixel: no errors of omission, no vagary—and yet, not a lot of success.

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Efforts to complete each phase with precise, unequivocal analyses, specifications, or programming, in our case and perhaps typically in similar projects elsewhere, increased the administrative burden, increased the focus on documentation, and, even worse, decreased the likelihood of creative, engaging learning activities. Costs increased and throughput decreased. Applying the process became the job, mediocre learning experiences the output.

Iterations Make All the Difference

Fortunately, there is a viable alternative to ISD. Imagine a process that:

• Helps teams work together more effectively and enthusiastically

• Is more natural and involves more players in meaningful participation from beginning to end

• Focuses on learning experiences rather than on documentation

• Produces better products

• Is based on iterations rather than phenomenal performance

• Can be a lot of fun

k

It’s called successive approximation. Successive approximation is a term k

I borrowed from psychology. In operant conditioning, it means that the gap between the current behavior and the desired behavior gets smaller as you give rewards for behaviors that are getting closer to the desired behavior. Its primary power in the world of learning comes from making incremental improvements in small steps rather than taking perfectly executed giant steps, which very few can do successfully.

Successive approximation actually

incorporates most ISD notions and all

Eva

ADDIE activities, but they are applied

luat

repetitively at the micro level rather than

io

reation

n

linearly at the macro level. It not only

C

allows, but prescribes, backing up. That

is, successive approximation prescribes

taking small steps and reiterating evalu-

ation, design, and development work as

insight and vision become clearer (see

Design

Figure 14.2). Instead of hoping to reach

FIGURE 14.2

The Successive

such perfection in each area of work so

Approximation Model.

as to prevent needed changes, the process

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looks for desirable changes to improve the overall design and product as it evolves from its beginning.

Some ISD or ADDIE defenders suggest that these differences are minor and even that ADDIE can be iterative as well. But I feel that successive approximation is nearly an antithesis of ADDIE’s fundamental content-centric legacy values, and that the results we’ve seen from ADDIE

indicate a need for a fresh new approach. I believe successive approximation is that new approach. Let’s take a look at it in closer detail.

Successive Approximation

There is an approach, a set of values, a way of thinking that is truly the essence and strength of successive approximation. Three primary tenets are enough to set you on your way. Once you get into it, all the critical nuances become natural and self-evident, rather than things to be memorized and applied dogmatically. The fundamental thoughts are as follows:

• No e-learning application is perfect (ever).

k

• Functional prototypes are better than storyboards and design specs k

(much better).

• Disposable, quick and dirty prototypes are beautiful (and we’re happy to try again, three times, then we move on).

No E-Learning Application Is Perfect

First and foremost is the recognition that no software application—or any product, for that matter—is perfect or ever will be. All applications can be improved, and as we make each attempt to improve them, we work to move successively closer to, or approximate, the theoretical ideal. We must be content to know that perfection is not achievable. Thankfully, it’s not a prerequisite to success. We will never get to perfection, but this process will ensure that each step we take will get us significantly closer.

Quite pragmatically, with successive approximation we are looking for the most cost-effective means we can find to enable learners to do what we want them to do. We want to spend neither more nor less than is necessary to achieve our goal. Both overspending and underspending are expensive mistakes. Without conducting some research and gathering critical information beforehand, there’s no way of knowing what is the right amount to spend on a project, although everyone wishes there were. So it’s 302

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FIGURE 14.3

Storyboards typically include screen layout sketches and detailed written descriptions of how interactions should work.

important that the process be sensitive to costs and diligent in determining the appropriate investment at the earliest possible moment.

Functional Prototypes Are Better than

Storyboards and Design Specs

Next is the observation that storyboards and design specifications are unacceptably weak in comparison to functional prototypes. A storyboard is a mock-up of the series of screens a learner will see in the completed e-learning piece, including feedback for each choice shown on the screen (see Figure 14.3).

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These detailed screen images are presented in the order in which the learner is likely to encounter them, in the hope of avoiding errors and omissions in the finished e-learning application. Similarly, design specifications (or specs for short) include written descriptions and rough drawings of the interface, navigation, instructional objectives, content text, and so on. Again, the hope is that subject-matter experts and others on the design team will be able to fully grasp the nature of the envisioned interactions and successfully appraise the impact the interactions will have on learners. Also, that the same beleaguered reviewers somehow will be able to spot errors and omissions in the design specs and thus prevent those errors from becoming part of the final e-learning application.

True Stories—Leaving ADDIE

A large publisher of law books formed a multimedia department to provide, among other things, training for its printing press operators. At first, a very linear design process was used. An instructional designer would follow ADDIE to the tee and hand over fully scripted storyboards and design documents to the production people (media people and programmers).

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As experience would predict, the applications had to be redesigned, because once the developers received the design documents and started producing the application, nobody liked what they saw. Everyone realized that very few people would get anything out of the training.

The organization learned from experience and changed its design process. Rather than creating design documents in a vacuum, the whole team (including end users) met for the project kickoff. Prototypes were built before filling in all the content. Once the appropriate design was determined, iterative development cycles took place.

The outcome? The production time was reduced by one-third to one-half, depending on the project. When people are aware that successive approximations are an option, experience pushes persuasively to this iterative model.

Storyboards and Design Specs

Storyboards have been valued tools to help clients, subject-matter experts, instructors, managers, programmers, and others understand and approve proposed designs. The logic is clear enough: Look at the sketches of screen designs, read the annotations of what is to happen, look at the k

interactions proposed and the contingent feedback messages students are k

to receive, and determine whether the event is likely to achieve the defined learning outcomes.

Storyboards are far better than nothing and much better than design specs that attempt to describe interactions verbally. Unfortunately, no matter how detailed storyboards may be, many of us have found that they fall short in their ability to convey designs adequately to all the concerned individuals. They are inferior as props for testing design effectiveness with learners. The sad truth is that storyboards almost invariably lead to problematic surprises when their contents have been programmed and their prescribed interactivity can then be experienced and tested.

I know that significant numbers of my much-appreciated readers are very attached, both intellectually and emotionally, to storyboards. They find storyboards so valuable they wouldn’t know any way of proceeding without them. Some, if not many, will feel that their storyboards have been the keys to many successes. Just between you and me, I’m actually thinking these successes probably weren’t all they might easily have been.

How much more might have been achieved had a more effective process been used? What opportunities were lost by not being able to witness interactive details of a learning experience before it was finalized?

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True instructional interactivity cannot be storyboarded well or communicated effectively through design specs. Yes, this may seem a radical, even rash, assertion. But consider the nature of a storyboard and the nature of instructional interactivity and try to reach any other conclusion. Storyboards, by their nature, are static documents. Just displaying a static document changes the nature of an active event. What looks good on paper rarely looks as expected on the screen. How you expect things to act and transition from looking at a static document is often not how they behave when programmed. Even with sketches and detailed descriptions, the original vision will mutate in the most unexpected ways when handled by a series of people and adding media treatments.

Prototypes

Functional prototypes have an enormous advantage over storyboards.

With functional prototypes, everyone can get a sense of the interactive nature of the application and its timing, as well as the conditional nature of feedback and its dependency on learner input. With functional prototypes, everyone’s attention turns to the most critical aspect of the design, which is the interactivity, as opposed simply to reviewing content presentations and talking about whether all content points are in evidence on the screen.

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Design specs aren’t even in the running. Unlike using storyboards or k

design specs, users of prototypes may enter into the learning experience, decide on responses to make, and then actually make them in order to see how the software will respond.

Are prototypes practical? Does development of prototypes take too long? For a skilled prototype developer, a useful prototype can usually be turned out in about two hours or less. Actually, it’s not uncommon with the powerful tools we have today to create useful prototypes in only 20 minutes.

Teams can produce excellent products if members have effective ways to communicate with one another. They need to be seeing and experiencing the same design rather than imagining different designs and assuming a common vision that really doesn’t exist. Teams need a way to share a common vision, lest they all start on individual journeys leading to very different places. Without help from each other and a common destination point, no one arrives anywhere desirable.

Ability to Evaluate

Think of the difference between watching Who Wants to Be a Millionaire and actually being in the hot seat. With nothing at risk, we casually judge the challenge to be much easier than it actually is. Imagine if, in storyboard Successive Approximation and SAM

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fashion, Millionaire’s correct answers were immediately posted for us on the screen as each question appeared, just as we’d see in storyboards. We’d easily think, “Oh, I know that. What an easy question!” But we wouldn’t really be facing the dreaded question: “Is that your final answer?” In the hot seat, we might actually have quite a struggle determining the answer.

Obviously, many contestants do. Quite possibly, our learners would have much more trouble than we would anticipate from prototypes—you just can’t tell very easily without the real tests that prototypes allow.

Comprehension of displayed text is inferior to comprehension of printed text. We also know that many designs that are approved in a storyboard presentation are soundly and immediately rejected when they are first viewed on the screen, and they are even more likely to be rejected when they become interactive. Prototypes simply provide an invaluable means of evaluating designs. Otherwise, with the storyboards approved and the programming completed, changes are disruptive at best. More likely, they cause budget overruns and a contentious work environment.

Quick and Dirty Is Beautiful

Finally, quick iterations allow exploration of multiple design ideas. Succes-k

sive approximation advocates believe attempts to perfect a design before k

any software is built are futile and wasteful. Alternative designs need to be developed with just enough functionality, content, and media development for everyone to understand and evaluate the proposed approaches.

I hasten to point out that there are problems with this approach if people don’t understand what’s going on. Some people lose confidence when asked to look at screens with primitive stick figures, unlabeled buttons, no media, incomplete text, and nonfunctioning buttons. Although these are the characteristics of valuable rapidly produced prototypes, some may be unable to see through the roughness to the instructional mechanics being portrayed. They can’t detach graphic polish, wording of text, and other attributes, important as they are, from the transactional issues being sorted out first.

To help, it is often worthwhile to produce a few polished screens to show what can be expected later in the process. Showing a prototype and then a finished product from another project can help relieve concerns that the end product might not have all the characteristics of professionally produced work. Also, communicating your production standards for the project in advance will help curb the tendency to nitpick designs that are ready only for high-level evaluation.

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Brainstorming

The first version of a new application will typically be furthest from perfection, the furthest from what we really want, no matter how much effort is applied. To optimize chances of identifying the best plan possible, alternative approaches need to be explored. In this brainstorming mode, divergent ideas aren’t judged before they’ve been developed a bit.

Brainstorming sounds like fun and can be. But the process isn’t always obvious to everyone, and it can be difficult to keep on track. Check Table 14.1 for some approaches my teams have found effective.

TABLE 14.1

Brainstorming Techniques

Using word

Take the whole problem and reduce it to two sentences. Then one reduction

sentence. Then five words. Then one word. The idea is truly to get at the conceptual heart of the process. As people go around the room and share their one word, you may find that everyone focuses on a different word! This ridiculous exercise reveals the direction for interactivity and can unearth potential conflicts.

Acting it out

Role-play the situation: the problem, how it’s working now, how it’s not working.

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Playing the

What’s the opposite of what’s desired? For example, the opposite of k

opposite game

what’s needed is to slam the phone down on a customer after screaming, “Don’t call back!” This backhanded example reveals a goal: End conversations with the customer eager to call back. This approach can be a very goofy, funny brainstorming approach, but don’t try this one first—there has to be some group trust before you start handling the client’s content with humor.

Oversimplifying

Have the subject-matter experts explain the problem as they might to a class of eight-year-old kids. This forces them to use easy words, explain jargon, and reduce the problem to its most basic elements.

It eliminates unnecessary complications.

Drawing it

Draw the problem statement instead of using words.

Finding analogies

“Our problem is like the problem furniture salespeople have when a customer doesn’t want to buy a bed that day.” “Our problem is like when you go to the dentist and you haven’t flossed and you feel guilty.” Find creative ways of expressing the problem other than directly—this will suggest paths for interactivity and reduce the problem to basic elements.

Setting a

Pretend that your users only have 10 minutes to experience all of the 10-minute limit

training. What would you expose them to? What would you have them learn? This activity can help users prioritize what’s important in the interactivity or the problem analysis.

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Alternatives at No Extra Cost

The total cost of a set of smaller creative design efforts (that is, prototypes) is easily affordable, because you don’t spend much on any given one. A quick review of alternatives incurs far less risk than single-pass or phased approaches that bet everything on one proposal. Further, with the iterative approach, course correction is performed as an expected part of the process and early enough to prevent full development of ultimately unacceptable (and therefore extremely costly) designs.

With a prototyping approach, expenses are kept to a minimum while the search for the best solution is being conducted. Each prototyping effort requires minimal analysis, leading to minimal design work, which leads to minimal development (prototyping) for evaluation. Note that this is just the opposite of legacy models, which work for perfection at each point and intend to perform each process only once. Instead, following a small amount of effort, ideas are available for evaluation by everyone—including students, who can verify what makes sense and what doesn’t, what is interesting and what isn’t, what’s funny and what isn’t, what’s meaningful and what’s confusing, and so on. No more money needs to be spent on anything that seems unlikely to work if there are more promising alternatives to explore.

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Unsuccessful Designs Provide Insight

Early evaluation is input that either confirms or refutes the correctness of the analysis or design. In either case, additional analysis will lead to new design ideas that can, in turn, be prototyped and evaluated. Again, it’s critical that early prototyping be regarded as disposable. In fact, it’s healthy for organizations to work with the expectation of discarding early prototypes and even a commitment to do so. There’s no pressure for this early work to be done with foresight for maintenance, standards compliance, or anything else that would detract from the challenge of identifying the most effective learning event as easily as possible.

Again, prototyping requires the availability of flexible tools and the skills to use them, because it is often valuable to perform prototype development live—even at times in front of the brainstorming team. Choose a tool that allows you to build your prototypes very quickly, concentrate on the learner experience instead of implementation details, and make modifications almost as quickly as ideas arise. Each correction will be a step forward.

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It’s Catching On

Successive approximation requires neither the intellect of Albert Einstein nor the imagination of Walt Disney. Yet, by putting teams in the best possible position to be inventive—to see and explore opportunities while they still have resources to pursue them—successive approximation can reliably produce outstanding, creative learning experiences that are meaningful and memorable. It’s really heartening to see how, after a couple of decades of using and sharing this model, it’s catching on internationally.

The successive approximation approach is a radical departure from the development processes entrenched in many organizations. Some folks are quite wedded to legacy models. I don’t think this is necessarily unfortunate in itself. Indeed, people should use what works best for them. What I’m disheartened to hear from some is that they believe those other approaches are the right approaches. Others are misguided or not professional.

What’s right is what works best. If you’ve only learned or used one approach, how can you be sure what you’re doing is best? Successive approximation may not be right for you, but with all the success so many are having with it, how can you be sure it might not be right for you if you haven’t experienced it yourself?

I used to teach ADDIE to my graduate students. And while I would k

apologize and redirect them now, it was the best approach I knew then.

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But I wouldn’t continue having students practice ADDIE after seeing the many advantages of successive approximation.

I’m particularly grateful that our leading professional organizations, such as The eLearning Guild and Training Magazine, have been so active in providing opportunities for organizations to learn about successive approximation. ATD has been particularly supportive not only encouraging presentations at their conferences, long before popular support for ADDIE began to give way to successive approximation, but also actively commissioning, publishing, and promoting books on the topic as well as sponsoring numerous workshops.

Change Requires Leadership

Make no mistake about it. I assume in the future we’ll have a better model.

Maybe you have one already. My campaign here is to promote better e-learning and to help make it as practical as possible. I’m urging you to consider successive approximations because I think you may have something important to gain from it.

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I have worked with many organizations that have rigid software development processes, defined in detail—painful, unending detail. These processes not only are blessed by top management but also are rigor-ously enforced. Unfortunately, the underlying methodology is typically a waterfall method, and corporate standards are implemented to enforce completion of each phase, with irreversible sign-offs, and systematic rejection of good ideas that come later than desired. Although I’ve invariably found that individuals within these organizations ingeniously find ways to employ some of the processes of successive approximation, they frequently have to do it surreptitiously.

The successive approximation approach also conflicts with many widespread notions of project management, so project managers not fully versed in its principles may be uncomfortable and edgy, if not actively resistant. They may try to impose constraints that seem both logical and harmless but, in actuality, handicap the process enough to call its effectiveness into question. Thankfully, the Agile model for general software development embraces many of the same values and concepts of successive approximation. Software development managers versed in Agile can be very supportive of and helpful to training departments switching over to successive approximation.

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It’s an interesting situation—those who have had success with succes-k

sive approximation cannot comprehend how any organization would stick to older methods, and those who are working to perfect traditional methods are unable to see the innumerable practical advantages of successive approximation. It appears that you have to get wet in order to swim, but some just aren’t willing to put even a toe in the water.

They need a shove! Go ahead and push!

Advisory

If you are an executive, you will need to find champions of successive approximations and give them your full support. If you are a project manager, designer, or developer, you need to find a supportive executive who cares more about the results than maintaining traditional processes that are easy to manage but rarely produce successful solutions—a person who will take a risk in the interests of developing learning applications that will actually achieve desired outcomes.

SAM—A Successful Program of Successive

Approximation

Unfortunately, just understanding and appreciating the three key principles of successive approximation doesn’t lead an organization easily to 310

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fluent application. To see how the principles can translate into some critical details, let’s look at my own organization’s application of successive approximations as a case study.

Successive Approximation Model (SAM) is the name Allen Interactions has given to an articulated application of successive approximation.

Because of its continuing success from almost every point of view (at least that’s our view), we hold dearly to the postulates of successive approximation and apply them in a program that involves:

• A Savvy Start

• Recent learners as designers

• Typical learner testing

• Breadth before depth sequencing of design and development efforts

• Team consistency and ownership

• Production with models

Let’s explore in more depth:

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Successive Approximation Model

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(SAM)

SAM is an iterative prototyping model through which prototypes evolve into the final product. It works through small steps, frequently taking measures to ensure work is proceeding on the right path. And it focuses far more on learning experiences, learner engagement, and learner motivation than it does on content

organization, presentation of informa-

Start

End

EVALUATE

tion, and summative posttests, although

these latter components get full and

adequate attention when and where

DEVELOP

DESIGN

appropriate.

Let’s look at the primary build-

ing block of SAM—the iteration (see

FIGURE 14.4

Simple SAM iteration.

Figure 14.4).

Evaluate

Note that the process is circular and has few components. It begins with an evaluation or analysis. As a project gets started, you’ll probably know Successive Approximation and SAM

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many things about the situation—the goals, the learners, the delivery platform—but in the first iteration, you should ask any of the following questions for which you don’t have answers, and even revisit some of the initial givens in order to identify the best thing to do:

• What forms of delivery are available to us?

• Who are the learners and what needs to change about their performance?

• What can they do now? Are we sure they can’t already do what we want?

• What is unsatisfactory about current instructional programs, if any exist?

• Where do learners go for help?

• How will we know whether the new program is successful?

• What is the budget and schedule for project completion?

• What resources are available, human and otherwise?

• Who is the key decision maker and who will approve deliverables?

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Design

Here begins an unusual step among instruction design models. With the limited amount of analysis having been done at this point and with vital information surely lacking, the SAM designer is encouraged to use his or her instincts to guess at what might be a good solution and present it to stakeholders after little time or thought. In fact, the designer typically generates the first prospective design in a brainstorming, project kick-off meeting known in SAM parlance as a Savvy Start with key stakeholders in attendance.

The plan, in contrast to typical processes, is to swap the traditional question, “What should we do?” for the more helpful question, “Why shouldn’t we do this?” Of course, “this” refers to the idea or prototype the designer just advanced. The former question, the typical design question, is so broad it’s very hard to answer it without an extended, time-consuming discussion that’s likely not to be very productive. SAM is intended to be a fast process and can’t afford drawn out conversations. The latter question, “Why shouldn’t we do this?” is a, specific question about a specific idea. We need only discuss what’s good and bad about the proposed approach, not all the things that would be good and bad about 312

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all the alternatives anyone can think of. Assuming the designer has based the design on some available information and has some experience, the proposal will be somewhat on the mark. The conversation stimulated by this question will help fill in some open questions regarding project requirements and constraints. Perhaps most important, the exercise will help the designer understand who is really in charge among the stakeholders, what’s important to the client/organization, where opportunities exist, what hidden agendas lie beneath the surface, who really knows the content, and so on.

