Handbook of Augmented Reality Training Design Principles

by Laura G. Militello, Christen E. Sushereba, Sowmya Ramachandran

Overview

The Handbook of Augmented Reality Training Design Principles is for anyone interested in using augmented reality and other forms of simulation to design better training. It includes eleven design principles aimed at training recognition skills for combat medics, emergency department physicians, military helicopter pilots, and others who must rapidly assess a situation to determine actions. Chapters on engagement, creating scenario-based training, fidelity and realism, building mental models, and scaffolding and reflection use real-world examples and theoretical links to present approaches for incorporating augmented reality training in effective ways. The Learn, Experience, Reflect framework is offered as a guide to applying these principles to training design. This handbook is a useful resource for innovative design training that leverages the strengths of augmented reality to create an engaging and productive learning experience.

Product Details

ISBN-13:	9781009216159
Publisher:	Cambridge University Press
Publication date:	06/01/2023
Pages:	190
Product dimensions:	5.98(w) x 8.98(h) x 0.35(d)

About the Author

Laura G. Militello is a co-founder of Unveil LLC, a startup company that delivers augmented reality-based recognition skills training to combat medics, emergency responders, and others. She co-authored Perspectives on Cognitive Task Analysis (2008) and she co-hosts the Naturalistic Decision Making podcast. Her work supports people who make tough decisions in challenging situations.

Christen E. Sushereba received her M. S. in Human Factors and Industrial/Organizational Psychology from Wright State University in Dayton, Ohio, USA in 2018. She has spent the first decade of her career applying cognitive engineering and human factors methods to a variety of domains including military pararescue, emergency medicine, aviation, and human-automation teaming.

Sowmya Ramachandran received her Ph.D. in Computer Science from The University of Texas at Austin, USA in 1998. She has two decades of experience in designing rich, interactive, personalized learning experiences for professional training, and is excited about the use of artificial intelligence to enhance training and education.

Table of Contents

1. Introduction; 2. Engagement; 3. Scenario Building; 4. Fidelity and Realism; 5. Supporting Mental Model Construction; 6. Scaffolding and Reflection; 7. Synthesis; 8. Conclusion; References; Index.

Editorial Reviews

‘This handbook lays out the foundations of skilled decision making and cognitive performance, focusing on recognition skills as fundamental. Designing training for developing and improving cognitive performance has been a hidden practice offered by only a very few pioneering researchers and practitioners until now. This book opens the lid on how to do this effectively based on both cutting-edge theory and models in cognitive performance, as well as an understanding of the technology offering. Every technology company investing money into developing these technology-driven mixed-reality training systems should be reading this to ensure relevance, utility, usability, and adoption to their training organisation customers.’ Rob Hutton, University of the West of England, UK

‘Augmented reality applications are unlikely to have an impact without guidelines for putting the technology into practice, and that’s what this book delivers. It is clearly written, with a number of good examples. This book’s implications extend beyond augmented reality - implications for anyone wanting to improve training programs.’ Gary Klein, Cognitive Psychologist and CEO of ShadowBox LLC

‘Finally! A gem of a handbook on how to design virtual learning experiences. Building on the science of learning, this handbook offers practical guidance to create training that makes a difference and works. A must source for scientists, instructional designers, practitioners, and for all who engineer technology-based learning environments.’ Eduardo Salas, Rice University, USA

From the Publisher