Augmented Reality Adaptive Training Principles

Abstract

As augmented reality (AR) technology offers enhanced capabilities for medical simulation training, research is required to understand how to best leverage the strengths of AR. We describe a literature review that will provide the foundation for articulating and testing candidate principles for AR adaptive training design. Our goal is to articulate and test design principles for designing recognition skills training as described in the recognition-primed decision model (Klein, 1997). We identified seminal articles from the the Naturalistic Decision Making literature, and used those to seed a systematic review of the medical education and combat medic training literatures. Findings from the literature review suggest three categories of candidate design principles: 1) fidelity and realism, 2) engagement, and 3) scaffolding. Next steps will include articulating specific design principles and designing a series of studies to test them using the VPIT AR training platform.