Designs should be visual from the beginning but not elegant. A quick, rough sketch is usually sufficient. It’s intended to be a disposable drawing that helps the team consider a possibility. This first design will surely be replaced in subsequent iterations, so it should have only just enough substance to identify strengths and weaknesses.

Develop

SAM is a process that depends on rapid prototyping to assist with ongoing analysis and design. In fact, development is more interleaved with design than subsequent to it. Design sketches are a form of prototype, or more often the basis of a prototype that will add essential interactiv-k

ity to the sketch to aid subsequent appraisal and evaluation by the team.

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Prototypes need be refined only to the point of clarifying what would be developed further were the project to continue building on the current design.

Functional prototypes substitute for detailed documentation (in common with Agile processes, which call for minimized, just-enough documentation) to be sure that time and effort are used most productively and to ensure the best communication to all stakeholders. Written specifications take considerable time to construct and even then are easily open to misinterpretation—especially when timing, logic, and the transitions of interactivity are involved. People can easily find they’ve approved a written specification that led to something entirely different from what they thought was described. Prototypes used to facilitate face-to-face discussion suffer much less from these liabilities and are essential in SAM.

Repeat Two More Times, Even Though

You Don’t Need To

Because you do need to. Upon completion of the first prototype, it’s time to evaluate it. We are returned to the top of the cycle where we repeat Successive Approximation and SAM

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the steps with some slight modification. In evaluation, we’re now looking at prototyped solutions from the previous cycle and again asking: “Why shouldn’t we do this?” Much hidden, incomplete, and inaccurate information is certain to be exposed at this time—information that might never have been revealed by even the most determined investigator in up-front analysis. Prototypes have a talent for flushing out information and doing so early before divergent expectations and understandings would be a disruptive surprise.

In the second iteration, it’s wise to set aside the first design even if it continues to have great appeal. Forcing yourself to come up with something entirely new is challenging and often seems both unnecessary and painfully difficult. But doing so nearly always reveals a superior design.

In the third iteration, design restrictions can be softened a bit. It’s still wise to try for something completely new. But if the preceding evaluations yielded no red flags and you cannot think of anything better, borrowing components from either or both the first and second designs is probably smart.

SAM Goes Commercial

The Simple SAM diagram in Figure 14.4 can actually serve as a com-k

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plete process for smaller projects. It’s simple, fast, and productive. Design and development interleave with evaluation assuring the process is on the right path. It’s the preferred process for academic and research pursuits.

But larger projects, especially those involving a team of more than a few people and needing formal budgets and project plans, or those projects for which development is completed by a separate team need to use a more formalized version of SAM as depicted in Figure 14.5. The major PROTOTYPE

IMPLEMENT

BACKGROUND

ROLLOUT

DESIGN

EVALUATE

DEVELOP

EVALUATE

Information

Savvy

Project

Additional

Design Proof

Alpha

Beta

Gold

Gathering

Start

Planning

Design

Preparation

Iterative Design

Iterative Development

Phase

Phase

Phase

FIGURE 14.5

Three-phase SAM is useful for larger projects and outsourced development.

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difference is that, in the extended model, the project moves on to a development phase when design iterations have been completed, whereas with Simple SAM, the product evolves through continuing iterations until time runs out or the team determines the product is ready for field testing.

Three-Phase SAM

Work in the three-phase version of SAM, “Big SAM,” is divided into these phases: preparation, iterative design, and iterative development.

Preparation Phase

The preparation phase is the period for gathering background information, even before attempting to design the first solution, which we are eager to do as quickly as possible. Backgrounding helps set the target, identify special issues, and rule out options that don’t need to be considered for some reason. It prepares for the intensive design activities by narrowing focus. This is the time for actively exploring the performance problem in broad terms—its context within the organization’s needs, goals, and outcome expectations.

Background information to be gathered includes:

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• Previous performance improvement efforts (if any) and their outcomes

• Programs currently in use (if any)

• Available content materials

• Organizational responsibilities for training

• Constraints, such as schedule, budget, and legal requirements

• The ultimate decision maker

• Predetermined definitions of project success

Key information gathering objectives:

• Identification of the key players and their commitment to participate. Key players include decision and budget maker, opportunity owner, subject matter expert, performance supervisor, recent learner, target learner, and organization’s deployment manager.

• Identification of the organization’s primary goal and its dependency on specifiable behavioral changes.

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In SAM, preparation work is done quickly at first, taking paths of least resistance. It’s not because this work is unimportant—it’s critically important to base decisions on accurate information and avoid the risk of making unverified assumptions, but the model prescribes performing analysis in the context of considering alternative solutions. It explicitly avoids exhaustive research that will be inevitably incomplete anyway and might not even prove useful.

At the start of the process, much time can be spent collecting information that could be relevant but turns out not to be very helpful. We need to get to the right research questions—quickly. Perhaps it’s surprising, but identifying the right questions comes most easily from iterative design where the context of alternatives makes them easier to consider. So we collect the information that’s readily available and move right on to the Savvy Start, knowing that analysis is far from finished.

The Savvy Start

The Savvy Start is really the same process as Simple SAM—a brainstorming event in which the design team and key stakeholders review collected background information and generate initial design ideas. This phase of the design process begins with jumping into solutions stakeholders may k

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already have in mind. It’s important to get these on the table as soon as possible, whether they are destined to become part of the final solution or eventually abandoned. Brainstorming proves invaluable for many purposes, not the least of which is determining who is really in charge and what outcomes are essential to success. And it is an amazingly efficient way of determining what the main performance objectives are, while simultaneously dealing with the organization’s hierarchy that can so easily obscure the real goals.

Further information is discovered by design and review of rapidly constructed, disposable prototypes. These prototypes promote brainstorming and creative problem solving, help the team determine what really is and isn’t important, and help align the team’s values.

Savvy Start Highlights

• Design cycles are used to evaluate the direction suggested by gathered information, assumptions, and early ideas.

• Prototypes are very rough and finished just barely enough to communicate and test ideas.

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• Outcome performance objectives are listed along with the prototyped designs that will be used to help learners achieve those objectives.

• Evaluation is done merely by discussion. Redefining and changing everything may be appropriate, including even the business problem to be addressed and the people to be trained.

• Speed is the key!

As in Simple SAM, design, prototyping, and evaluation continue to be done iteratively in small steps, but only exemplary samples of the instructional content are worked to completion. Additional content is created later. Even then, it’s done iteratively.

Iterative Design Phase

With larger projects or teams, documentation and coordination are prerequisites to success, but SAM pushes for minimal documentation.

Only essential documents should be

produced, and all should be questioned

PROTOTYPE

as to whether face-to-face communication

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or communication through prototypes

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wouldn’t be better.

DESIGN

EVALUATE

Note the additional activities along

the bottom of the model diagram (see

Project

Additional

Figure 14.6). Project planning identifies

Planning

Design

tasks, schedules their completion, and iden-

Iterative Design

Phase

tifies who will be responsible for them.

Additional design is produced through more FIGURE 14.6

Iterative design

iteration by a smaller team after the Savvy

phase.

Start team has disbanded. This produc-

tion design team focuses on additional content, resolving inconsistencies among designs, and solving any problems that may have arisen along the way. Additional design needs may also be identified in the development phase as issues or opportunities are discovered. In fact, it’s likely that will happen.

Iterative Design Phase Tasks

Project Planning

Project planning involves quantitative assessment of remaining project development details affecting timeline and budget. It involves careful Successive Approximation and SAM

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consideration not only of cost and quality management, but also of related communication, risk, schedule, scope, and staffing implications.

As discussed before, a concept essential to successive iteration is that no project is ever perfect, but through repeated work, projects can evolve and become closer to the ideal. This notion lends a great deal of practicality; it urges developers to put projects into use and think of making future iterations based on feedback from the field, rather than endlessly refining something that was actually good enough to begin with.

In support of planning, there can be more certainty of project availability on a preset date than is possible with other approaches. From the time functional prototypes are available, SAM projects continue to have courseware that can be used. The quality will rise, but at any point that it’s desirable to begin instruction, the best product possible within the project’s constraints will be available. This is a big deal and a major advantage.

To assist with this ultimate practicality, as improvement tasks are listed, each is given a level of priority for the next iteration: Threshold

Must be completed in this iteration

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Target

Expected to be completed in this iteration

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Future

Will be held back for a future iteration

Epic

To be considered after this project has been put in use Based on the designs created or selected in the Savvy Start, it becomes possible to create a project plan that has integrity. Of course, there are typically many pressures to produce schedules and budgets before enough is known to do so with credibility. But project planning really needs to be held off until after a Savvy Start. Once completed, content writing, media development, and programming can be estimated for the overall project plan.

Below is a list of project planning guidelines:

• The first step is to capture discussions and decisions by preparing and circulating a Savvy Start summary report.

• Initial media and content style guides can also be prepared for discussion. These are likely to be incomplete until additional design cycles have been completed. It’s easy and efficient to capture preferences as they spill out.

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• An initial draft of a content development plan can be prepared, indicating responsibilities and estimates of what material will be needed. Remember to prioritize items by threshold, target, and future.

The biggest risk lies with learning and performance objectives for which no solutions have yet been prototyped. There are likely to be some of these, which is why additional design is expected.

Additional Design

The Savvy Start session may take only a half-day, three full days, or sometimes even more. The length is often determined as much by incidental factors, such as availability of people or meeting space, as it is by project parameters, such as quantity and complexity of content or variation in learner readiness. As intense (and fun) as these sessions often are and should be, they are more properly considered brainstorming sessions rather than design sessions.

Good ideas and preferences spill out, the need for research and more information becomes apparent, and attractive instructional approaches emerge that need to be thoughtfully reviewed and refined, if not modi-k

fied extensively or even replaced on closer examination. Further, while the k

involvement of key stakeholders is essential to understanding the full picture of boundaries and expectations, these people usually can’t afford the time necessary to reach needed depth or cover all the content. Additional design work will be needed.

The additional design team will likely be smaller, and team members are often charged with preparing ideas in advance of meeting with others.

It remains important, however, to follow the rule of breadth before depth.

That is, it’s important to consider all the content to understand whether a broad variety of instructional treatments will be necessary, or whether just one or a smaller number will be appropriate for all content. The breadth before depth rule is harder to follow than it appears and can be the biggest liability of using SAM. With each iteration, design becomes more specific and reaches greater depth until all details are finalized. The temptation is to follow up immediately on ideas as they emerge. This takes the team into great depth, potentially spending too much time on a single content segment and leaving too little time for the rest. Generally, no content area should receive more than three iterations until after all types of content have been worked through their three.

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Prototypes

Prototypes continue to be important throughout the process to test and communicate ideas for the many reasons already cited. Multiple types of prototypes may be developed following the Savvy Start, depending on the selected means of delivery.

Media prototypes integrate media elements to demonstrate the desired “look-and-feel.” Layout, colors, fonts, images, and samples of other elements are brought together to form a clear design example and set criteria for full product development.

Functional prototypes are usually derived from Savvy Start prototypes by enhancing or adding details to make them testable with learners. In the case of e-learning, increased functionality provides a better sense of interactivity and usability.

Integrated prototypes present the amalgamation of functional and media prototypes along with representative content (i.e., feedback text, sound, video, and so on).

Special-purpose prototypes are created to test any technical or design components that must be finalized early in the process.

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Guidelines for Additional Design Tasks

• The same iterative process of design→prototype→evaluate is used.

The key decision makers should review and approve the new prototypes before development commences. Trusting they will be happy with how things are evolving is not a good practice.

• Except for small projects and those with a very narrow focus, there isn’t enough time to create functional prototypes for all behavioral objectives. It’s therefore important to review all content and organize it by similarities so that the smallest number of necessary treatments and prototypes can be identified. You need a prototype for each type of content, but not for each instance of the same type of content.

Iterative Development Phase

The iterations that are so advantageous to the design process are equally powerful for development activities. They allow stakeholders to have 320

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a continuing means of evaluating

IMPLEMENT

decisions and making corrections

within project constraints. The

importance of this advantage can-

ROLLOUT

DEVELOP

EVALUATE

not be overstated. Because a func-

tional product becomes available

quickly, before time-consuming

Design Proof

Alpha

Beta

Gold

refinements are made, stakeholders

Iterative Development

Phase

can get an invaluable preview of

the design becoming real. (See

FIGURE 14.7

Iterative development

Figure 14.7.)

phase.

Iterative Development Phase Tasks

Design Proof

At the beginning of the development phase, a plan is made to produce a design proof, which is typically the product of the first development phase cycle. Projects with large amounts of content will require a cycle for each type of instructional approach. Approval or disapproval will determine whether:

k

• Additional design work is needed. If so, the process returns to k

iterative design to produce needed designs.

• Another development iteration is needed to make corrections.

• Iterative development can proceed to producing an alpha version of the final product.

The design proof is essentially a visual, functional demonstration of the proposed solution that integrates samples of all components to test and prove viability. It has greater functionality and usability than the design prototypes and is built with the same tools that will produce the final deliverable. In this way, it not only tests the viability of the design but also of the production system. If technology is involved, the design proof needs to run on the equipment and network to be used by learners and demonstrate functional communication with the learning management system, if one is to be used. If role-playing, field demonstrations, or other activities are involved, trial runs are needed to be sure all details have been addressed to make activities run smoothly.

Design proof evaluation is a critical event in the process. Design proofs are used to scout out potential problems so they don’t become last-minute Successive Approximation and SAM

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crises. It’s the big opportunity for the design team and the stakeholders to check how the course will function as a whole. At this point, it is possible to get the clearest sense of what the overall solution is becoming while still having time to note corrections that are clearly needed.

Design Proof Highlights

• The first production cycle produces the design proof, which provides an opportunity to confirm all design decisions by actually presenting and testing a functional application on the intended delivery platform.

• Design proofs test:

• Design viability

• Whether the design is in a form that communicates requirements effectively

• The suitability of development tools

• The ability to deliver required learning experiences reliably and repeatedly

• Design proofs combine sample content, including examples of all k

components, with design treatments. Text and media are polished k

and representative of the final quality to be expected for all similar elements.

Alpha

The alpha is a complete version of the instructional application to be validated against the approved design. All content and media are implemented. If problems exist, and they well might because it is often important to begin evaluation before all issues can be rectified, those known problems are listed. No major, undocumented issues are expected to be found, but it’s nevertheless common for them to surface despite everyone’s best efforts.

Evaluation of the alpha release identifies deviations from style guides, graphical errors, text changes, sequencing problems, missing content, lack of clarity, and functional problems.

Alpha Highlights

• The second production cycle (or set of cycles for large projects) produces the alpha from approved designs.

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• Full content development integration occurs in this cycle. Samples no longer suffice.

• The alpha is nearly the final version of the complete instructional program to be validated against the approved design. All content and media are implemented.

• Completion and approval of the alpha signals the beginning of the validation cycles.

• Review of the alpha is expected to find only minor deviations from style guides, writing issues, graphical errors, and functional problems.

Beta

Because errors are nearly always found in alpha releases, a second cycle, called the validation cycle, is scheduled as part of the process to produce a second final product candidate, the beta release. The beta is a modified version of the alpha that incorporates changes identified during evaluation of the alpha. If all goes as expected and corrections are made carefully, the beta review should discover few errors, and those errors should include k

only minor typographical errors or corrections in graphics.

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Beta Highlights

• The alpha release is modified to correct errors identified in its evaluation. The resulting beta release is viewed as a first gold release candidate. There should be no functional errors at this stage. If there are, another iteration may be necessary to produce a second beta release and additional prospective releases if significant errors continue to be found.

• Not only subject-matter experts but also actual learners representative of the target population should evaluate the beta release.

Gold

Construction of the gold release is the final phase of development. At this point, although no project ever reaches perfection, the courseware becomes fully usable within the parameters of previously approved project guidelines.

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Gold Release Highlights

• If problems are identified, they must be rectified before the beta release can be given the gold crown. A modified version of a beta,

“beta 2” (sometimes called “gold candidate 2”), and, if necessary, a succession of numbered candidates is produced until all problems are resolved.

• When the beta performs as expected and no additional problems are identified, it simply becomes the gold release without further development and is ready for rollout implementation.

• It is hoped, but happens all too rarely, that rollout signals the beginning of an evaluation study to determine whether targeted behaviors are actually achieved and whether these new behaviors secure the expected performance success in the field.

More Help

SAM is conceptually very simple. Indeed, how complicated is the notion of (1) check your situation, (2) throw out some ideas, (3) pick out one or more k

to prototype and ask why it/they wouldn’t be a good approach, and (4) k

repeat until done? Of course, the quality of the ideas should be guided by professional knowledge of which instructional approaches are appropriate for the type of content at hand and for the learning population. But in terms of a process, this is pretty simple.

In addition to simplicity, the process helps identify the ultimate decision maker, keeps key people involved by giving them a comfortable level of control, and uses time and budget as effectively as possible. The goal is always to produce the best instructional product possible within given constraints.

But it isn’t as easy as one might think. Little nuances are important.

Tasks critical to other processes can actually be detrimental to SAM. But not all these details could be fitted within the confines of this book. So I highly recommend you turn to Leaving ADDIE for SAM: An Agile Model for Developing the Best Learning Experiences (Allen and Sites, 2012), and Leaving ADDIE for SAM Field Guide (Sites and Green, 2014), both ATD

publications.

Another iterative model developed independently by David Merrill (2013) shows many of the same principles espoused here as well as by agile software development practices. Agreement among these separately 324

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derived models confirms their advantages. Merrill’s excellent Pebble in the Pond is another excellent and helpful resource.

The Takeaways

Successive approximation is an approach for developing the best product possible within given constraints. It rests on three foundational concepts: 1. No e-learning application is perfect (ever). Pragmatic iterations advance initial designs, getting even closer to perfection.

2. Functional prototypes are better than storyboards and design specs (much better).

3. Quick and dirty prototypes are beautiful (and we’re happy to try three times).

Recognizing perfection is unattainable, the process uses iterations to first brainstorm ideas, subjecting each to the question of why the idea shouldn’t be implemented, and then selects promising ideas to proto-k

type and evaluate further. The winners of this process become functional k

prototypes, which evolve into the final deliverable product through continuous, iterative improvement and expansion.

The rule of breadth before depth provides an important governor to the spiraling process to prevent so much focus being spent on one content segment that others are either treated insufficiently or the project goes over budget. Following this rule, only three alternative treatments are allowed on any one segment of content before focus moves on such that all content has received design treatment. After the initial coverage, if time, money, and desire exist to continue improving the courseware before a field text commences, it can be done with positive results.

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Part III

Serious Learning

Games

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Chapter 15

Serious Learning

Games: Where

Rules Rule

As instructional designers, one of the things we should fear most is creating boring instruction that learners seek to avoid or escape how-k

ever they can. The very idea of a game seems attractive and energizing, k

as people engage in games voluntarily—quite the opposite of how they react to another dreary classroom training class or dreadful e-learning course. But games can also consume a lot of the learner’s time. And there’s the question, Can they really accomplish serious instructional goals?

As with all great creative achievements, it looks to the many designers that one must be born with unusual talents to create successful games or work tirelessly for thousands of hours. When it comes to games, we understand that markets allow corporations to spend extravagant sums to build commercial games just for their entertainment value. They start with multimillion dollar budgets, then search out top talent, out-fit them with the latest and most powerful hardware and software tools, and set them to work in very un-corporate-like environments. And still they expect only a few of these efforts to achieve great success.

How then can we even contemplate creating instructional games with essentially no time to develop our game design skills and relatively minuscule budgets?

