1st Edition

Learning Engineering Toolkit Evidence-Based Practices from the Learning Sciences, Instructional Design, and Beyond

Edited By Jim Goodell, Janet Kolodner Copyright 2023
    438 Pages
    by Routledge

    438 Pages
    by Routledge

    The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a rigorous and fast-emerging discipline that synthesizes the learning sciences, instructional design, engineering design, and other methodologies to support learners. As learning engineering becomes an increasingly formalized discipline and practice, new insights and tools are needed to help education, training, design, and data analytics professionals iteratively develop, test, and improve complex systems for engaging and effective learning. Written in a colloquial style and full of collaborative, actionable strategies, this book explores the essential foundations, approaches, and real-world challenges inherent to ensuring participatory, data-driven, learning experiences across populations and contexts.

    This book's second of two introductions, "What Is Learning Engineering?", is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

    Foreword by Chris Dede
    Preface by Bror Saxberg
    Introduction by Jim Goodell
    Part 1. Foundations: Essential Concepts in Learning Engineering
    Chapter 1. Learning Engineering is a Process by Aaron Kessler, Scotty D. Craig, Jim Goodell, Dina Kurzweil, and Scott W. Greenwald
    Chapter 2. Learning Engineering Applies the Learning Sciences by Jim Goodell, Janet Kolodner, and Aaron Kessler
    Chapter 3. Learning Engineering is Human-Centered by Khanh-Phuong Thai, Scotty D. Craig, Jim Goodell, Jodi Lis, Jordan Richard Schoenherr, and Janet Kolodner
    Chapter 4. Learning Engineering is Engineering by Avron Barr, Brandt Dargue, Jim Goodell, and Brandt Redd
    Chapter 5. Learning Engineering Uses Data (Part 1): Instrumentation by Erin Czerwinski, Jim Goodell, Steve Ritter, Robert Sottilare, Khanh-Phuong Thai, and Daniel Jacobs
    Chapter 6. Learning Engineering Uses Data (Part 2): Analytics by Michelle Barrett, Erin Czerwinski, Jim Goodell, Daniel Jacobs, Steve Ritter, Robert Sottilare, and Khanh-Phuong Thai
    Chapter 7. Learning Engineering is Ethical by Jordan Richard Schoenherr
    Part 2. Tools: Short Practical Chapters with Easy-Reference Checklists, Guides, + Templates
    Chapter 8. Tools for Understanding the Challenge by Erin Czerwinski and Jim Goodell
    Chapter 9. Tools from the Learning Sciences by Jim Goodell, Janet Kolodner, and Aaron Kessler
    Chapter 10. Tools for Teaming by Dina Kurzweil and Erin S. Barry
    Chapter 11. Lean-Agile Development Tools by Michelle Barrett and Jim Goodell
    Chapter 12. Human-Centered Design Tools by Sae Schatz, Khanh-Phuong Thai, Scotty D. Craig, Jordan Richard Schoenherr, Jodi Lis, and Janet Kolodner
    Chapter 13. Data Instrumentation Tools by Erin Czerwinski, Jim Goodell, Steve Ritter, Robert Sottilare, and Khanh-Phuong Thai
    Chapter 14. Software and Technology Standards as Tools by Jim Goodell, Andrew J. Hampton, Richard Tong, and Sae Schatz
    Chapter 15. Tools for Learner Motivation by Laura Casey, Diana Delgado, Jim Goodell, and Prasad Ram
    Chapter 16. Implementation Tools by Jodi Lis, Jessie Chuang, and Jordan Richard Schoenherr
    Chapter 17. Ethical Decision-Making Tools by Jordan Richard Schoenherr and Jodi Lis
    Chapter 18. Data Analysis Tools by Erin Czerwinski, Tanvi Domadia, Scotty D. Craig, Jim Goodell, and Steve Ritter
    Part 3. Vision and Commentary: A Short Story About Learning Engineering in the Future
    Chapter 19. The Future World with Learning Engineering: A Story by Sae Schatz and JJ Walcutt
    About the Authors


    Jim Goodell is Director of Innovation at Quality Information Partners, USA, and Chair of the Institute of Electrical and Electronics Engineers’ Learning Technology Standards Committee.

    Janet Kolodner is Professor of the Practice in the Caroline A. and Peter S. Lynch School of Education and Human Development at Boston College, USA, and Regents’ Professor Emerita, Georgia Institute of Technology, USA.

