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

ISBN-13: 9781032232829 / Angielski / Miękka / 2022 / 438 str.

Jim Goodell

Opis

The Learning Engineering Toolkit is a practical guide to the rich and varied applications of learning engineering, a process and practice that synthesizes the learning sciences with human-centered engineering design methodologies and data-informed decision-making to support learners and their development. 

Spis treści

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