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This chapter reveals the fundamental components of successful games, showing that a game need not be complex or expensive to exhibit strong appeal to players. It notes that nearly all games depend on players learning and that commercial games have surprisingly much in common with e-learning. We set the stage for later chapters in which we see how to integrate instructional content and entertaining games to create effective serious learning games.

Fun and Learning

Learning is often associated with

drudgery—a focused effort that isn’t

pleasant, that isn’t playtime. Home work

conjures up hours of drudgery and sac-

Get Back

rificing time that could be spent with

To

friends, fun, or needed relaxation. When

Work!

we hear students talk about having to

study, many of us recall those nagging

k

obligations. We’re relieved we’ve been

k

there, done that, and no longer have it

hanging over our heads. All that work when we would have preferred to be playing and having fun.

Generations have inherited the notion that, if it’s fun and something we would do voluntarily, it can’t be learning. Learning is a serious thing. It’s work and isn’t meant to be fun. The implication is that the distinguishing factor between learning and play is that, while play is easy and fun, learning isn’t either of these things. And, of course, we’ve probably all witnessed instructors trying to make learning fun. And it wasn’t.

But wait. We expect to expend energy when we play games and sports. And those activities are fun by definition. We participate in them voluntarily and precisely because they’re fun. We can be delighted when we’ve exhausted ourselves and played well. We’re doubly delighted if we’ve won or at least improved over past performances.

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Hold on. That sounds like fun and effort are natural ingredients for both play and learning. Why not consider them prerequisites? Just as with games, we should expect to expend energy and have fun learning!

Let’s Play! (And See What We

Can Learn!)

There’s an interesting dissonance here that

mustn’t be ignored. People, including some

GO PLAY!

of those funding training development, tend

to think fun activities aren’t particularly valu-

able (except for relief, maybe). And they think

strenuous activities will be rejected by trainees

who would be having anything but fun. This

line of thinking can lead to unfortunately

“easy” e-learning that is dry and, well, boring.

Learning games present great relief from

boring e-learning and offer an excellent learn-

ing platform, producing significant performance enhancement. We need to get leaders on board with just how smart it is to up the ante for investment in fun Serious Learning Games (SLGs).

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It’s Not Rocket Science

The ideas that learning can be a game and a game can provide valuable learning aren’t hard to grasp, but they may not be everyone’s first thought.

In support of the hampering perspective of fun versus learning (pick one) are bushels of attempts to make learning fun that resulted in boring games that produce little learning—failures on both scorecards. It would seem a simple and natural concept (fun games + learning activities = fun learning), but the combination has often resulted in anything but fun or learning.

Although learning is integral to games, it nevertheless seems to be quite challenging to inject instructional events into games without annihilating the fun. Is it because as players we sense seriousness when the content appears instructional and therefore take on a recalcitrant attitude? Does content need to be frivolous for us to keep our sporting hats on? Can we have fun only if it’s something we don’t have to do?

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My Stance

GOOD E-LEARNING IS

FUN!

Making e-Learning Worse

I have no reservation about promoting e-learning in general. It has many, many capabilities to assist each learner reach competency. Next to a private mentor, whom I’d often (but not always) prefer, e-learning offers great benefits—when it’s done right, of course. Not all e-learning is alike. And when e-learning is bad, it’s really bad. Even mediocre e-learning is bad.

k

Make no mistake about it; doing e-learning right isn’t as easy as throw-k

ing some presentation content together, even if you can present it with crisp clarity and professional-quality media. Although advancing tools help us tremendously to kick out digital courseware, it still takes thought, time, and effort to create e-learning that’s worth the learner’s time. And, if after that, the e-learning experience isn’t fun, I feel we’ve still missed the mark. We should always create learning experiences that are engaging, valuable, spirited, and, well, fun!

There are many ways to give learning experiences the appeal of games.

So many, in fact, that some scholars are grappling to identify and catalog them (Breuer and Bente, 2010). Karl Kapp (2014) is tremendously insightful and helpful in his book on gamification and his fun conference presentations. But as all working studiously in this field note, not all games have equal appeal. And when learning games are bad, they’re really bad.

Even mediocre learning games are usually worse than straightforward tutorials.

So, how can we get it right?

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The Essence of Serious

Learning Games

As always, my intent is to drive immediately to practical, applicable principles and guidelines. You will have no trouble finding guidelines for game design, even for learning game design elsewhere. A quick Internet search will return hundreds of links ready to send you on your way. But my assessment is that many of these enthusiastic mentors, while speaking eloquently on the subject, will mislead you or miss the critical points, even while their points seem logical and drawn from experience. Many of these sources oversimplify the issues, whereas some make the topic more complicated than it really is.

Some sources, for example, confuse gamification with SLGs. They may talk about the importance of scoring, power-ups, sound effects, great graphics, high-energy animations, and so on, because those elements are common in games. But while their novelty can be amusing and entertaining, you can create great games, learning and otherwise, without them. And, conversely, you can have all the bells and whistles without having created an effective learning game, serious or k

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otherwise.

As noted, Breuer and Bente have undertaken an effort to categorize games with particular focus on SLGs and how they relate to other educational concepts. These researchers observed there are “many partially conflicting definitions of serious games and their use for learning purposes.” The numerous efforts cited to classify games reflect the complexity of the issue. Indeed, games have many attributes, which, when added to the number of attributes each instructional paradigm has, result in an unwieldy list.

For the pragmatist, it’s important not to get hung up on terminology, but rather to focus on the critical attributes of SLGs and to gain confidence that proper deployment of them will make our learning experiences effective. Ornamentation can refine our work, but with much tighter constraints on learning game development than on developing mass-market games for entertainment purposes only, we need to skillfully address critical elements first.

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The Fundamentals

What Makes a Good Game?

I’ve learned you can create great games, instructional or not, without animation, sound effects, and all the typical ornamentation of video games, some of which is very expensive. I learned this from an outstanding keynote presentation given by Eric Zimmerman in 2009 at an e-Learning Guild’s DevLearn conference. Eric (here’s his website: ericzimmerman.com)

asked the audience, “What makes a good game?”

We answered … Eric replied …

Great graphics?

Nice to have, but no. Not essential.

Cool animation?

Nice to have, but no. Not essential.

Sound effects?

Nice to have, but no. Not essential.

Timer?

Nice to have, but no. Not essential.

Story?

Nice to have, but no. Not essential.

Scoring?

Nice to have, but no. Not essential.

Levels?

Nice to have, but no. Not essential.

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Leaderboard?

Nice to have, but no. Not essential.

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Failing to provide a satisfactory answer over an extended period of time, we finally gave up. I think it’s pretty interesting that the hundreds of us in the auditorium couldn’t find the answer Eric was looking for. He finally revealed his insight: “What makes a good game? Good rules.”

“Good Rules–Good Game.”

Zimmerman’s repeated answers of, “Nice to have, but not essential to a good game,” are something I’ve thought about many times as I’ve pondered why it seems so hard to develop instructional games that have the fun and attractiveness of successful entertainment games. I’ve come to understand and greatly appreciate his point: “good rules–good game; poor rules–poor game.” He’s right. And his insight is particularly important to those of us interested in merging games and instruction. You can have good games without expensive ornaments and enhancements, but you can’t have a good game that doesn’t have good rules.

Consider tic-tac-toe as an example (as Eric did). Tic-tac-toe is a classic and enduring game based on a simple nine-cell grid. A paper napkin 334

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× and a pencil are sufficient components (as all parents caught with restless children at slow

restaurants know). No graphics, animation,

sound effects, story, scoring, levels, or leader-

×

board required. What more do you need than

a napkin and pencil? The rules. Players need to

have rules to govern their play and determine

×

who wins and under what circumstances.

Rules and Strategies as Content

for Learning

Rules provide a critical element of context for game play while strategies provide the means to winning. Rules and strategies are foundational to the structure and nature of a game. Both rules and strategies have to be learned, of course, so game designers and instructional designers share a common interest in learning. Instructional designers have the additional need for learned skills to be transferable to useful performance outside the game.

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Because games succeed based on how much fun they are to play, game k

designers have a keen interest in making it quick and easy to get started.

The learning necessary to play should not be a distraction to the fun of playing. As instructional designers, we should share this interest with game designers, although we have a complementary interest in making sure the fun isn’t a distraction to the learning. But game designers are often more adept than we are at keeping learners learning and practicing over extended periods of time, even to the point of overlearning and developing robust skills. We need to understand and apply their techniques.

Types of Rules

For understanding games more deeply and using them for instructional purposes, it is useful to divide game rules into two groups, Rules of Play and Outcome Rules. These rules define how a game works: Type of Rule

Definition

Rules of Play

What players must, can, and cannot do

Outcome Rules

How the game responds to player actions

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Such stipulations can be written as production rules, that is, as specific if-then statements, and often are in game design and development, especially in programming. Here are some examples from tic-tac-toe: Type of Rule

Example Tic-Tac-Toe Rules1

(shown in production rule syntax)

Rules of Play

If it’s Player 1’s turn, then Player 1 must place one and only one X marker in an empty cell.

If it’s Player 2’s turn, then Player 2 must place one and only one O marker in an empty cell.

Outcome Rules

If Player 1 has just placed a marker, it becomes Player 2’s turn.

If Player 2 has just placed a marker, it becomes Player 1’s turn.

If a Player has placed three markers in a row (horizontally, vertically, or diagonally), then that player wins, and the game is over.

To play a game, it’s sufficient to learn the Rules of Play and Outcome Rules. But players must learn more to be successful (unless the opponent k

is clueless). The successful player learns strategies—when and how to take k

specific actions—and applies them effectively. This is where we see the primary opportunity to use games for serious instructional purposes.

Strategies are actions taken based on learning, recognition, recall, and reasoning. Even if these mental processes don’t reveal a strong basis for an action decision, they can narrow the choices from which to make an

“educated” guess. Developing successful strategies requires learning both types of rules (Rules of Play and Outcome Rules). Strategies are useful, of course, only in games that give players options and a basis for choosing among those options. Therefore, an important criterion for choosing a game structure for an SLG is the extent to which it gives players options and relevant criteria for choosing among them.

Definition: SLGs are games devised such that the strategies a successful player uses require the same skills of situation analysis, decision making, and performance as are needed in real-life situations.

1These are rules for contemporary play. There have been many variations, such as those that allow players only three markers, but markers can be moved from one cell to another as a turn of play.

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Merging targeted performance outcomes into the game rules themselves separates SLGs from the generally less effective, less serious, but still valuable and easier to create gamification, as we’ll see in a later discussion. But for SLGs, the parallel between successful player strategies and successful job performance is a key concept.

Anatomy of a Game of Strategy

Again I’ll use tic-tac-toe as an example of rules and strategies. I hasten to point out that the content and strategies of tic-tac-toe are not very transferable to performance abilities outside the game, but we’ll get to that essential element in the next chapter.

Rules of Tic-Tac-Toe

.

Rules of Play: What must, can, and cannot be done 1. Players must alternate turns.

2. Each player must use a unique set of markers (commonly Xs and Os).

3. Each player must add one and only one marker per turn.

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4. A marker may not be placed in an occupied cell.

k

5. Once placed, markers cannot be moved.

Outcome Rules: The Games Response

to Player Actions

6. The game ends if all cells are occupied.

7. A player wins and the game ends if he or she has three markers in a row, whether vertically, horizontally, or diagonally.

Strategies of Tic-Tac-Toe

1. If it’s the first play, then (as production rules) the player should take a corner cell, as the second player will then have the fewest winning options.

2. If the first player initially takes a corner cell and the second player does not take the center, then the first player can win by next choosing another corner (leading to two incomplete rows, only one of which the second player can block).

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3. If the first player takes a corner cell, then the second player should take the center square to avoid losing per consequence number 2

(assuming the first player plays strategically).

4. If one player has two markers in a row, then the other player should fill the third cell in the row to block (or risk a likely loss).

The Rules of Play need to be learned first and then the strategies can be learned. It’s essential to know what options you have as a player—what you can and cannot do—before you can begin to understand how strategies work, let alone discover valuable strategies yourself. With multilevel games, players learn a basic set of rules and then learn how to apply them successfully. Successes at the first level reveal additional rules associated with newly activated options, which enable additional strategies. Learning advances by alternatively learning rules and then mastering strategies.

Making a Serious Learning Game

Understanding the essential role rules play in games provides the basis for SLGs. As we either develop an entirely new game or adapt an existing k

one to use instructionally, rules and strategies that build on the rules are k

a prime design focus. As we’ll explore in much more depth in the next chapter, instructional content can usually, if not always, be written in the form of rules. Examples:

• If the product being returned was purchased within the last 60 days, then offer the choice of a cash refund, product replacement, or store credit.

• If the light switch works sometimes but not always, then check to see whether other switches are on the same circuit and exhibit the same behavior.

• If writing for publication, then make sure you schedule time to set aside your first draft for several days before making a second pass.

Once instructional content is formatted in this way, the design objective is to see how fully the content can become the game’s Outcome Rules.

Ideally, all instructional content rules would overlap on the Outcome Rules and/or the Rules of Play. See Figure 15.1

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Rules of

Outcome

Instructional

Play

Rules

Content

Rules of

Outcome

Play

Rules

FIGURE 15.1

SLGs merge instructional content and

Outcome Rules.

The Takeaways

Games require players to learn something even if it’s only the Rules of Play. And learn we do in the fun spirit of playing games. Games prove k

that learning can be fun and that we need not think learning must be k

an arduous task to be undertaken only when forced. Many past attempts to combine games and learning have not recognized the fundamental requirements of each, resulting in boring games that are neither fun nor instructional.

Developing successful learning games requires understanding what’s essential to a successful game. A primary concept is that good games are founded on good rules. If the rules are poor, no amount of ornamentation will sustain interest and involvement for long.

There are two types of game rules: Rules of Play and Outcome Rules.

Both types can be written as production rules (i.e., in an if/then format) and have to be learned to be a successful game player. A third type of rule, Game Strategies, must also be learned to be successful in most games, even in tic-tac-toe. SLGs are made by making the content to be learned and game rules the same—at least to a large extent.

Instructional content can be written as production rules also, which facilitates integrating instructional content and game structures.

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Chapter 16

Integrating

Instructional Content

and Games

Why does understanding the architecture of successful entertainment games, as we studied in the previous chapter, matter to us in the construction of serious learning games? It matters because we want to retain k

k

the entertainment factor as we either incorporate instructional content into existing game structures or develop a new game to help teach our content. Going either way requires us to understand fully the nature of both so that their integration provides the maximum effectiveness of each.

In this chapter, we take a closer look at the different types of games created primarily for entertainment, classifying them in a continuum ranging from pure games of chance at one extreme to games of pure skill at the other. We look to see which structures most readily accommodate instructional content while also retaining the aspects that make them fun.

We then look at a practical method of integrating games and content by converting instructional content into rules having the same structure as the rules that define entertainment games.

Types of Games

Within the realm of cognitive games, it’s useful to divide games into three major categories: games of chance, memory games, and games of skill (see Figure 16.1). Although many games have components of each, most k

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Games of

Memory

Games of

Chance

Games

Skill

5

9

K

12

Q

Q

J

J

K

3

20 7

Value of

Strategy

1

18

Bingo,

Jeopardy

Bridge Chess

Roulette

Wheel of

Soduku

Fortune

Blackjack

FIGURE 16.1

Types of games and value of player strategy.

games are primarily of one type. Roulette and bingo, for example, would be considered games of chance. There’s very little you can do to affect the outcome. You just wait to see whether you’re a winner. In the case of bingo, you might play more cards to facilitate an earlier win, but that doesn’t turn bingo into a game of skill.

k

Perhaps just to spice them up, all types of games can and generally do k

involve an element of chance. Consider Scrabble or the many card games in which players must work with randomly selected tiles or cards and yet can still apply strategies that greatly improve prospects of winning.

A combination of skill and luck determine the outcome, but with luck, anyone can win. An inexperienced player can defeat a highly skilled player, thus making the game interesting to a wider range of players. Generally, however, the greater skill you have, the greater likelihood of successful outcomes especially through repeated play.

Somewhere between memory games and games of chance are games dependent on recognition. This is where we might place Name That Tune and Pictionary. Jeopardy is primarily a knowledge recall game, but a good dose of chance determines whether familiar topics are available to a player.

As we move along the continuum from games of chance to games of skill, the value of strategy increases. SLGs reside where strategies and skills are fundamental to the game. Let’s examine each game category in more detail.

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Learning in Games of Chance

Games of pure chance do not pro-

vide opportunities for strategic play.

Figure 16.2 illustrates content to be

P

learned in games of chance. Before

ing

Rules of Play

la

they can play, players need to learn the

rn

yi

rules—at least some of them, although

a

n

e

g

there are usually few rules in games of

L Outcome Rules

chance. The roll of the dice, the draw of

the cards, a spin of the spinner, or the

computer’s random selection determines

the player’s fate.

Games of chance have little applica-

FIGURE 16.2

Basic game rules

bility for serious learning because chance

comprise the learning content in

determines outcomes completely, rather

games of chance.

than the player’s performance. Learning

is needed but confined to learning Rules

of Play and Outcome Rules, which are particular to the game itself. There is little transferability to performance outside the game.

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Learning in Memory Games

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Figure 16.3 illustrates the added learning required to succeed at memory games. From a learning perspective, memory games can promote drill and Content

P

ing

Rules of Play

la

rn

yi

a

n

Content

e

g

L Outcome Rules

Content

FIGURE 16.3

Targeted learning content is external

in memory games.

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practice when failed items are presented to the learner again. Memory games such as You Don’t Know Jack and Jeopardy provide frameworks that can be used best for testing, but there are more efficient and effective approaches for instruction (such as the Corrective Feedback Paradigm introduced in Chapter 13) and for testing. Perhaps their greatest asset is wide familiarity with their Rules of Play.

These games can be modified for learning applications, of course. For example, challenges can require learners to perform accounting tasks or to correct grammar. There is no limitation to simple recall, such as naming the authors of famous books or the inventors of various devices as is often associated with such games. Further, the basic structure can be used to select challenges to the learner based on past performance. The tasks presented by a Jeopardy card can actually be generated or switched to make them appropriate for players/learners as they work to complete a full panel (see Figure 17.2 in the next chapter).

Memory games are generally neutral with respect to the type of content to be learned or performed. We call these games extrinsic because the game is unconcerned with the instructional content, looking only for

“correct” or “incorrect” outcomes to determine what will happen next. If any instruction is provided, and it often isn’t, it is an incidental adjunct to k

the game structure and not actually part of it. (We’ll discuss the advantages k

and disadvantages of extrinsic games in just a moment.) Strategic versus Nonstrategic Games

Games of chance and memory games contrast with strategic games in fundamental ways. Although nonstrategic games can provide a useful environment for drill and practice, they are insufficient and inefficient for helping learners develop skills. Tasks in these games are often selected at random without instructional logic.

Nonstrategic games don’t easily incorporate learning multistep tasks or provide authentic contexts to help transfer learning to application in job performance. Further, their repetitive nature can become boring, at least partly because the game structure is (purposely) not related to the performance skills to be learned and applied. In fact, each answer given by learners is usually discrete and unrelated to previous or subsequent answers. The game fails to underscore and clarify relevance of this play to the learner. In contrast, serious learning games focus on strategic game structures. (See Table 16.1.)

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TABLE 16.1

Utility of Nonstrategic and Strategic Games

for Learning

Nonstrategic Games

Strategic Games

Good For

Drill & practice

Sustained engagement

sometimes

Relevance and value

Learning new skills

Multistep tasks

Authentic tasks

Learning in Strategic Games

Figure 16.4 illustrates components of strategic games—games in which players make decisions to achieve goals and receive rewards. Note that content is brought into the game itself and consists of three major parts:

• Rules (Rules of Play and Outcome Rules)

k

• Player strategies (deciding what actions to take when) k

• CCAF (context, challenge, activity, and feedback).