    “I am so impressed with how clearly and methodically this book has laid out the main tenets of the field and provided both practical examples and inspiring stories to bring the principles to life. I think this will be an immensely useful resource.”
    Joseph South, PhD, Chief Learning Officer, International Society for Technology in Education, and former director of the Office of Educational Technology at the US Department of Education

    “Popularized by MOOCs and the move to online learning during the pandemic, learning engineering is an emerging field that will become a standard discipline within universities in the years to come. Where science is the understanding of nature and engineering is the use of science in service of humanity, learning engineering incorporates learning science and cognitive science-based strategies to improve student outcomes. The Toolkit is an essential resource for understanding this field and a playbook for leveraging learning engineering.”
    Anant Agarwal, PhD, Chief Open Education Officer at 2U and Founder of edX

    “Great advancements in learning can come from a multi-disciplinary approach that recognizes the value of different professions and mindsets.”
    Angela L. Hernandez, EdD, Lead Skills Architect, Western Governors University

    “The outstanding authors of this text answered most of my uncertainties about the new learning engineering approach. The chapters in this well-written book clearly describe the questions that need to be addressed when designing learning experiences for all ages and contexts. It then provides tools that can be used to provide answers and generate new questions. Readers who might be concerned about whether “engineering” can be applied to human learning will be impressed with the scope of the chapters and the examples provided.

    I was especially attracted to the emphasis on supporting diverse learners and on making ethical decisions as well as the tools suggested for scaling small but successful efforts. The approach described in this book is our best hope for drawing together the many professional fields and specializations that attempt to create effective learning experiences in all areas. The authors clearly intend to adopt the best of what we’ve learned from past research in related areas while developing tools that fill the gaps in those areas. I intend to use the book as an introductory text for my undergraduate instructional design and educational psychology students.”
    Richard E. Clark, EdD, Emeritus Professor of Educational Psychology and Technology, University of Southern California

    “This new Toolkit brings together complementary, diverse, and fresh perspectives on learning and development in our rapidly changing world. I can see it forming an invaluable handbook for learning and development professionals, or curious organisational leaders interested in the science and engineering of effective learning at scale.”
    Julian Stodd, author and founder of Sea Salt Learning

    “I have talked with many CEOs of EdTech companies and chief learning officers over the past few years. All of them have asked, “what is learning engineering and how do we do it?” I have wanted to have a handbook I could hand them and their teams to be able to better mature their systems for designing and improving learning. Well, here it is! Full of theory, process, methods, tools, and above all, examples, stories, and extremely practical tips. This book has everything a learning team needs to begin applying learning engineering. And no wonder: It was written by a truly cross-disciplinary, cross-industry, cross-functional, and truly boundary spanning team. This book will sit next to my computer—well worn and marked through—as I guide teams in building impactful learning experiences.”
    David Porcaro, VP of Learning and Innovation at General Assembly and former Director of Learning Engineering at the Chan Zuckerberg Initiative

    “The Learning Engineering Toolkit effectively introduces the foundations of this emerging field and then provides a plethora of tools, strategies, and relevant examples that help the reader clearly see what this might look like in practice. There are many valuable concepts here for learning scientists, data scientists, software engineers, and leaders of organizations who are seeking a systematic approach to actively designing and building interventions to improve learner outcomes. This book presents a compelling case for learning engineering as a distinct field and topic to which any future-thinking education professional should be paying attention.”
    Chris Millet, Senior Director of Learning Design for the Penn State World Campus, Pennsylvania State University

    “The references and storytelling bring new insights, a fresh perspective and wonderful synthesis.”
    Jim Flanagan, Chief Operating and Strategy Officer, International Society for Technology in Education

    “This book is an essential toolkit for learning and development professionals. It’s a comprehensive roadmap for the new way of learning and working.”
    Amy A. Titus, EdD, Human Capital Managing Director, Deloitte Consulting

    “The Learning Engineering Toolkit offers a path to revolutionize how we experience learning at school and work—by codifying the development and delivery of learning as a data-driven, continuous design process. In the true spirit of human-centered design, learning engineering integrates the power of diverse scientific disciplines, mixed-methods data collection, and a bias for action through constant iteration and co-production with learners. Research is design, and design is research. By building evidence into every step of the learning design and delivery process, learning engineering can ensure learners engage fully, learn deeply, and perform optimally.”
    Sydney Heimbrock, PhD, Chief Industry Advisor for Government, Qualtrics