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

✍ Scribed by Jim Goodell

• Publisher: Routledge
• Year: 2022
• Tongue: English
• Leaves: 438
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Cover
Title Page
Copyright Page
Table of Contents
Foreword
Preface
Introduction
How do I use this book?
What is learning engineering?
Foundations
Chapter 01: Learning Engineering is a Process
Chapter 02: Learning Engineering Applies the Learning Sciences
Chapter 03: Learning Engineering is Human-Centered
Chapter 04: Learning Engineering is Engineering
Chapter 05: Learning Engineering Uses Data (Part 1): Instrumentation
Chapter 06: Learning Engineering Uses Data (Part 2): Analytics
Chapter 07: Learning Engineering is Ethical
Tools
Chapter 08: Tools for Understanding the Challenge
Chapter 09: Tools from the Learning Sciences
Chapter 10: Tools for Teaming
Chapter 11: Lean-Agile Development Tools
Chapter 12: Human-Centered Design Tools
Chapter 13: Data Instrumentation Tools
Chapter 14: Software and Technology Standards as Tools
Chapter 15: Tools for Learner Motivation
Chapter 16: Implementation Tools
Chapter 17: Ethical Decision-Making Tools
Chapter 18: Data Analysis Tools
Vision and Commentary
Chapter 19: The Future World with Learning Engineering: A Story
Authors
About the Authors