After learning at least enough rules so

that players can take acceptable actions,

strategic game players need to learn or

P

develop strategies to reach the great-

ing

Rules

la

est reward(s). In many strategic games,

rn

Player

yi

a

n

players must discover or construct essen-

e

Strategies

g

L

tial strategies through play and trial and

error. Hints may be offered, but solu-

CCAF

tions may not be revealed. This requires

learners to focus and think. It also builds

motivation and enhances the rewards

FIGURE 16.4

Learning content

for learners who succeed by developing

in strategic games.

successful strategies.

Players may also have to achieve a certain level of performance competency to make “power” options available that, even when available, Integrating Instructional Content and Games

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may not be presented or explained—thus rewarding experimentation and further learning.

CCAF in Games

Context, challenge, activity, and feedback are the primary components of instructional events. They are also, quite interestingly, the primary components of contemporary electronic games. This isn’t coincidental, to be sure, and the CCAF structure is extremely helpful for the development of SLGs (see Table 16.2).

Maximized Integration of Content

A primary difference between strategic games and other types of games is that strategic games are built on the content to be learned. The content can be fictitious facts, concepts, processes, and procedures or useful content to be learned and applied on the job. The key point: Most strategic game rules are if/then relationships the player/learner is expected to learn.

They provide a natural environment for integration of meaningful and useful content.

Level-Ups

k

As shown in Figure 16.5, a very popular and effective strategic game k

structure involves level-ups. Multiple levels segment content to avoid overwhelming beginning players/learners. This is akin to advancing learners from working on sets of enabling objectives stepwise up to full performance goals. Players need learn only a minimal set of rules to get started.

TABLE 16.2

Parallel Uses of CCAF for Entertainment Games

and SLGs

CCAF

Entertainment Games

SLGs

Context

Use a context or story to set

Use context to create relevance to

expectations and help players

the player/learner

make sense of the Rules of Play

Challenge

Use challenges to set goals for

Use challenges to define problems

players to achieve

learners should expect to encounter

Activities

Use activities to involve players and Use activities to develop and determine contingent outcomes

practice problem-solving skills

Feedback

Give points and other rewards to

Show consequences of

represent progress toward goals

player’s/learner’s decisions and

performance

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Level 2 Strategies

Level 2 Outcome Rules

Level 2 Rules of Play

Level 1 Strategies

Level 1 Outcome Rules

Level 1 Rules of Play

Game Play Success

Learning

FIGURE 16.5

Levels of learning in strategic games.

Games that require learning an extensive set of rules at first are much less appealing, of course, whether instructional or not.

The initial rules to learn are the Rules of Play, which enable the quick-est commencement of play. Playing yields the opportunity to learn Outcome Rules, typically by witnessing the consequences of actions.

k

Once some Rules of Play and Outcome Rules are internalized, players k

can begin to develop and apply strategies. This approach to instruction and learning is classic constructivism (Jonassen, 1999), in which learners actively discover and then come to appreciate the utility of discovered concepts. Learners apply strategic methods to determine relationships, rather than having them dished out to them in bullet points.

Fun in Learning

As we’ve seen, it is helpful for building SLGs to understand that rules determine the quality of a game and the fun as well, but there’s more to consider. And this is particularly important to understand when blending games and instruction:

What actually makes many games fun is discovering how to use rules to achieve desired outcomes.

When players develop rule-compliant strategies to achieve specific goals, they feel empowered and rewarded. They feel good about themselves and their learning. They feel eager to demonstrate, even if only to themselves, what they can now do. This is learning at its best.

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In a single-player game, it’s fun to demonstrate how quickly and efficiently you can meet a challenge. You look to beat your prior performance.

In a multi-person game, you hope your opponent has not developed as much understanding or ability as you have. And if your opponent is equal in this learning, you hope your opponent will make mistakes, perhaps because of having practiced less.

From this perspective of game analysis, consider how much of the fun in games is derived from learning and practice. And how much learning and practice contribute to successful game playing. Games and learning clearly go hand in hand.

Keeping the Fun: Keep Quiet

and Reward Strategic Play

In many games, fun comes from discovering the Outcome Rules and the power of various strategies. To take advantage of the motivational energy of fun, we need to resist the common temptation of instructional designers to teach rule-based outcomes and strategies explicitly. Keeping in mind that we learn important lessons from making mistakes, we need to let learners make mistakes and witness the consequences of those actions.

Trying to head off mistakes by explaining and demonstrating everything k

in detail prior to letting learners see what they can do, not only reduces k

the scope of what learners might learn but also reduces the motivational characteristics that games offer. And, it takes the fun right out of the game.

Both Outcome Rules and strategies are exactly the content to be learned when developing skills. Well-designed instructional games minimize the time and effort needed to learn the interface, so play can begin as soon as possible. With an intuitive interface, player/learners can focus primarily on the rules and strategies needed not only to succeed in game play, but also on the real world tasks they apply to. When the context is similar to the context in which learners will actually perform, transfer of learning to performance is increased, the learning experience is said to be authentic, and learners will consider their time to have been well spent.

Let’s look at the Sunny Side Grill, this time from the SLG perspective.

FIGURE 16.6

Initial Rules of Play.

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Example

Short Order Chef

E

http://zebr.as/1KJiQWw

This example game is fun and challenging to play. Its success as an SLG

derives from making nearly all the Rules of Play and Outcome Rules the very same content learners need to learn to be successful in their jobs. In other words, the Content Rules, Outcome Rules, and Strategies overlap almost fully.

As a short-order chef, most food preparation is relatively simple, consisting mainly of placing items on the grill or in a skillet and transferring properly cooked items to a plate. But timing and sequencing become very challenging when simultaneous orders come in for foods that vary significantly in cook time (see Figure 16.7).

This game is primarily about determining when to start cooking each food item so all items on an order ticket finish cooking at almost exactly k

k

the same time. Players/learners drag raw foods onto the grill or skillet in any order and at any time they wish.

What’s critical is that cooked items are cooked for the correct amount of time, not too little or too much, and served while all items are still hot. When there are multiple items to be served in the same order, it’s important not to let some cooked items get cold (they turn blue if they do) while waiting for other items to finish cooking.

Challenge Levels

As the player demonstrates ability to prepare orders and serve plates of the correct foods, properly cooked and at appropriate temperatures, the game advances to the next level where challenges increase. Some of the ways challenges increase are:

• The variety of foods requested increases.

• The variance in cook times increases.

• The number of items per plate orders increases.

• The number of plates to serve at the same time increases.

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k

FIGURE 16.7

Game board for Sunny Side Grill. This player dragged raw foods at k

top to grill and skillet, waited until properly cooked, and then dragged them to plates below, matching color-coded order tickets on the left.

Challenges at higher levels are both more difficult and more typical of actual situations employees will face. See Figure 16.8 for examples.

Learning Aids

A continuous running clock is available as an aid, and relative cook times are available for reference (see Figure 16.9).

Items on the grill continue cooking and customers continue to wait while learners are looking up cook times. As a further incentive to learn relative cook times so it won’t be necessary to look them up repeatedly, player/learners find a mess in the kitchen to clean up when returning to the game after each reference to aids. Let’s look at the underlying rules.

Rules of Sunny Side Grill

Level 1 Rules of Play: What must, can, and cannot be done 1. Player must select correct raw foods to cook matching presented order(s).

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Level 4

Two plates with three items

each

Congratulations on your new

job! Celebrate later, though,

’cause we’ve got a breakfast

counter to serve. Luckily,

customers come single file, so

you can focus on one ticket at a

time.

Level 5

Three plates—all served at

once

This is it: a triple-plate

showdown. You’ve made it to

the main dining room. Of

course, when you rise through

the ranks, the stakes rise with

you. Get ready to cook and

serve hot meals three at a time.

Not a single item can go cold.

Good luck, chef!

k

k

FIGURE 16.8

Challenge levels increase as players

demonstrate mastery.

2. Player can drag any food items to the grill, fry skillet, or plate.

3. Player can drag cooking (including overcooked) items away to discard.

4. Player cannot stop the clock or adjust grill temperature.

5. Player cannot stop cooking foods once items have been place on the grill or skillet.

6. Player cannot put cooked foods under a warming lamp or otherwise delay cooling once items have been plated.

Level 1 Outcome Rules: The game’s response to player actions Note: Plate orders appear one at a time in Level 1.

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FIGURE 16.9

Reference information available to players upon request.

1. If player fails to fulfill two one-item-per-plate orders with foods k

properly cooked and served at correct temperature on the first try, k

then player is given a second try.

2. If player fails to fulfill two one-item-per-plate orders with foods properly cooked and served at correct temperature on a second try, then player is sent back to the introduction.

3. If beaten eggs are placed on the grill, they will be rejected.

4. If beaten eggs are poured into the skillet, they will be cooked.

5. If player fulfills two one-item-per-plate orders with foods properly cooked and served at correct temperature, then player advances to Level 2.

6. If foods are not cooked long enough (times are specific to each type of food and revealed in the accessible reference chart), then they cannot be served and will be rejected.

7. If foods are left cooking too long after they appear fully cooked, then they burn and cannot be served.

8. If all foods ordered for a plate have been placed on the plate, then service is requested immediately.

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Level 1 Strategies (which are also targeted learning outcomes) 1. If foods have not finished cooking, then don’t plate them.

2. If foods have finished cooking, then get them plated quickly.

3. If fresh fruit is ordered, then put it on the plate at any convenient time (and never on the grill).

4. If scrambled eggs are ordered, then put them in the skillet.

Although we’ve only looked at Level 1 of this game in detail so far, note that game rules are the content we’d want learners to learn. Simply presenting this information to learners would not have nearly the same impact or meet the criteria of meaningful, memorable, and motivational learning. In fact, the information is very likely to be forgotten before the new chef got to the kitchen. Playing this game (which you can do at http://

bit.ly/1KJiQWw) makes the value of this experience quite clear. I had to return to Level 4 and practice many times before I successfully completed Level 5, but I had no thought of giving up until I’d met the challenge.

You’ll probably have the same experience and definitely would if you were actually an aspiring short-order cook.

Level-Ups

k

k

As the game advances through its multiple levels, the challenges become considerably more difficult. Not unlike the classic Lucille Ball skit in which she and best friend Ethel have to individually wrap chocolates Integrating Instructional Content and Games

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and keep up with a speeding conveyor belt in the factory, game players will have more food on the grill finishing up faster and faster. It becomes difficult to serve all food properly cooked and at the right temperature, until you can instantly recall relative cooking times. It took me many tries to meet the final challenge, but the game kept me practicing through all the repetitions necessary for me to have fully mastered the relative cooking times and also to have developed the ability to keep multiple orders in my head while working through them. Unfortunately, there was no opportunity to just gobble up my mistakes, like Lucy and Ethel did.

By the way, the player/learner is exposed to additional rules and needs to develop new and more complex strategies to succeed at the game. Subsequent levels require various combinations of foods on each plate, with multiple plates needing to be ready to be served at the same time. Chefs have to scan all plate orders going to the same table and manage increasing numbers of items cooking at the same time. Some of the more advanced game strategies and content to be learned include the following: Advanced Level Strategies (which are also targeted learning outcomes)

General Strategies

k

k

1. If multiple items must finish cooking at the same time, then a. slower-cooking items must start cooking before faster-cooking items.

b. faster-cooking items must start cooking before slower-cooking items have finished.

Example Instance-Specific Strategies (of which there are many) 2. If bacon and scrambled eggs or pancakes are ordered, then start eggs and pancakes when bacon is about one-fourth cooked.

3. If toast or fried eggs are ordered with other items, start them at the same time and

a. when bacon is three-fourths done or

b. before scrambled eggs/pancakes/hash browns are one-half done or

c. when sausages or ham are one-half done.

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Building Serious Learning Games

Understanding the components of SLGs informs the process of building them:

1. Start by itemizing content in the form of defined performance outcomes.

2. Articulate this learning content into rules, perhaps expressed by if/then statements, writing as many rules as necessary to define all challenges learners need to meet, including the contexts they will need to work within and the activities they will need to perform to be successful.

3. Sort the rules into the appropriate categories of (1) Rules of Play, (2) Outcome Rules, or (3) Strategies.

Learning content will transform into and constitute most of the Outcome Rules and nearly all of the strategies.

Rules of Play will likely require some special rules devised specifically to create the game framework, such as user interface protocols, k

conditions for changing levels, and so on. Outcome Rules may also k

include some game-specific mechanisms, such as performance scoring and rewards.

But the great benefit of this understanding is that it identifies exactly what needs to be done to create an SLG.

The Takeaways

Of the three classes of games, games of chance, memory games, and games of skill, the latter, games of skill, take the most advantage of player strategies and relates to the most important purpose e-learning addresses—the development of valued performance skills, including skills in which decision making and strategy determine success. SLGs work with skill-related content to achieve performance objectives.

The components of SLGs are:

• Rules (two types): Rules of Play and Outcome Rules, the latter of which relate various possible outcomes or consequences to specific actions player/learners may take.

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• Strategies: Goal-focused actions taken to get interim and, ultimately, the final desired results. Players learn to select actions based on their knowledge of Outcome Rules.

• Instructional content: Most usefully written as if/then statements and integrated into the application as either Outcome Rules or Rules of Play.

• CCAF: The framework for the game and learning experience: context, challenge, activity, and feedback.

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k

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Chapter 17

Learning Games,

Serious or Not?

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Although games are defined by their rules and depend on players learning the rules, not all games provide an optimal framework for learning and building performance skills useful outside the game. For instructional games, we want to use fun, engagement, and focus to achieve learning outcomes transferable to performance in real-world situations.

Sometimes game mechanisms that provide great entertainment actually get in the way of learning targeted skills. We don’t want player/learners focusing on aspects of games that don’t provide useful skills outside the game. Some games throw in random complexity just to keep learners from getting too comfortable. Some games intentionally make it difficult to determine Outcome Rules, even changing them without notice. Discovering hidden rules can be rewarding, but can also take a lot of time and effort. There is even a chance some players will never figure them out properly.

However, if players deduce cause-and-effect relationships in context, the discovery can be very rewarding and memorable. Sometimes even random rule changes are exactly what are needed, as it can reflect what happens in real performance contexts. Done right, obfuscation can actually enhance motivation and engagement, but it has to be done carefully and with safeguards, such as providing hint and help buttons when the k

player/learner has failed to make critical connections (but perhaps not k

before giving enough opportunities to try).

Games have excited the e-learning field recently, although game constructs have informed many successful e-learning applications for decades. Perhaps we’ve recognized that page-turning courses aren’t having the impact technology-supported instruction should have. But in the excitement, it’s important to be deliberate and purposeful in the use of games and game elements for learning lest we fail our learner as we do with page turners.

In this chapter we review alternatives designers have and examine guidance from various theoretical frameworks.

Selecting the Best Framework

Most important is selecting the right type of game to begin with. Some types of content fit well with some types of games but not with others.

Sometimes there are game formats that are quite suitable and other times it takes more work to adapt the format than to create an entirely new game.

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It’s basically a choice of whether you adapt the content to the game or the game to the content. Or whether you just add some game components to an e-learning framework. All approaches can succeed.

Serious Learning Games (SLGs), as discussed in previous chapters, can overcome some major learning obstacles, such as low learner motivation, complex situation-specific content, and the need for extended practice. SLGs can engage learners in content more fully, underscore relevance continuously, and keep the experience moving energetically toward defined performance goals. But just adding a few game-like elements can also have positive effects when done right. It can be faster and effective just to add a few game mechanisms. It requires less design creativity, too (Kapp, 2012). This is called gamification.

My take on the expected ROI in terms of learning outcomes for a range of approaches is depicted in Figure 17.1. Presentations, while they are by far the simplest and least expensive to develop also have the least likely impact. Gamification shows the first significant improvement, and as we move toward SLGs, while the cost and effort go up, the impact rises disproportionately to show superior ROI.

The chart is conceptual, of course. Many factors determine the actual ROI achieved. Clearly one can spend far too much on an SLG and yet k

have little learning impact, while gamification might be exactly the right k

approach. So let’s delve into the critical factors to determine how to achieve the best ROI.

Types of Learning Games

Let’s first sort learning games into two categories, depending on how they use instructional content. Extrinsic games are prestructured to work Presentation

Extrinsic

Gamification

Adaptive

Serious

Game

Tutorial

Learning

Game

FIGURE 17.1

Expected return on investment.

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without modification of the game to suit the content and frequently without much modification of content either. Intrinsic games are built on the nature of the content, such as declarative or procedural, and frequently also on specifics of the content, which can require logical, mathemati-cal, verbal, and/or visual simulation of a system. As we will see, intrinsic games provide the most powerful instructional platform but are also more difficult to construct.

Note: It’s important not to confuse terms and concepts here. Intrinsic and extrinsic motivators are not the same as intrinsic and extrinsic game structures. Although there is some correlation, when we are talking about game structures being intrinsic or extrinsic, we are talking about whether content is integrated into the game (intrinsic) or not (extrinsic) where it can be changed without modifying the game itself.

Extrinsic Learning Games

We frequently see some of the most famous TV game shows used as frameworks for e-learning. Jeopardy and Wheel of Fortune have provided successful entertainment and TV advertising venues for decades.1 When people, including instructional designers and authoring tool developers, think of games, they often think of such formats. Using these game k

formats for learning produces extrinsic learning games.

k

Advantages of Extrinsic Games

The main attraction of extrinsic games for e-learning is that they can be built as generalized structures or models for quick, easy insertion of content. You can acquire a prebuilt game structure/template or build it yourself and feed it content. It doesn’t matter whether the content is physics, famous athletes, chronology of war, or food preparation; factual content can be loaded into these games readily.

When the appropriate learning experience is drill and practice, extrinsic games can provide visual interest and a scoring system, as shown in Figure 17.2. Extrinsic games are actually cleverly disguised forms of navigation—page-turning, in fact, non-instructional interactivity—taking learners from one question or exercise to another, reporting progress, and calculating scores. Multiplayer versions build on competitive motivation, which provides an element of risk (losing to another player) that keeps learners attentive. Extrinsic games can be fun to play, and we value fun immensely.

1 Wheel of Fortune premiered in 1975. Jeopardy premiered in 1964.

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FIGURE 17.2

Extrinsic game board.

A further advantage of well-known game formats is that many people have already learned the Rules of Play and even the Outcome Rules. In this sense, the games are transparent and do not distract players from the instructional content where we want their focus.

As long as extrinsic games are used for repetitive practice, they can be a valuable and inexpensive step up from what might otherwise be monotonous practice. Whether staged as a competition with your own best prior performance, a race against the clock, or an opportunity to top the leader board, frameworks that help us stay energized while we practice are good and valuable.

Disadvantages of Extrinsic Games

There’s an important caution in the use of extrinsic game structures that is easily overlooked, especially because of the almost-irresistible enticement of quick and easy game development. While any game format seems more appealing than a lecture or presentation, misuse of games can actually deliver a worse experience and poorer results. There are many unfortunate Learning Games, Serious or Not?

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instances of applications intended to be instructional games that aren’t fun and don’t teach or foster learning well. When something fashioned and purported to be a game turns out not to be a game at all, learners are disappointed. Their response can be strongly negative. Similarly, when learners set aside time to learn a needed skill and the learning game leads to little learning, the response won’t be good.

Building on Extrinsic Games

When the game structure can be modified, there may be an opportunity to use much of the structure, take advantage of learner familiarity with Rules of Play, and create a more effective learning experience. For example, using a Jeopardy shell, consider the weakness that after an item is answered, correctly or incorrectly, that item is retired. But we know just seeing what a correct answer (or question in the case of Jeopardy) should have been doesn’t mean we will remember it (let alone understand it). Learners need to rehearse until they can confidently respond correctly.

A minor modification to the Outcome Rules of the game can help.

Retain the learner’s goal of completing the board, but instead of retiring a missed item, suppose you made it rest and reappear later. The game isn’t k

over until all items have been mastered. Your rules could be: k

1. If a correct answer is given on the first try, then make that item unavailable until after the learner has attempted at least four other items and then put it back on the board.

2. If a second correct answer is given to an item with no interim incorrect answer to it, then retire the item permanently.

3. If an incorrect answer is given, then make that item unavailable until after the learner has attempted at least two other items and then put it back on the board.

Such modification of extrinsic games, while not creating a full SLG, can yield very effective drill and practice experiences.

Drill and Practice versus Instruction

When extrinsic games are used for instruction rather than practice, they can be very inefficient and frustrate learners. My criterion for instruction (please forgive the redundancy, but it bears repeating) is that learning experiences must be meaningful, memorable, and motivational. All three 362

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are required; none are optional for making best use of the learner’s time.

Although baking all three qualities into a learning experience takes some knowledge and skill, intrinsic game concepts can provide designers excellent guidelines and constructs to work with.

Extrinsic games, however, provide little to make learning experiences meaningful. When extrinsic games are used to teach rather than to support extended practice, the positive result is that, yes, we have a game. That delivers a spark of interest and intrigue. Games suggest fun. And if its development can actually save authoring time as using extrinsic game structures can, there’s a double win. But what if learning takes more time and difficulty in mastery increases? It’s not inevitable that those things will happen with an extrinsic game format, but it’s likely they will, resulting in wasted development and learner time, not to mention the negative impact from frustrated, ill-prepared people.

Intrinsic Learning Games

Although action-consequence relationships can be memorized, in performance-targeted instruction we have higher learning goals. We want learners to achieve the ability to assess situations, determine appropriate k

actions, and affect them. We’re not after just the ability to recite what happens k

when a certain action is taken; we’re striving for the ability to perform effectively in real contexts. For full mastery, it’s important to be able to identify salient properties of a situation, construct a list of alternative actions, evaluate each based on anticipated outcomes, and then select and properly TABLE 17.1

Pros and Cons of Extrinsic Learning Games

Pros

Cons

• Low-cost enhancement to e-learning

• Requires learning game rules that have

no transferable value to targeted

• Accelerated development of e-learning

learning

• Enhanced motivation when learner isn’t

• Game structure doesn’t contribute to

motivated by the content itself (i.e., it

development of applicable

lacks intrinsic motivation)

performance skills

• Learners focus on winning rather than

learning

• Temptation to misuse a structure suited

to practice for instruction instead

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enact an effective response. And do so confidently and efficiently. The appropriateness of a game for acquiring performance skills seems obvious.

SLGs are intrinsic games and vice versa. The consequences of player/learner actions aren’t just judgments such as “Correct!” or “Sorry, no,” they are outcomes specific to the conditions and actions taken. As in real life situations, the outcomes in SLGs are often a modification of the situation the player/learner is in, which in turn requires another sequence of determining and taking further action as shown in Figure 17.3.

Intrinsic games are built on Outcome Rules. That is, intrinsic games enact Outcome Rules, allowing learners to witness the consequences of their actions and learn the critical relationships of context, challenge, action, and consequential feedback. As shown in Figure 17.4, the outcome consequence is often a new situation or challenge to be handled.

To walk through the diagram a bit, under Situation A, Action 1.B

results in Situation B. Action 1.C results in Situation C, and so on.

Context

Situation/Challenge

Identify possible, relevant actions

Identify probable consequences of each action

k

Select and take action

k

New situation

FIGURE 17.3

Actions modify the situation and

create the next challenge.

Context

Situation A

Action 1.B

Situation B

Action 1.D

Action 1.C

Situation C

Situation D

FIGURE 17.4

Context, situations, and actions in intrinsic

games.

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Context

Situation F

Situation A

Action 1.B

Situation B

Action 2.F

Action 1.D

Action 1.C

Action 2.B

Situation E

Action 2.E

Situation C

Situation D

FIGURE 17.5

Compounding consequences of actions in

intrinsic games.

Perhaps what engrosses us most in games is that actions we take open some possibilities for the next actions and preclude others. We can sometimes correct mistakes we’ve made. For example, note possible Action 2.B in Figure 17.5 retains the ability to achieve Situation B from Situation C. But sometimes actions taken preclude certain outcomes. For example, from Situation C, it is no longer possible to reach Situation D.

It can be important content to learn which actions hamper or delay, if k

not preclude, us from taking other actions in the future. In some games, k

making poor critical choices results in needing to start the game over again, which helps us remember the importance of taking appropriate actions at critical junctures.

Both intrinsic games and performance-targeted instruction have rules (Rules of Play and Outcome Rules) and strategies at their core. Presented situations in both cause learners to think, evaluate, and practice making critical decisions. This fortunate commonality between instruction and games provides the means for successful instructional games.

Game Component

Player/Learner Activity

Situations/Challenges

Identify possible actions

Possible actions

Select and take action based on learned consequences Consequences

Evaluate as new situation and challenge

Gamification

Presented information is easily and quickly forgotten unless it’s used, recited, or rehearsed in some way.

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We have an undercounter icemaker we turn on and off seasonally. It’s a great unit in terms of making ice that clinks just right in a glass of iced tea. But I have to keep the owner’s manual in a drawer next to the machine because none of us can remember how to turn it on and off. I guess the manufacturer didn’t want just anyone turning it on and off, so they made the controls far from intuitive. Strange.

I can remember that the instructions for switching the icemaker on and off are on page 10. (I remember the page number because it seems insane to have to scan through documentation, lots of it, to find buried in a nested paragraph the instructions for turning the unit on.) The needed information is clearly stated there. But I don’t remember what it says.

Okay, perhaps now I will. But I haven’t before writing this and neither have any family members. “You have to hold a button down for a long time, don’t you?” (Yes. The right button. A long time.) Infrequently used information is hard to remember, especially when you have no effective network of associations to help you. So we need to do more for our learners than present information to them.

Gamification is a snazzy term that catches attention. And thank goodness it does because it properly suggests there are many features we can use to enliven our e-learning. Gamification is not the same k

as making a game out of an e-learning module. It

k

doesn’t turn a presentation or a tutorial into a game.

But there are good reasons to be enthusiastic about it anyway. It often doesn’t take much to punch

up what would otherwise be dry and ineffective.

Gamification is simply the inclusion of game

elements, such as timers, points and scores,

levels, competition, and rewards to motivate and

engage learners. It falls between extrinsic games

and adaptive tutorials in terms of likely impact and return on investment.

(Refer to Figure 17.1.)

Gamification can enliven learning expe-

1

riences, but it is not a substitute for good

instructional design. Although I do not cham-

pion gamification over thoughtful instructional

2

3

design, a combination of both can be very

effective. Thoughtful design should frequently,

if not always, include game-like elements from

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the start. They are typically very easy to implement with today’s advanced authoring systems and can add focus on goals and motivation.

Caution

Gamifying e-learning doesn’t substitute for an effective instructional approach. It’s unfortunate, and all too common, to see attempts to overcome fundamental instructional design flaws through gamification. This is a sure path to ineffectual e-learning that learners find boring.

Once again, the CCAF framework—with its components of context, challenge, activity, and feedback—that works so well as a basis of interactive learning leads naturally to creating active learning and even gamification. If performance requires proficiency, then the measures of performance probably include such things as speed and accuracy. To make the learning context as authentic as possible, you would then want to include measures of speed, such as a timer, and accuracy, such as a point scoring system. These are the very mechanics that gamification looks to provide.

k

k

Instructional Thinking

Although promotion of game-thinking for instructional designers is popular and warranted, the importance of instruction-thinking when using game concepts should not be glossed over. Indeed, with game-based learning so popular, there’s a trend toward skipping essential principles of effective instruction and learning support in the excitement of creating games.

As Karl Kapp has shared with me, “Instruction doesn’t become more effective just because some type of game framework is involved.” Kapp (2012) compiled a collection of meta-analyses which clearly indicate that game-based instruction can be very effective and offer advantages such as learner enthusiasm and motivation. But the studies clearly point out that games lacking clear instructional objectives and techniques appropriate to specific learning outcomes perform less well than more straightforward tutorials (Clark, 2013). Yet we see the assumption that almost any game improves the learning experience. Enthusiasm for games sometimes overrides analytic caution for ensuring the game is actually appropriate and helpful.

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Gunter, Kenny, and Vick (2006) suggest, “A failure to base serious game design on well-established and practical instructional theories as proposed by well-respected educators like Robert Gagné and James Keller increases the risk of the game failing to meet its intended educational goals” (p. 2).

But they also point out choosing a theory to follow is difficult.

Theoretical Frameworks

Researchers have much to say about the critical elements of instructional events—its content, objectives, and approaches. Their research has much to offer but can be overwhelming to the practitioner. Let’s take a quick look to see what we can put to use.

The most well-known and representative models are as follows:

• David Merrill—First Principles of Instruction

• Benjamin Bloom—Cognitive Taxonomy (revised)

• John Keller—ARCS Motivational Model

• Robert Gagné—Taxonomy of Learning Outcomes

k

Each of these works contributes substantially to our knowledge of k

creating effective instruction. Let’s look briefly now to see what they offer for game-based instruction.

Merrill’s Classification

David Merrill’s work (2013) provides tremendous value through his focus on clear concepts with pragmatic application for the design and development of efficient, effective, and engaging ( e 3) instruction.

Fully in accord with my own perspective, Merrill focuses on problem-solving skills and performance development, as these capabilities are what most allow learners to increase the value they can contribute.

Recall of factual information facilitates problem solving and performance, but is rarely a sufficient goal by itself.

Merrill’s work has produced a practical classification of content, which identifies five types of content (see Table 17.2): (1) Information-about, (2) Parts-of, (3) Kinds-of, (4) How-to, and (5) What-happens.

Crossing each type of content with four types of instructional modes or strategies— tell the learner, ask the learner, show the learner, and have the learner do something—Merrill suggests an instructional strategy for each combination.

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TABLE 17.2

Instructional Strategies for Each Type of Content Instructional Strategy

Type of

Content

Tell/

Ask/

Show/

Do/Apply

Present

Practice

Demonstrate

Information-about

Name & Information Name &

—

—

Facts, associations

Information

Parts-of

Name & Information Name &

Name & locate

Name & locate

Name, description

Information

Kinds-of

Definition

Definition

Examples &

Classify examples

List of defining

nonexamples

property values

How-to

Steps & sequence

Steps &

Demonstrate task

Perform task

Steps and sequence

sequence

Conditions &

Conditions &

What-happens

Predict

consequences

consequences

Demonstrate

Conditions and

consequences

(if/then

(if/then

process

consequence

or determine

relationships)

relationships)

cause

Adapted from Merrill 2013, pp. 49, 89.

The Value for SLGs

k

SLGs focus on the right column and the bottom row—the performance k

outcomes column and the conditions-consequences row—shaded in Table 17.2. These outcomes are made of component skills, that is, the items identified in other cells of the table that must also be learned.

Depending on the quantity and complexity of these components, they can all be learned within one game, perhaps at graduated levels, through a series of games or other types of instructional events. The point here is that we have an excellent guide for identifying and classifying component content along with suggested instructional strategies.

We can construct interactions easily enough to teach each of these components, as Merrill demonstrates with many examples (2013). If the amount of content is relatively small, a series of interactions that asks the student to “tell, ask, show, and do” is likely to be quite sufficient and actually superior to many common approaches taken, such as simply presenting information to learners and then judging them on their ability to answer multiple-choice questions.

In SLG design, Merrill’s work is also of great value, showing how to decompose the ultimate performance goal and itemize all components players/learners need to learn. Whether the player/learner identifies the need on his or her own or game logic determines the need, effective Learning Games, Serious or Not?

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facilities geared to content type should be provided to assist the learner.

Merrill’s framework identifies just how to do this.

Bloom’s Taxonomy

Lorin Anderson and David Krathwohl (2001) revised the work Benjamin Bloom and his team did back in 1956 in creating a taxonomy of instructional content based on the cognitive activity each type of performance outcome requires (see Table 17.3).

Perhaps no other model has been used for so long as the basis of designing instruction. As with the other models, perhaps all borrowing from Piaget’s theory of cognitive development, it suggests a progression of abilities, each level of learning and skill a prerequisite to the next. Brenda Sugrue having previously taken issue with Bloom’s taxonomy (2002) has subsequently proposed an interesting and pragmatic approach (2013), combining the taxonomy with Merrill’s work and research by Koedinger, Corbett, and Perfetti (2012) to produce a Pure Performance Alternative.

The Pure Performance Alternative

As Sugrue (2002) proposes, a more radical approach would be to have no k

taxonomy at all, but instead to assume that all objectives are at the use k

level (i.e., “performance” objectives) and that learners will practice or be assessed on the particular performance in representative task situations.

After all, our ultimate goal is successful performance, so perhaps we’re overcomplicating things. If there are “enabling” subobjectives, those too can be treated as performance objectives without further classification. If, for example, a loan officer needs to be able to distinguish among types TABLE 17.3

Bloom’s Taxonomy (Modified)

Cognitive

Observable Performance

Activity

Create

Reassemble a set of parts, concepts, or procedures to produce an alternate solution.

Evaluate

Identify and compare advantages and disadvantages

Analyze

Deconstruct the whole and define relationship of parts Apply

Produce a desired result

Understand

Explain in original words or actions

Remember

Recall information (from long-term memory)

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of mortgages and describe the pros and cons of each type of mortgage as an enabling skill for matching house buyers with mortgages, then we design/provide opportunities to practice categorizing mortgages and listing their pros and cons before practice on matching buyers to mortgages.

If a car salesperson needs to be able to describe the features of different car models as an enabling skill for selling cars, then we design/provide opportunities to practice describing the features of different cars before practice on selling cars (see Table 17.4; Sugrue, 2013).

The Value for SLGs

Especially in SLG design but also in all e-learning design, we have to look at all objectives at the use level—which can readily be interpreted as making sure all learning activities take place within a meaningful context.

TABLE 17.4

Sugrue’s Content-Performance Matrix

Content

Information to

Practice/Assessment

Type

Present

(Depending on Level of

(Regardless of

Performance)

Level of

Remember

Use

k

Performance)

k

Fact

The fact

Recognize or recall

Recognize or recall

the fact

during task

performance

Concept

The definition,

Recognize or recall

Identify, classify, or

critical attributes,

the definition or

create examples

examples,

attributes

nonexamples

Principle/Rule

The principle/rule,

Recognize, recall, or

Decide whether the

examples,

explain the principle

principle applies,

analogies, stories

predict an event,

apply the principle

to solve a problem

Procedure

List of steps,

Recognize, recall, or

Perform the steps

demonstration

reorder the steps

Process

Description of

Recognize, recall, or

Identify origins of

stages, inputs,

reorder the stages

problems in the

outputs, diagram,

process, predict

examples, stories

events in the

process, solve

problems in the

process

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In the context of performance goals where recall of some information is necessary, as is perhaps always the case, it makes sense to both practice and assess recollection together in a meaningful context. This sounds a lot like learning in a simulated context which is exactly what we have in SLGs.

Keller’s ARCS Model of Motivation

Keller (1984, 2010) has focused on the role of motivation in learning for a long time. Indeed, the question is not whether motivation is important; it’s how do we enhance and maintain learner motivation? Or even more basically, how do we avoid dampening whatever motivation learners have when we begin to instruct them?

We are interested in games for learning precisely because games can motivate people to focus and learn, sometimes without even noticing how much time and effort they’ve happily invested. Although research on motivational factors was scattered and disjointed when he entered the field, Keller found studies clustered with respect to four determinants of human motivation. The four robust categories are shown in Table 17.5.

The Value for SLGs

k

k

Having the validated components of motivation for learning clearly identified gives explicit direction to the design of SLGs. As we design any e-learning, we can make it more effective by addressing each dimension.

• Attention Make sure we capture interest and curiosity at the outset.

This can be done by not revealing too much at first. In my own work on motivation, I’ve identified intrigue as a powerful means of getting people to focus and consider changing their behavior patterns.

TABLE 17.5

Dimensions of Human

Motivation (The ARCS Model)

Attention

Capturing the interest of learners;

stimulating the curiosity to learn

Relevance

Meeting the personal needs/goals of the

learner to effect a positive attitude

Confidence

Helping the learners believe/feel that they

will succeed and control their success

Satisfaction

Reinforcing accomplishment with rewards

(internal and external)

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Exactly the opposite of trying diligently to explain everything, it can be far more effective to demonstrate without explanation and challenge learners to figure it out. Don’t we all wish we could figure out how magicians seemingly do the impossible?

• Relevance It’s important in game design not to become focused on the game, making it fun and fanciful and so doing, making it irrelevant. Instead, we must always focus on authentic contexts and challenges, which make relevance obvious to learners.

• Confidence As with all instruction, it’s extremely important to match the level of challenges given to learners to their level of readiness. Too simple: it’s boring. Too difficult: it’s frustrating. Both are demotivating. The great thing about games is that when done well they can rapidly ramp up the challenge from a low entry point.

This avoids thwarting learner confidence by starting too high and actually rewards the learner by acknowledging entry abilities.

• Satisfaction Although some games have no end point, causing interest in them to diminish, meeting challenges that enable people to do things they couldn’t before can lead to great satisfaction.

Again, the nice thing about SLGs is that learners can see for k

themselves as they reach the final goal that they are, indeed, k

performing at a new and effective level.

Because Keller’s model is so consistent with the elements of a game and CCAF, these principles serve as excellent guides to ensuring learners stay motivated through their interaction with learning games.

Gagné’s Taxonomy of Learning

Outcomes

Not to be forgotten is Gagné’s classic taxonomy of learning outcomes (Gagné, Briggs, and Wager, 1992). Also working for a systematic and reliable method of designing instructional events, Gagné asserted that the following steps are close to essential and that they proceed in the following order (p. 190):

1. Gaining attention (reception)

2. Informing learners of the objective (expectancy) 3. Stimulating recall of prior learning (retrieval) Learning Games, Serious or Not?

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4. Presenting the stimulus (selective perception)

5. Providing learning guidance (semantic encoding)

6. Eliciting performance (responding)

7. Providing feedback (reinforcement)

8. Assessing performance (retrieval)

9. Enhancing retention and transfer (generalization).

Learning is necessarily an internal process. This taxonomy suggests the internal steps of learning, shown above in parentheses, are assisted by the external or instructional steps listed to the left.

The Value for SLGs

As the authors point out and much subsequent research suggests, one could have confidence that implementing the nine steps would result in learning, especially if one were to do this in a laboratory setting or in an instance where motivation was high, the content relatively short, and other conditions favored good outcomes. Actually, in any situation, this theory and supportive research should be given attention. They have k

obvious relevance to SLG design and should provide welcome assistance k

to designers.

Theory and Research as a Guide

I’m going to get myself in trouble now. But I’m going to forge ahead with the thought that questioning traditional principles and the legacy foundations of instructional design is always appropriate. Considering alternative perspectives can help us move forward or understand more fully. I’m in the odd position of lamenting how little learning research is considered in the development of the mountains of e-learning being shoveled out on the one hand and simultaneously encouraging people not to be religiously bound to it on the other hand. Obvious errors are made far too often, with many designers perusing novelty over effectiveness.

One may need to know the basic rules before being able to improvise effectively. But innovation is definitely needed.

Perhaps my most dangerous admission is that even though educated as a scientist, I’m not easily persuaded by a lot of research. In this, I’m holding fast to my scientist friend’s perspective that no one is and should be 374

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more skeptical of scientific findings than a good scientist. A good scientist is hesitant to generalize findings and quick to point out that unrecognized variances are always numerous. Any one or more of them may well be the most important determinants of any research finding and as yet unidentified. All studies of human behavior involve the spectacular complexity of the human brain and physiology. Varied outcomes are the norm, whether we’re looking at the effectiveness of medications or the means of training.

Many replications of studies are necessary before we should begin to have confidence in their conclusions.

So even with my hesitancy to follow the recommendations of studies, I hope to remain on good, if not credible, terms with my scientist friends and all my professors who may be questioning what their efforts with me have begotten. I’ll let feedback from learners and performance outcomes speak for my reasoned approaches, even as researchers continue their earnest efforts to discover just how to create superb learning experiences systematically. Skeptical as I may be, I’m rooting for their success.

And regardless of any unintentional implications of the preceding words, I strongly recommend becoming and remaining as familiar as possible with ongoing research regarding instruction and learning.

So, there it is. In the meantime, along with Sugrue who found support k

k

in questioning Bloom’s taxonomy from Bereiter and Scardamalia (1998) and Moore (1982), I wonder whether formal models aren’t too cerebral—if they don’t try to create too much structure out of what already has a serendipitous nature. I see many valiant attempts to structure learning materials carefully in both sequence and in content according to what Bloom’s and Gagné’s models prescribe. Professional efforts. And I think right away: boring.

Indeed, as I’ve often relayed, no one in all my education, even through my educational psychology doctorate, talked to me about the poisoning effects of learner boredom. That’s not to say formal models don’t suggest design characteristics that, rationally, shouldn’t be boring. But even relevance (which I think is important), for example, doesn’t guarantee an interesting learning experience. Things I know apply to me as a learner and that I would benefit from can still seem boring if not encountered in the right way.

So my unabashed design question is constantly: How can I be sure what I’m creating isn’t boring? A solution of great interest to me for some time now has been: intrigue.

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Intrigue

Let’s talk about intrigue in the light of SLGs. In notable contrast to revered instructional practices, game designers aren’t always so eager to give out information—even the information they know the player/learner needs. The fascinating thing to glean here is that game designers tend to keep quiet as much as possible and let player/learners discover what they need to know and be able to do. Think about that. They aren’t extolling the virtues of the content—explaining it and why it’s important. They are letting learners discover it!

Even then, learners may need to find a means of getting instruction.

It isn’t presented via pressing Next. When they do find the instruction and learn, learners feel as though they’ve discovered a secret tip they’re anxious to take advantage of. Contrary to many very logical (but not nearly as fun and creative) design virtues, wherein instructional designers explain what needs to be learned and why, game designers often work backward. Instead of setting forth anything like instructional objectives, game designers may show:

• A competitor (real or fictional) getting around obstacles, somehow k

doing something different from what the player/learner is doing.

k

Intrigue: How is he doing that?

• Nothing happening. Intrigue: Why isn’t it?

• Mounting costs of warrantee services. Intrigue: What’s causing this?

• Typical disastrous outcomes from doing the usual things. Intrigue: What needs to change?

There’s nothing like an enigma to get people curious, exploring, and thinking. It can free us from our typical safeguards, getting us to explore, to take a chance, and to appreciate surprises. Intrigue may be the most interesting learning motivator of all. Intrigue is exciting. Resolving it builds confidence and satisfaction.

Elevating intrigue may, and probably does, involve components of reception, expectancy, retrieval, selective perception, and so on.

To help learners when they’re stuck, we need to know how to break down complex skills into their components and provide the specific help intrigued learners may be anxious to get. I find Merrill’s work particularly helpful in thinking about ways to do this. But I think what’s really interesting for intriguing game-based design is what we initially leave out of an orderly, logical progression.

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Perhaps what I’m saying is what many have espoused (and been criticized for): there’s an art and skill to effective instruction that science is never going to supply. We need to let creative, inspiring, passionate instructors take the lead and do their magic through e-learning so unlimited numbers of learners can benefit.

The Takeaways

Extrinsic games are game structures that can use and substitute content information without modifying the game structure. They can help drive repetitive practice, by giving the learner a visually interesting indication of progress. And because practice is vital, extrinsic games have value.

Extrinsic games are not generally well suited to initial instruction or to the introduction of new content, however, and with their lack of ability to support specific content, may focus learners on winning or completion rather than on learning useful skills.

Intrinsic games and SLGs are built on specific content, incorporating the if/then relationships of the content into Outcome Rules and Rules of Play. The more similar the content rules are to Outcome Rules and k

Rules of Play, the more fully intrinsic the game is. Intrinsic games provide k

a powerful framework for teaching performance skills and promoting transfer of learning to post-learning performance.

Gamification can heighten motivation to engage in learning events, although it does not create a game from presentations or tutorials. Gamification involves adding mechanics often found in games such as timers, scoreboards, and rewards, but needs to support learning objectives purposefully or risk those same mechanisms becoming distractors.

Theoretical frameworks provide helpful reminders and structures for making sure learning games implement well-established and effective support for learning. CCAF is reflective of the four major theoretical frameworks informing instructional design and provides a strong, helpful foundation for creating SLGs.

Intrigue is a powerful motivator and, in some senses, turns the systematic application of learning theories upside down. Contrary to leading learners through a rational and validated series of steps to learning, intrigue happens when inexplicable events are presented. As with magic tricks, intrigue can attract learners to search, explore, and learn.

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About the Author

Michael W. Allen has been a pioneer in the

e-learning industry since 1970, when he devel-

oped one of the first learning management

systems for the NSF-funded Bio Learning

Center and for introductory psychology at The

Ohio State University. He was the innovative

force behind one of the most successful author-

ing tools ever created, Authorware, and the new

authoring and publishing system, ZebraZapps.

With over 45 years of professional, aca-

k

Michael Allen

demic, and corporate experience in for teach-

k

Ellis Island Medal of Honor ing, developing, and marketing interactive learning and performance support systems, he

has led teams of doctorate-level specialists in learning research, instructional design, computer-based training, and human engineering.

For decades, he has concentrated on defining unique methods of instructional design and development that provide meaningful and memorable learning experiences through stimulated cognitive interactivity.

He developed the advanced design and development approaches now used widely, including context, challenge, activity, feedback (CCAF)-based design and the SAM process for iterative, collaborative development.

Michael is a prolific writer, sought-after conference speaker, and recognized industry leader. For his widely recognized leadership in learning technology and business, he received the Ellis Island Medal of Honor from The National Ethnic Coalition of Organizations (NECO).

He received ATD’s Distinguished Contribution to Workplace Learning and Performance Award and also The eLearning Guild’s Guild Masters Award, which recognizes an individual for consistently contributing to the e-learning community in terms of both quantity and quality of content, thus helping make the community a vibrant center for learning.

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He holds M.A. and Ph.D. degrees in educational psychology from The Ohio State University and is an adjunct associate professor at the University of Minnesota Medical School.

Michael Allen was the director of advanced educational systems research and development of Control Data Corporation’s famous PLATO computer-based education system used around the world.

He was the founder and former chairman of Authorware, Inc. and also the primary architect of Authorware Professional, which was based on Allen’s extensive research on creativity and creative problem solving. It became a groundbreaking authoring tool combining power and ease of use, and ultimately the industry standard. Authorware, Inc. merged with Macromind/Paracomp to become Macromedia, which was later acquired by Adobe.

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380

About the Author

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References

Allen, M. W., Meleca, C. B., and Myers, G. A. 1973. A Model for the Computer-Management of Modular, Individualized Instruction. Columbus, Ohio: The Ohio State University.

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Allen, M. W. 2008. Michael Allen’s e-Learning Annual. San Francisco: Pfeiffer.

Allen, M. W. 2011. Successful e-Learning Interface: Making Learning Technology Polite, Effective, and Fun. San Francisco: Pfeiffer.

Allen, M. W., and Sites, R. H. 2012. Leaving ADDIE for SAM: An Agile Model for Developing the Best Learning Experiences. Alexandria, VA: American Society for Training and Development.

Allen, M. W. 2018. “The Successive Approximation Model (SAM): A Closer Look.” In Trends and Issues in Instructional Design and Technology, edited by R. A. Reiser and J. V. Dempsey. Boston, MA: Pearson Education.

Allen, M. W., and Merrill, M. D. 2018. “SAM and Pebble-in-the-Pond: Two Alternatives to the ADDIE Model.” In Trends and Issues in Instructional Design and Technology, edited by R. A. Reiser and J. V. Dempsey.

Boston, MA: Pearson Education.

Alessi, S. M., and Trollip, S. R. 2001. Multimedia for Learning: Methods and Development. Needham Heights, MA: Allyn & Bacon.

Andersen, D., Robert, C., and Covey, P. 1996. The Dax Cowart Case.

New York: Routledge.

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Blakemore, S., and Frith, U. 2005. The Learning Brain: Lessons for Education. Oxford: Blackwell.

Bloom, B. S. (ed.). 1956. Taxonomy of Educational Objectives: Classification of Educational Goals. Handbook 1: Cognitive Domain. New York: Longman, Green & Co.

Boggs, D. e-Learning Benefits and ROI Comparison of e-Learning vs. Traditional Training. http://www.syberworks.com/articles/e-

learningROI.htm Retrieved Nov. 2015.

Breuer, J., and Bente, G. 2010. “Why So Serious? On the Relation of Serious Games and Learning,” Eludamos. Journal for Computer Game Culture 4 (1): 7–24, www.eludamos.org/index.php/eludamos/article/

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Bruyckere, P. D., Kirschner, P. A., and Hulshof, C. D. 2015. Urban Myths about Learning and Education. Amsterdam: Elsevier.

Carlzon, J. 1987. Moments of Truth. New York: Harper & Row.

Clark, R. 2013. Why Games Don’t Teach. www.learningsolutionsmag.com/

articles/1106/why-games-dont-teach.

Docebo. March 2014. “e-Learning Market Trends & Forecast 2014–2016 Report.” Retrieved from https://www.docebo.com/landing/

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docebo-report.pdf.

Driscoll, M. 2002. Web Based Training, 2nd ed. Wiley, John & Sons.

Duffy, T. M., and Jonassen, D. H. 1992. Constructivism and the Technology of Instruction: A Conversation. Hillsdale, NJ: Lawrence Erlbaum Associates.

EDUCAUSE. 2013. The State of E-learning in Higher Education: An Eye toward Growth and Increased Access. www.educause.edu.

Gagné, R. 1985. The Conditions of Learning, 4th ed. New York: Holt, Rine-hart & Winston.

Gagné, R. M., Briggs, L. J., and Wager, W. W. 1992. Principles of Instructional Design. Fort Worth, TX: Harcourt Brace Jovanovich.

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Gunter, G. A., Kenny, R. F., and Vick, E. H. 2006. “A Case for a Formal Design Paradigm for Serious Games.” Journal of the International Digital Media and Arts Association 3(1): 93–105.

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Jonassen, D. H. 1991. “Thinking Technology: Context Is Everything.”

Educational Technology, June.

Jonassen, D. H. 1999. “Designing Constructivist Learning Environments.” In Instructional-Design Theories and Models: A New Paradigm of Instructional Theory, edited by C. M. Reigeluth (Vol. II, pp. 215–239).

Mahwah, NJ: Lawrence Erlbaum Associates.

Kapp, K. M. 2012. The Gamification of Learning and Instruction: Game-Based Methods and Strategies for Training and Education. San Francisco: Pfeiffer.

Kapp, K. M., Blair, L., and Mesch, R. 2014. The Gamification of Learning and Instruction Fieldbook: Ideas into Practice. San Francisco: John Wiley & Sons.

Keller, J. M. 1987. “Strategies for Stimulating the Motivation to Learn.”

Performance and Instruction 26(8): 1–7.

Keller, J. 2010. Motivational Design for Learning and Performance: The ARCS

Model Approach. New York: Springer.

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Keller, J. M., and Suzuki, K. 1988. “Use of the ARCS Motivation Model k

in Courseware Design.” In D. H. Jonassen (ed.), Instructional Designs for Microcomputer Courseware (pp. 401–434). Hillsdale, NJ: Lawrence Erlbaum Associates.

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Sugrue, B. 2002. Problems with Bloom’s Taxonomy. Performance Express, December.

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Additional Resources

In addition to those works quoted and specifically referenced, the following works have been particularly valuable to me in my work in e-learning and, without doubt, shaped much of my thinking. I share them in hopes they will benefit you as well.

Aldrich, C. 2009. Learning Online with Games, Simulations, and Virtual Worlds: Strategies for Online Instruction. San Francisco: Jossey-Bass.

Bingham, T., and Conner, M. L. 2010. The New Social Learning: A Guide to Transforming Organizations through Social Media. Alexandria, VA: ASTD

Press.

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Buxton, W. 2007. Sketching User Experience: Getting the Design Right and k

the Right Design. San Francisco, CA: Morgan Kaufmann.

Carroll, J. M. 1998. Minimalism beyond the Nurnberg Funnel. Cambridge, MA: MIT Press.

Clark, R. C., and Mayer, R. E. 2016. E-learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. Hoboken, NJ: John Wiley & Sons.

Cross, J. 2007. Informal Learning: Rediscovering the Natural Pathways That Inspire Innovation and Performance. San Francisco: Pfeiffer/

John Wiley & Sons.

Dirksen, J. 2012. Design for How People Learn. Berkeley, CA: New Riders.

Gee, J. P. 2003. What Video Games Have to Teach Us about Learning and Literacy. New York: Palgrave Macmillan.

Harasim, L. M. 2012. Learning Theory and Online Technologies. New York, NY: Routledge.

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Papert, S. 1980. Mindstorms: Children, Computers, and Powerful Ideas.

New York: Basic Books.

Peters, D. 2014. Interface Design for Learning: Design Strategies for Learning Experiences. Berkeley, CA: New Riders.

Rossett, Allison. 1998. First Things Fast: A Handbook for Performance Analysis. San Francisco: Jossey-Bass.

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Index

Page references followed by fig indicate an illustrated figure; followed by t indicate a table.

Absenteeism problem, 49

supply chain training, 183

Activity

trapdoor hints model on, 269

autonation interactive sales scenario,

What Does Glue Stick? training, 187,

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206, 207 fig

185 fig –190 fig

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characteristics of good and poor

Who Wants to Be a Miller? training,

interaction, 254 t

278–280 fig, 281 fig

Cooking with Flair training, 166

See also CCAF (context, challenge,

Earthquake epicenter e-learning

activity, and feedback) framework

instruction, 37 fig

ADDIE model (or ISD)

Expedia phone-based customer service

advantages of successive approximation

training, 137, 140 fig

approach over, 309

instructional interactivity component

description of the, 104–106

of, 237, 240 fig –241 fig, 247–248 fig, five phases of ISD or, 299–300

250–251, 254 t

flawed process of the, 300–301

In Their Virtual Shoes training, 294 fig

successive approximation approach

NYU Medical Center ICIS training,

superiority over, 309

272, 274–275

successive approximation as alternative

POST LERT First Responder

to, 301

training, 193, 195 fig –197 fig

true story on law book publisher

POST LERT Recognizing and

training and poor experience with,

Reporting training, 288, 290 fig

303–304

Railroad Safety for Professional

“A-ha!” experiences, 201

Drivers training, 247–248 fig

Airline mechanics training objectives,

short-order chef training, 151

142–143

Substance Abuse training, 285, 286 fig

Alessi, S. M., 69

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Allen Interactions, 311

Blended training

Allen, M. W., 5, 105, 215

improving performance environment

Alpha SAM (Successive Approximations

with, 54–55

Model) version, 322

improving training outcomes with,

Andersen, D., 86

54–55

Anderson, L., 370

Bloom, B., 368, 375

ARC’s Motivational Model, 368,

Bloom’s taxonomy, 368, 370, 375

372–373

Boggs, D., 23, 25

Attention

Bonk, 31

as dimension of human motivation,

Boring e-learning instruction

372 t

as being the most expensive training,

Keller’s ARC’s Motivational Model on,

22 fig

373

as not being effective instruction, 20

Authentic tasks

why it is deemed “acceptable,” 20–21

Earthquake epicenter e-learning

Brain research

instruction, 37 fig

instructional design guided by theory

importance of having learners perform,

and, 374–375

192

problems when applying to

POST LERT First Responder

instructional design, 69–71

training, 193–197 fig

providing insights for teaching, 1

Authorware

Brainstorming learning experience

earthquake epicenter e-learning

design, 307, 307 t

instruction created using, 39

Breuer, J., 332, 333

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WorldTutor, 228–229, 231

Bruyckere, P. D., 2, 3, 287

ZebraZapps, 39, 218–219 fig, 220 fig, Business problems

223, 223 fig

disguised competency problems,

Autonation interactive sales scenario,

47–50

205–208 fig

importance of identifying the “real,” 50

“Awareness goals,” 99–100

nonperformance, 45

performance environment, 53–55

Behavior, effect of motivation on, 124 fig

performance-related, 43–45

Behavior change

understanding that most are

creativity role in e-learning projects

performance problems, 45–46

for, 68–69

Business problem solving

incentives for, 51–53 fig

e-learning opportunities for, 46 t

See also E-learning goals; Outcomes

understanding limitations of training

Bente, G., 332, 333

for, 45–47

Bereiter, C., 375

See also Training

Berra, Y., 100

Beta SAM (Successive Approximations

Carlzon, J., 49

Model) version, 323

Carnegie Mellon University, 86

Bio/CMI, 214

Cavalier, R., 86

Biology Learning Demonstration

CCAF (context, challenge, activity, and

Center, 214

feedback) framework

Blakemore, S., 1

four basic steps in the, 101–102

390

Index

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gamification development using,

Common instruction paradigm, 158 fig

365–366

Competence. See Performer competence

instructional interactivity using the,

Computer-assisted instruction (CAI),

238–264

174

instructional success strategy of,

Computer History Museum, 8

101–103

Computer-managed instruction (CMI),

parallel uses for entertainment games

208, 209

and SLGs, 346 t

Confidence

POST LERT First Responder training

as dimension of human motivation,

using, 193–197 fig

372 t

research findings on e-learning and, 8

Keller’s ARC’s Motivational Model on,

See also Activity; Context; Feedback

373

Challenge

Constructivism theory, 69–70

autonation interactive sales scenario,

Content

205–206

e-learning and type of, 86

characteristics of good and poor

e-learning equation and presentation

interaction, 253 t –254 t

of, 123, 125, 126–127

Cooking with Flair training, 166

game rules and strategies as learning,

Expedia phone-based customer service

335–338

training, 138, 139 fig

guide learners to appropriate, 76, 78

instructional interactivity component

learner-constructed, 35–36

of, 238, 240 fig, 247 fig, 249–250,

navigation that lets learners see

253 t –254 t

organization of, 216, 220–221,

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In Their Virtual Shoes training, 294

230 fig

NYU Medical Center ICIS training,

navigation that lets learners see the,

272, 273 fig

216–219 fig, 226–228 fig

POST LERT First Responder

performance focus versus, 112

training, 193, 194 fig

select the right one for each learner,

POST LERT Recognizing and

132 t, 156–170

Reporting training, 288

short-order chef training, 150

providing learners with, 132 t, 146–147

Content classification

Railroad Safety for Professional

instructional strategies for each type

Drivers training, 247 fig

of, 369 t

short-order chef training, 150–151

Merrill’s work on, 368–369

on size fits all versus individualized,

SLGs application of, 369–370

114

Context

Substance Abuse training, 285

autonation interactive sales scenario,

supply chain training, 183

205

trapdoor hints model on, 269

characteristics of good and poor

What Does Glue Stick? training, 187,

interaction, 253 t

186 fig

Cooking with Flair training, 166

Who Wants to Be a Miller? training,

Expedia phone-based customer service

278

training, 138

Clark, R., 367

instructional interactivity component

Cognitive skill-building, 86

of, 238 fig, 239 fig, 245 fig, 249, 253 t Index

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Context ( Continued )

common design processes that may

In Their Virtual Shoes training, 293

prohibit, 71

knowledge delivery versus authentic,

the divergence and utility nature of, 68

113

of e-learning projects for behavior

learning sequences and, 178

change, 68–69

motivating learning and transfer skills

instructional design as art versus

using, 175–179 t

science debate over, 68–69

novelty versus reality of technology-led

instruction and, 172–175

Delay judgment instruction

NYU Medical Center ICIS training,

asking learners why their answers are

272

correct, 204 fig

POST LERT First Responder

autonation interactive sales scenario

training, 193

example of, 205–28 fig

POST LERT Recognizing and

motivating learners by, 132 t,

Reporting training, 289 fig

201–208 fig

Railroad Safety for Professional

valuable U-turns to provide learners,

Drivers training, 245 fig

202–204

Substance Abuse training, 284

Design. See E-learning instructional

supply chain training, 183

design

trapdoor hints model on, 269

Design specs

use an appealing, 132

functional prototypes preferred over,

t, 173 fig –191

302, 303–304

What Does Glue Stick? training, 187,

true instructional interactivity not

184 fig

k

possible with, 305

Who Wants to Be a Miller? training,

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Discovery learning model

278, 279 fig

description of the, 287

See also CCAF (context, challenge,

POST LERT—Recognizing and

activity, and feedback) framework

Reporting training using the,

Control Data Corporation, 12, 56–57

288–289 fig, 290 fig

Cooking with Flair training

reusability of the, 289, 292

context, challenge, activity, feedback

Disguised competency problems

used in, 166

outdated product designs, 48

“Do the Dip!” module of the,

poor morale, 49

167 fig –169 fig

tarnished reputation, 49

test-and-tell method used in, 166–170

turnover and absenteeism, 49

Corbett, A. T., 370

undercapitalized operations, 48

Corrective Feedback Paradigm (CFP)

unreliable equipment or tools, 49

description of the, 277–283

Docebo, 89

not for all instructional needs,

“Do the Dip!” test-and-tell example,

282–283

167 fig –169 fig

reusability of the, 282

Duffy, T. M., 70

spaced practice using the, 277 fig

Who Wants to Be a Miller? training

Earthquake epicenter e-learning

using the, 278–283

instruction

Covey, P., 86

experience versus presentation example

Creativity

in, 36–39

392

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learner activity in authentic context

delivering better learning with less,

example of, 37 fig

11–12

learner experience teaches the

optimal training project to budget and,

principle example of, 38 fig

19 fig

let the learner play example of, 38 fig

The e-learning dream, 18

page-turner versus page-turner with

E-learning equation, 122–123, 125,

question examples of, 36 fig

126–127

EDUCAUSE, 5

E-learning failure

Einstein, A., 110, 122

change is necessary to avoid, 42–43

E-learning

counterfeit successes as driving, 30

as being about individual and

the cycle of, 20 fig, 21

organizational success, 19–20

failing to define realistic goals as

as being fun, 332

reason for, 29

blended training solutions to improve,

to-do-list projects to avoid, 30–33

54–55

undercover operations as driving, 30

delivering lower costs and better

why we do things that we know will

learning, 11–12

result in, 62

high attribution rate of learners, 70,

See also e-learning failure; e-learning

126

success

how it fits in with effective training,

E-learning goals

83–94

beware of “awareness goals,” 100

learner motivation to learn versus to

match instructional strategy to

learn via, 128–129

outcomes and, 99

k

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smart, 87–89

problem of failing to define realistic, 29

you have choices in, 86–87

process of transforming, 30 fig

See also Instructional interactivity;

smart e-learning goal to change

Training; True training stories

behavior, 88 t

E-learning applications

typical ineffective strategy to reach

buyer alert regarding purchase of,

performance goals, 99 t

77–78

understanding what really matters in

limited emphasis on learner motivation

training, 32–33

in, 77 fig

See also Behavior change; Outcomes

E-learning benefits

E-learning guide for executives

anticipated, 174

design versus technology, 74–75

attributes of good e-learning and,

differentiating the good and the bad,

23 t– 24 t

73–74

competitive positioning organization

three priorities for training success,

as, 24

76–82

infrastructure advantages as, 27 fig

understanding e-learning as mean to

strategic advantages as, 25 t –26 t

training success, 81–82

tactical advantages as, 26 t– 27 t

E-Learning Guild’s DevLearn

training delivery advantages as, 27 t

conference (2009), 334

E-learning costs

E-learning instruction

boring instruction is too expensive,

boring, 20–21, 22 fig

22 fig

the failure cycle of, 20 fig, 21

Index

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E-learning instruction ( Continued )

prerequisites to, 43

optimal training project budget for,

unrecognized contextual factors, 42

19 fig

Emotion-arousing experiences, 103–104

practicality of delivering effective,

Employees

23–27 t

poor morale by, 49

rationale for reduced quality of, 21–22

providing incentives for good

reviewing the different perspectives of,

performance, 51–53 fig

4–9

turnover and absenteeism of, 49

the success cycle of, 18, 19 fig

See also Learners

understanding that entertaining

Enhanced drill-and-practice model

doesn’t equate good, 21

Corrective Feedback Paradigm (CFP)

See also Instructional design

type of, 277–283

E-learning instruction perspectives

description of, 277

as instructional approach instead of

EPSSs (electronic performance support

delivery platform, 5–6

systems)

lack of e-learning expertise, 6

description of, 258

learning games, 8

instructional interactivity versus,

low expectations of e-learning, 5

258–259 t

new mobile delivery options, 6–7

instruction applications of, 260–264

prevalence of e-learning, 4–5

Equipment problems, 49

social learning, 9

Evaluation

E-learning partnerships

of entertaining but ineffective training,

learner participation in, 88 t, 92

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21

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management and e-learning

of functional prototypes, 313

developers, 88 t, 89–91

Kirkpatrick’s four-level model of, 21

subject-matter experts (SMSs)

participation in, 88

measuring outcomes as part of, 31

t, 91–92

E-learning solutions

SAM iterative design phase, 314 fig,

Autonation interactive sales scenario,

317–320

205–208 fig

SAM iterative development phase,

Operation Lifesaver’s Railroad Safety

316 fig, 320–322

for Professional Drivers training,

Successive Approximations Model

244–248 fig

(SAM) component of, 311 fig –312

POST ALERT First Responder

Executives

training, 193–194

guide to good e-learning for, 74–82

E-learning success

needed for e-learning design, 59 t

checklist for doing the right thing for,

See also Management

63

Executive’s e-learning guide

the cycle of, 18, 19 fig

design versus technology, 74–75

design as the means to, 64

differentiating the good and the bad,

essential resources for, 57–62

73–74

how counterfeit successes drive

three priorities for training success,

failures, 30

76–82

list of some of the factors for, 41

understanding e-learning as mean to

pillars of, 91 fig

training success, 81–82

394

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Expedia phone-based customer service

POST LERT First Responder

training, 138–139 fig

training, 193

Expertise

POST LERT Recognizing and

challenges with simulated outcomes

Reporting training, 289, 291 fig

for created, 85

provide learners with intrinsic, 132 t,

comparing tell-and-test to the

198–200

test-and-tell methods to achieve,

Railroad Safety for Professional

165–170, 181

Drivers training, 247–248 fig

practice as necessary for developing, 84

real-world consequences versus

subject-matter experts, 59 t, 88 t, 91–92

didactic, 114

Extrinsic feedback, 199 t

short-order chef training, 151

Extrinsic learning games

Substance Abuse training, 285, 287 fig

advantages of, 360

supply chain training, 183

building on, 362

trapdoor hints model on, 270

description of, 359–360

What Does Glue Stick? training, 187,

disadvantages of, 361–362

184 fig –190 fig

drill and practice versus instruction

Who Wants to Be a Miller? training,

using, 362–363

280–282

game board of, 360, 361 fig

See also CCAF (context, challenge,

Jeopardy (TV game show) example of,

activity, and feedback) framework

360, 362

Field Guide (Sites and Green), 105

Outcome Rules of, 361, 362

First Principles of Instruction, 368,

369 t –370

k

pros and cons of, 363 t

k

Rules of Play of, 361

Functional prototypes

See also Intrinsic learning games

designing learning experiences using,

305, 308

evaluating your, 313

Failure. See e-learning failure

SAM iterative design phase, 314 fig,

Feedback

317–320

autonation interactive sales scenario,

206, 207 fig

Gagné, R., 368, 373

characteristics of good and poor

Gagné’s Taxonomy of Learning

interaction, 254 t

Outcomes, 368, 373–374

Cooking with Flair training, 166

Game rules

Expedia phone-based customer service

as content for learning, 335, 337

training, 137, 141 fig

how good games have good, 334–335

extrinsic, 199 t

tic-tac-toe, 337

instructional interactivity component

See also Outcome Rules; Rules of Play

of, 238, 241 fig –242 fig, 247–248 fig, Games

251–253, 254 t

CCAF applied to, 346 t

In Their Virtual Shoes training, 295 fig

the fundamentals of a good, 334

key performance indicators (KPIs)

getting the fun back into learning

providing authentic, 184 fig

using, 330–331, 347–354

NYU Medical Center ICIS training,

the ideas that learning can be a, 331

272

rules and strategies of good, 334–338

Index

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Games ( Continued )

IBM typewriters, 171 fig –172

Sunny side Grill, 348–354

ICIS training. See NYU Medical Center

tic-tac-toe, 334–335, 337

ICIS training

See also Learning games; Serious

ICONOS, 187

Learning Games (SLGs)

Incentives

Games of chance

different types of, 52

learning in, 342 fig, 343

management and training partnership

as nonstrategic game, 344

for success of, 53 fig

Games of skill, 342 fig

performance improvement by

Game strategies

combining penalties with, 55–56

description of, 336

Individualization

Serious Learning Games (SLGs), 336

e-learning as being about

Sunny Side Grill game, 353, 354

organizational and individual

tic-tac-toe, 337

success, 19–20

Game types

practical solutions for achieving

games of chance, 342 fig, 343

instruction, 164–170

games of skill, 342 fig

selecting the right content for each

learning in strategic games,

learner, 132 t, 156–170

345 fig –347 fig

on size fits challenge all versus, 114

memory games, 342 fig, 343

Individualization continuum

strategic versus nonstrategic games,

common instructional design paradigm

344–345 t

rating on, 158 fig

Gamification

individualized instruction paradigm

k

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caution about using, 367

rating on, 161–164

CCAF framework used for, 367

remedial instruction paradigm rating

issues to consider for using, 358–359

on, 160–161 fig

learning through, 365–367

selective instruction paradigm rating

ROI (return on investment) of, 359 fig

on, 159–160

serious e-learning versus, 333

Individualization practical solutions

Global positioning data (GPS), 7

comparing tell-and-test to the

Gold SAM (Successive Approximations

test-and-tell methods, 165–170,

Model) version, 323

181

Green, A., 105, 324

fixed content, variable learning,

Gunter, G. A., 368

164–165

fixed learning, variable time and

Hawking, S., 110

content, 165

Hippocratic oath, 110

fixed time, variable learning, 164

Homeland Security. See POST

Instruction

LERT—Recognizing and Reporting

complexity of effective, 64–65

training

EPSSs (electronic performance

Hulshof, C. D., 2

support systems) applications for,

Human resources

260–264

executives as essential, 59 t, 73–82

extrinsic games drill and practice

list of those required for e-learning

versus, 362–363

success, 59 t

interactive, 235–260

396

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novelty, 172–175, 181–191

Bloom’s taxonomy, 368, 370, 375

See also Technology-led instruction

cognitive activity and observable

Instructional design

performance, 370 t

art versus science debate over, 68–69

Gagné’s Taxonomy of Learning

challenges of designing learning

Outcomes, 368, 373–374

experiences, 298–302

Keller’s ARCS Motivation Model, 368,

checklist for what should be included

372–373

in, 63

Merrill’s First Principles of Instruction

complexity of effective, 64–65

and content classification, 368, 369 t

earthquake epicenter e-learning

Sugrue’s Content-performance Matrix,

instruction example of, 36–39

370–371

essential resources to support, 57–62

theory and research as a guide for

how it can heighten or stifle

design, 374–375

motivation, 125–129

Instructional interactivity

learner-constructed content is not

activity component of, 238,

substitute for, 35–36

240 fig –241 fig, 247–248 fig, 250–251, as the means to success, 64

254 t

motivation related to priorities of, 124

CCAF framework applied to, 238–265

potential problems when applying

challenge component of, 238, 240 fig,

research results to, 69–71

247 fig, 249–250, 253 t –254 t

as requiring study and practice for

context component of, 238 fig, 239 fig, excellence, 13

245 fig, 249, 253 t

selling it to the learner, 127

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definition of, 237, 264

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take a “design backward” approach to,

e-learning environments and rehearsal

101

taking a pragmatic approach to, 71–72

through, 236–237

technology versus the, 74–75

feedback component of, 238,

theory and research as a guide for,

241 fig –242 fig, 247–248 fig, 251–253, 374–375

254 t

See also E-learning instruction;

good versus poor interaction

Instructional design

components, 253 t –254 t

Instructional designers

natural learning environments of, 236

“A-ha!” experiences of, 201

pseudo, 255–259 t

design goal set by Manifesto for, 118

questioning versus, 260–264

game-thinking vs. instruction-thinking

as the supernatural power of

by, 367–368

e-learning, 236

Hippocratic oath for, 110

three-point checklist for good, 255 t

quality obligations of, 110–111

See also E-learning

Instructional design paradigms

Instructional interactivity examples

common, 158 fig

In Their Virtual Shoes training,

individualized, 161 fig –164

293–296

interactivity, 267–296

NYU Medical Center ICIS training,

remedial, 160 fig –161

272–276

selective, 159 fig –160

Operation Lifesaver Railroad Safety

Instructional frameworks

training, 244–253

Index

397

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Instructional interactivity examples

e-learning and “everything has

( Continued )

changed,” 4–10

POST LERT—Recognizing and

implications of new technologies, 9–10

Reporting training, 288–292

the “nothing has changed,” 3–4

Substance Abuse training, 283–287 fig

Insurance plans training story, 51

Supervisor Effectiveness training,

Integrated prototypes, 320

235–241

Interactivity. See Instructional

Who Wants to Be a Miller? training,

interactivity

278–283

Internal Revenue Service training, 86

Instructional interactivity paradigms

In Their Virtual Shoes training,

discovery learning, 288–292

293–296, 295 fig

enhanced drill and practice/Corrective

Intrinsic feedback

Feedback Paradigm (CFP), 276–283

examples of extrinsic versus, 199 t

problem-solving investigation model,

overview of, 363–365

283–287 fig

providing learners with, 132 t, 198–200

storytelling model, 292–296

Intrinsic learning games

task model, 271–276

action–consequence relationships in,

trapdoor hints model, 268–270

363, 364 fig

Instructional objectives

context situations and actions in, 363,

acceptable verbs for behavioral, 136 t

364 fig

airline mechanics training example of,

description of, 359

142–143

Outcomes Rules of, 363

Rules of Play of, 364

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components of quality, 135 fig –136

k

Expedia’s example of meaningful and

See also Extrinsic learning games

Investigation model

memorable, 138–141 fig

description of the, 283

how to better write motivating, 136

Substance Abuse training using the,

motivating learners through, 133–135

284–287 fig

See also Learning

Islam, K., 126

Instructional strategies

adapting e-learning to primary

Jeopardy (TV game show), 360, 362

performance outcomes, 85 fig

Jonassen, D. H., 70, 175, 347

consideration of task and learner

readiness, 85 fig

Kapp, K., 332, 359, 367

fitting to targeted outcomes, 83–87

Keller, J. M., 76, 368, 372–373

Merrill’s content classification and

Keller’s ARC’s Motivational Model, 368,

corresponding, 369 t

372–373

performance goals and typical

Kenny, R. F., 368

ineffective, 99 t

Key performance indicators (KPIs),

Seven Simple Success Strategies,

184 fig

97–107

Kirkpatrick’s four-level model of training

types of, 84 fig

evaluation, 21

Instructional systems design (ISD). See

Kirschner, P. A., 2

ADDIE model (or ISD)

Knowledge delivery vs. authentic

Instruction perspectives

contexts, 113

398

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Koedinger, K. R., 370

the ideas that it can be game, 331

Korn, E. R., 86

practice is necessary to, 85

Krathwohl, D., 370

social, 9

KTCA-TV’s Newton’s Apple (public TV

what we know about, 3

show), 187–191

See also Instructional objectives;

Outcomes

Learner-constructed content

Learning audience

don’t discard good instructional design

autonation interactive sales scenario,

for, 35–36

206

increased increase in, 35

Operation Lifesaver’s Railroad Safety

Learners

for Professional Drivers training,

attendance versus engagement by, 113

244

comparing typical and serious

POST LERT First Responder

e-learning for, 112–113

training, 193

don’t baby your, 132 t, 146–147

Learning environments

ensuring they are motivated to learn,

interactivity in the natural, 236

76–77

private versus social, 145–146

guide them to appropriate content, 76,

Learning experiences

78

advisory on creating M&M&M, 79

having them perform multistep tasks,

challenges of designing, 298–302

132 t, 192–197 fig

characteristics of quality, 109–110

high attrition rates of e-learning, 70,

emotion-arousing, 102–103

126

how e-learning can deliver lower costs

k

placing emphasis on motivation of,

k

and better, 11–12

77 fig

Successive Approximations Model

putting them at risk as learning

(SAM) to create, 3–4

motivator, 132 t, 144 t –155

See also Meaningful, memorable,

recent, 59 t

motivational (M&M&M) learning

selecting the right content for each,

experiences

132 t, 156–170

Learning experiences design

selling excellent instruction to the, 127

ADDIE model (or ISD) for, 104–105,

smart e-learning partnership with, 88 t,

299–301, 302, 303, 309

93

alternatives for, 308

strategy consideration of task and

brainstorming for, 307, 307 t

readiness of, 85 fig

constraints challenge of, 298–299

See also Employees; Motivation

functional prototypes for, 305

Learning

insights provided by unsuccessful, 308

contexts to stimulate, 178 t

prototypes for, 305, 308

examining the differing perspectives

quick iterations to explore multiple

on, 2

design ideas for, 306

game rules and strategies as content

See also SAM (Successive

for, 335–338

Approximation Model)

games for getting the fun back into,

Learning games

330–331, 347–354

“edutainment,” 8

getting the fun back into, 330–331

extrinsic games, 359–364 t

Index

399

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Learning games ( Continued )

Mastery. See Expertise

intrinsic games, 359, 363–365 fig

The Matrix (film), 1

instructional implications of, 8

Mayer, R. E., 287

overview of, 357–358

Meaningful, memorable, motivational

ROI (return on investment) of,

(M&M&M) learning experiences

358–359

advisory on importance of designing,

types of, 359–365 fig

79

See also Games; Serious Learning

how e-learning can provide, 81–82

Games (SLGs)

instructional design of, 80–81

Learning Management Systems (LMSs)

providing learners with, 76, 78–82

Bio/CMI, 214

using novelty to create, 146 fig –190 fig description of, 214–215

See also Learning experiences

services offered to learners, 215

Media prototypes, 320

See also Navigation

Meleca, C. B., 215

Learning objects. See Reusable learning

Memory games

objects (RLOs)

description of, 342 fig

Learning perspectives

learning in, 343 fig –344

e-learning and “everything has

as nonstrategic game, 344

changed,” 4–10

You Don’t Know Jack and Jeopardy

implications of new technologies, 9–10

examples of, 342 fig, 344

the “nothing has changed,” 3–4

Merrill, D., 368, 369 t –370

Learning research

Merrill’s First Principles of Instruction

instructional design guided by theory

and content classification, 368,

k

k

and, 374–375

369 t –370

on potential of learning games, 8

Mico, B., 70

providing insights for teaching, 1

Misguided training story, 44

Leaving ADDIE for SAM: An Agile Model

Mitzel, H. E., 214

for Developing the Best Learning

M-learning

Experiences (Allen and Sites), 105, 324

impact of new mobile delivery options

Leaving ADDIE for SAM Field Guide

for, 6–7

(Sites and Green), 324

mobile performance support versus, 7

Mobile delivery

Mager, R., 76

common questions and answers

Magic Keys. See Motivational Magic

about, 7

Keys

perspectives on impact of, 6–7

Malone, T. W., 76

Moments of Truth (Carlzon), 49

Management

Moore, 375

incentives for good performance role

Motivation

of, 53 fig

dimensions of human, 372 t

partnership between e-learner

effect on behavior by, 124 fig

developer and, 88 t, 89–91

e-learning equation and, 122–123,

See also Executives

125, 127–128

Manhattan Associates, 183

ensuring learner’s, 76–77

Manifesto. See The Serious eLearning

how e-learning design can heighten or

Manifesto

stifle, 125–129

400

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instructional design priorities related

additional learner-interface ideas, 226 t

to, 124–125

description and function of, 212–213

Keller’s ARC’s Motivational Model on,

interactivity versus, 257–258

368, 372–373

reusable, 213–214

to learn versus motivation to learn via

services for learners, 212–213

e-learning, 128–129

WorldTutor, 228, 232

perception and, 123–124

ZebraZapps, 218, 219 fig, 220 fig, 223, persistence for learning tied to, 124

223 fig

placing emphasis on learner, 77 fig

See also Learning Management Systems

See also Learners

(LMSs)

Motivational learning experiences, 81

Navigational metaphors

Motivational Magic Keys

description and function of, 232–233

1: build on anticipated outcomes, 132 t,

simplicity is best for, 233–234

133 fig –143

some concerns about, 233

2: put the learner at risk, 132 t,

Navigation imperatives

144 t –155

1: let learners see what’s here,

3: select the right content for each

216–219 fig

learner, 132 t, 156–170

2: let learners see how the content is

4: use an appealing context, 132 t,

organized, 216, 219–221

171 fig –191 fig

3: let learners see where they are, 216,

5: have the learner perform multistep

222 fig –223 fig

tasks, 132 t, 192–197 fig

4: let learners go forward, 216,

6: provide intrinsic feedback, 132 t,

k

222–223

k

198–200

5: let learners back up, 216, 224

7: delay judgment, 132 t, 201–209 fig

6: let learners correct their errors, 216,

Multistep tasks

225

importance of performing authentic,

Navigation (NYU Medical ICIS

192

training)

motivating learners with, 132 t,

192–197

1: let learners see what’s here, 228

fig

fig,

Supervisor Effectiveness training use

229,

of, 242 fig

2: let learners see how the content is

Myers, G. A., 215

organized, 229–230 fig

3: let learners see where they are, 230,

Nass, C., 146

231 fig

National Food Service Management

4: let learners go forward, 230–231

Institute

5: let learners back up, 231

Cooking with Flair training of,

6: let learners correct their errors,

166–170

231–232 fig

Who Wants to Be a Miller training of,

Newton’s Apple’s Why Does Glue Stick?

278–283

series, 187–191

National Science Foundation’s Biology

Nonperformance problems

Learning Demonstration Center,

e-learning opportunities for

214

improving, 46 t

Navigation

examples of, 45

Index

401

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Nonperformance problems ( Continued )

it’s expensive, 33

understanding limitations of training

it’s risky, 34–35

to solve, 45–47

it’s slow, 34

Nonstrategic games

Operation Lifesaver training. See

description of, 344

Railroad Safety for Professional

games of chance as, 342 fig, 343, 344

Drivers training

strategic versus, 344–345 t

Outcome Rules

utility for learning, 345 t

description of, 335, 336

Norris, B., 12 fig

extrinsic games, 359, 360

Novelty instruction

fund from discovering the, 348

creating memorable experiences using,

games of chance, 343 fig

182 fig –191

intrinsic learning games, 363–365

drawing learner’s attention using, 182

memory games, 343 fig

short-lived nature of, 173

Serious Learning Games (SLGs), 338,

supply chain training example of, 183

339 fig

technology-led instruction reality

strategic game level-ups, 347 fig

versus, 172–175

Sunny Side Grill game, 351–352

when it can be a valuable tool,

See also Game rules

181–191

Outcomes

Why Does Glue Stick?, 187–191

adapting e-learning to primary

NYU Medical Center ICIS training

performance, 85 fig

navigation of the, 228–232

blended training to improve

task model used for interactivity of the,

e-learning, 54–55

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272–276

creating expertise and challenges with

NYU Medical Center ICIS training

simulated, 84

navigation

e-learning equation and edification (or

1: let learners see what’s here, 229,

e-learning outcomes), 122, 124,

238 fig

127–128

2: let learners see how the content is

e-learning strategies consideration of

organized, 229, 230 fig

task and learner readiness, 85 fig

3: let learners see where they are, 230,

fitting strategy to targeted, 83–86

232 fig

Gagné’s Taxonomy of Learning

4: let learners go forward, 230–231

Outcomes, 368, 373–374

5: let learners back up, 231

match instructional strategy to desired,

6: let learners correct their errors,

99

231–232 fig

measuring e-learning, 31

motivating by building on anticipated,

Objectives. See Instructional objectives

132 t, 133 fig –143

Ohio State University, 214–215

See also Behavior change; E-learning

On-the-job training

goals; Learning

costs of, 34

Outdated product design problem, 48

e-learning failure due to undercover,

30

Page-turning mistake, 111

On-the-job training costs

Paradigms. See Instructional design

illustration of the stacked, 34 fig

paradigms

402

Index

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Part-task training, 178

POST LERT First Responder training,

PCD3 system, 56

193–197 fig

Penalties

POST LERT Recognizing and

performance improvement by

Reporting training, 288–292, 291 fig

combining incentives with, 55

Practice

when desired performance is

Corrective Feedback Paradigm (CFP)

unwittingly penalized with, 56

spaced, 277 fig

Perfetti, C., 370

extrinsic games instruction versus drill

Performance environment

and, 362–363

blended training solutions to improve,

necessary to learning, 84

54–55

onetime events versus spaced, 114

using training to fix the, 53–55

putting learners at risk during,

Performance goals

147–149

adapting e-learning to outcomes of

short-order chef training, 150–154

primary, 85 fig

Pre-flight safety checks training story, 44

In Their Virtual Shoes training, 293

Presentations

Operation Lifesaver’s Railroad Safety

earthquake epicenter e-learning

for Professional Drivers training, 244

example of experience vs., 36–39

typical ineffective strategies for

emotion-arousing experiences instead

reaching, 99 t

of, 103–104

Performance improvement

interactivity versus, 257–258

combining penalties with incentives

page-turning, 111

for, 55–56

Private learning environments, 145–146

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the possibilities of training for, 50–51

Problem-solving investigation model

providing incentives for, 51–53 fig

description of the, 283–284

Performance problems

Substance Abuse training using the,

e-learning opportunities for solving,

284–286 fig

46 t

Project planning tasks, 317–319

misguided training as traditional

Prototypes

approach to, 44–45

functional, 305, 308, 313, 321

performer competency as cause of, 43

integrated, 320

Performance supervisors, 59 t

media, 320

Performer competency problems

SAM iterative design phase, 314 fig,

as cause of poor performance, 43

317–320

e-learning opportunities for

special-purpose, 320

improving, 46 t

Pseudo interactivity

understanding who needs training to

caution regarding, 255–256

improve, 43–45

EPSS versus instructional interactivity,

when business problems are disguised

258–259 t

as, 47–50

navigation versus interactivity form of,

Performers (untrained) testing, 59 t

257–258

PLATO and the lights story, 121–122

presentation versus instruction form

PLATO system (1970s), 8, 12, 56, 145,

of, 256–257 t

215

Psychomotor skill building, 86

Poor morale problem, 49

Pure Performance Alternative, 370–372

Index

403

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Questioning vs. interactivity, 260–264

Reusable navigation, 213–214

Quinn, C. N., 6

Roland Berger Strategy Consultants, 5

Rules of Play

Railroad Safety for Professional Drivers

description of, 335, 336

training

extrinsic games, 359–361

activity component of interactivity,

game of strategy and role of, 337

247–248 fig

games of chance, 343 fig

background of, 244–245

intrinsic learning games, 363

challenge component of interactivity,

memory games, 343 fig

247 fig

Serious Learning Games (SLGs), 338,

context component of interactivity,

339 fig

245 fig

strategic game level-ups, 347 fig

feedback component of interactivity,

Sunny Side Grill game, 350–351

247–248 fig

See also Game rules

Recent learner’s design role, 59 t

Reeves, B., 146

SAM iterative design phase

Relevance

additional design task during the, 319

as dimension of human motivation,

guidelines for additional design tasks

372 t

during, 320

Keller’s ARC’s Motivational Model on,

illustrated diagrams of the, 314 fig,

372

317 fig

Remedial instruction paradigm,

overview of the, 317

160 fig –161

project planning task during the,

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Repurposing e-learning materials, 60–62

317–319

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Reputation problem, 59

prototypes task during the, 320

Research. See Learning research

SAM iterative development phase

Resources

design proof task during the, 322

caution against repurposing e-learning

illustrated diagram of the, 321 fig

materials, 60–62

overview of the, 316

list of human, 59 t

SAM preparation phase

reusable learning objects, 61 t, 65–67

illustrated figure of the, 314 fig

understanding the essential, 57–58

overview of the, 315–316

Reusability

the Savvy Start, 316, 318

Corrective Feedback Paradigm (CFP),

SAM (Successive Approximations

282

Model)

discovery learning model, 289, 292

ADDIE model compared to, 104–105,

problem-solving investigation model,

309

285

alpha version of the, 322

reusable navigation, 213–214

applying the postulates of successive

task model, 275–276

approximation to the, 311

trapdoor hints, 270

beta version of the, 323

Reusable learning objects (RLDs)

building learner-centered learning

description and advantages of, 65–67

experiences using, 3–4

pros and cons of, 61 t

description of, 70–71, 104–105,

specificity versus applicability of, 67

311–312

404

Index

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design component of the, 311 fig,

Serious Learning Games (SLGs)

312–313

application as learning game, 357

develop component of the, 311 fig, 313

CCAF applied to, 346 t

evaluate component of the,

examining the potential of, 8

311 fig –312

Gagné’s Taxonomy of Learning

getting help and additional resources

Outcomes value for, 368, 373–374

on, 324

the intrigue of using, 376–378

gold release of the, 324

Keller’s ARC’s Motivational Model

illustrated diagram of, 104 fig, 311 fig

value for, 372–373

remember that no e-learning

Outcome Rules of, 338, 339 fig

application is perfect when using,

ROI (return on investment) of,

302–303

358–359 fig

as simple success strategy, 104–105

Rules of Play of, 338, 339 fig

three-phases of the, 314 fig –322

strategies of, 336

See also Learning experiences design;

Sugrue’s Content-performance Matrix

Simple Success Strategy

for design of, 370–372 fig

SAM (Successive Approximations

Sunny side Grill, 348–354

Model) phases

See also Games; Learning games

illustrated diagram of the, 314 fig

Sheikh, K., 86

iterative design, 314 fig, 317–320

Short-order chef training, 150–151

iterative development, 314 fig, 320–322

Simple Success Strategy

preparation, 315–317

1: ask, would you want to learn from

Sandweiss, J. H., 86

this?, 97–98

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Satisfaction

2: match instructional strategy to

as dimension of human motivation,

outcome goals, 99

372 t

3: challenge awareness goals, 100

Keller’s ARC’s Motivational Model on,

4: design backward, 101

372–373

5: think context, challenge, activity,

Scardamalia, M., 375

feedback (CCAF), 101–103

Selective instruction paradigm,

6: think emotion-arousing experiences,

159 fig –160

103–104

Serious e-learning

7: use the Successive Approximation

basic principles of, 112, 115–117

Model (SAM), 104 fig –106

building the, 355

See also SAM (Successive

comparison of typical e-learning and,

Approximations Model)

112–114

Sites, R. H., 105, 324

the essences of, 333

Skills

gamification versus, 333

cognitive, 85

The Serious eLearning Manifesto

psychomotor, 86

basic principles of serious e-learning in

soft, 86

the, 112, 115–117

Skills hierarchy

description of the, 74

don’t start instruction at the bottom of

design values listed in the, 112–114

the, 132 t, 179–180

providing a goal to strive for

playing poker’s partial, 181 fig

instructional designers, 118

Skills transfer, 175–177 t

Index

405

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Smart e-learning

leadership required for organizational

critical elements of, 87–88 t, 89–92

adoption of the, 309–310

importance of engaging in, 87, 89

Sugrue’s Pure Performance Alternative,

Smart e-learning elements

370–371 t, 374

adequate financial investment, 87, 88 t

Sugrue, B., 370

goal is to change behavior, 87, 88 t

Sunny Side Grill game

necessary partnerships, 88 t, 89

advanced level strategies, 354

Social learning, 9

challenge levels of the, 349–350,

Social learning environments, 145–146

351 fig

Soft skill building, 86

game board of the, 350 fig

South Dakota State University, 215

learning aids, 350, 352 fig

Special-purpose prototypes, 320

Level 1 strategies, 353

Storyboards

level-ups of, 353–354

description and applications of,

Outcome Rules, 351–352

304–305

overview of the, 349

functional prototypes preferred over,

Rules of Play, 350–351

302, 305 fig –304

Super Mario Bros. (game), 147–148 fig

true instructional interactivity not

Supervisor Effectiveness training

possible with, 305

activity component of interactivity,

Storytelling model

240–241 fig

description of, 292

analysis of the, 243–244

In Their Virtual Shoes training using

challenge component of interactivity,

240 fig

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the, 293–296

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context component of interactivity,

reusability of, 295–296

239 fig

Strategic games

feedback component of interactivity,

learning in, 345 fig –347 fig

241 fig –242 fig

level-ups structure of, 346–347 fig

introduction to, 238

nonstrategic versus, 344–345 t

Supply chain training, 183

Strategies. See Game strategies;

Suzuki, K., 76

Instructional strategies

Szabo, M., 214

Subject-matter experts

e-learning partnerships with, 88 t,

Target audience

92–93

autonation interactive sales scenario,

needed for e-learning design, 59 t

206

Substance Abuse training, 283–287 fig

Operation Lifesaver’s Railroad Safety

Successive approximation method

for Professional Drivers training, 244

ADDIE model compared to, 104–105,

POST LERT First Responder

309

training, 193

advisory on finding champions to

Tarnished reputation problem, 49

promote, 310

Task model

applying postulates to the SAM,

description of the, 271

310–311

NYU Medical Center ICIS training

illustrated diagram of the, 301 fig

example of the, 272–276

introduction to the, 301–305

reusability of, 275–276

406

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Tasks

blended, 54–55

Earthquake epicenter e-learning

don’t drink the Kool-Aid on

instruction, 37 fig

learner-constructed content for,

instructional strategy consideration of,

35–36

85 fig

how e-learning fits in with effective,

motivating learner with perform

83–94

multistep, 132 t, 192–197 fig

incentives for good performance role

POST LERT First Responder

of, 53 fig

training, 193–197 fig

measuring outcomes of the, 31

risk of part-task training, 178

on-the-job, 30, 33–34 fig

Supervisor Effectiveness training use

risk of part-task, 178

of multistep, 242 fig

story on misguided pre-flight safety

Taxonomy of Learning Outcomes, 368,

checks, 44

373–374

understanding what really matters in

Teacher design role, 59 t

the, 32–33

Technology-led instruction

See also Business problem solving;

computer-assisted instruction (CAI),

E-learning; specific training examples

174

Training solutions

computer-managed instruction (CMI),

autonation interactive sales scenario,

214, 215

205–208 fig

e-learning design versus the, 74–75

Operation Lifesaver’s Railroad Safety

implications of, 9–10

for Professional Drivers training,

novelty versus reality of, 172–175

244–248 fig

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the typing ball syndrome,

POST ALERT First Responder

171 fig –172

training, 193–194

See also Instruction

Training success priorities

Tell-and-test method, 165–166 t

1: ensuring learners are highly

Test-and-tell method

motivated to learn, 76–78

comparing tell-and-test method to,

2: guide learners to appropriate

165–166 t

content, 76, 78

cooking training example of, 166–170

3: provide meaningful and

“Do the Dip!” module using the,

memorable learning experiences, 76,

167 fig –169 fig

78–82

starting context at the end using the,

Trapdoor hints model, 268–270

181

Trollip, S. R., 69

Thalheimer, W., 21, 31, 79, 146

True training stories

3M Company, Inc., 187

on inadequate training application of

Tic-tac-toe game

ADDIE model, 303

description of, 334–335

misguided pre-flight safety checks

rules of, 337

training, 44

strategies of, 337

“ridiculous expectations” of insurance

To-do-list project problem, 30–33

plans training, 51

Training

unwittingly penalizing desired

attempting to solve performance

performance, 56

problems with misguided, 44–45

See also E-learning

Index

407

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Turnover problem, 49

Why Does Glue Stick? novelty

The typing ball syndrome, 171 fig –172

instruction, 187–191

Wolf, S. L., 86

Undercapitalized operations problem, 48

WorldTutor, 228, 231 fig, 232

Unreliable equipment or tools problem,

49

ZebraZapps

Untrained performer design role, 59 t

description of, 218–219

earthquake epicenter e-learning

Vick, E. H., 368

instruction created using, 39

Sneak Peek feature of, 218–219 fig,

Wheel of Fortune (TV game show), 360

219 fig, 220 fig

Who Wants to Be a Miller? training,

template with current place and

278–283

progress reporting built in, 223,

Who Wants to Be a Millionaire (TV show),

223 fig

305

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Index

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WILEY END USER LICENSE AGREEMENT

Go to www.wiley.com/go/eula to access Wiley’s ebook EULA.

Document Outline

- Cover

- Title Page

- Copyright

- Contents

- Foreword by Tony Bingham

- Preface

- Acknowledgments

- Chapter 1 What's New?

- Part I The Business Perspective

- Chapter 2 Plain Talk

- Chapter 3 What You Don't Know Can Kill (Your e-Learning)

- Chapter 4 Making Success Possible

- Chapter 5 Executive's Guide to Good e-Learning

- Chapter 6 Where Does e-Learning Fit?

- Part II Great e-Learning Design

- Chapter 7 Seven Simple Success Strategies

- Chapter 8 The Serious e-Learning Manifesto

- Chapter 9 Motivation in Learning

- Chapter 10 Seven Magic Keys to Motivational e-Learning

- Magic Key 1: Build on Anticipated Outcomes

- Magic Key 2: Put the Learner at Risk

- Magic Key 3: Select the Right Content for Each Learner

- Magic Key 4: Use an Appealing Context

- Magic Key 5: Have the Learner Perform Multistep Tasks

- Magic Key 6: Provide Intrinsic Feedback

- Magic Key 7: Delay Judgment

- Chapter 11 Navigation

- Chapter 12 CCAF and Interactive Instruction

- Chapter 13 Interactivity Paradigms That Work

- Chapter 14 Successive Approximation and SAM

- Part III Serious Learning Games

- Chapter 15 Serious Learning Games: Where Rules Rule

- Chapter 16 Integrating Instructional Content and Games

- Chapter 17 Learning Games, Serious or Not?

- About the Author

- References

- Additional Resources

- Index

- EULA

Table of Contents

Cover

Title Page

Copyright

Contents

Foreword by Tony Bingham

Preface

Acknowledgments

Chapter 1 What's New?

Part I The Business Perspective

Chapter 2 Plain Talk

Chapter 3 What You Don't Know Can Kill (Your e-Learning)

Chapter 4 Making Success Possible

Chapter 5 Executive's Guide to Good e-Learning

Chapter 6 Where Does e-Learning Fit?

Part II Great e-Learning Design

Chapter 7 Seven Simple Success Strategies

Chapter 8 The Serious e-Learning Manifesto

Chapter 9 Motivation in Learning

Chapter 10 Seven Magic Keys to Motivational e-Learning

Magic Key 1: Build on Anticipated Outcomes

Magic Key 2: Put the Learner at Risk

Magic Key 3: Select the Right Content for Each Learner

Magic Key 4: Use an Appealing Context

Magic Key 5: Have the Learner Perform Multistep Tasks

Magic Key 6: Provide Intrinsic Feedback

Magic Key 7: Delay Judgment

Chapter 11 Navigation

Chapter 12 CCAF and Interactive Instruction

Chapter 13 Interactivity Paradigms That Work

Chapter 14 Successive Approximation and SAM

Part III Serious Learning Games

Chapter 15 Serious Learning Games: Where Rules Rule

Chapter 16 Integrating Instructional Content and Games

Chapter 17 Learning Games, Serious or Not?

About the Author

References

Additional Resources

Index

EULA