Customized, Optimized Adaptive Coaching Hub for Immersive Environments (COACH Immersive)

Immersive learning and adaptive training represent a progressive approach to classroom education, aiming to create an engaging and effective, personalized learning experience.  While these methods are promising, they are not without challenges.  Developers of immersive training systems may lack the specialized knowledge necessary to understand how people learn and process information, as well as how to tailor and adapt training effectively.  Additionally, there’s a tendency to prioritize use of cutting-edge technologies and eye-catching features with Virtual and Augmented Reality (VR/AR).  These issues can lead to training systems that are not only less effective but may also be distracting or confusing, potentially hindering the learning process rather than facilitating it. To address these challenges, ARO Corp and Dr Richard Mayer, University of California, Santa Barbara (UCSB), propose to apply extensive research on multimedia learning to design a methodology – a two-step technical approach – that addresses key aspects of instructional design.  This approach seeks to optimize learning in VR/AR environments and apply a reliable, adaptive training capability to account for the distinct characteristics and actions of the student, training content, and environment. As an instructional method, this versatile framework can be integrated into a variety of immersive classroom environments.  To demonstrate its potential, in Phase 1, we will design an approach using our knowledge of a Navy relevant use case: the Visual Identification Virtual Reality (VIDVR) navigation training system.The purpose of adaptive training is to attune to the unique needs of individual learners and foster the application of knowledge to the real-world.  Our proposal addresses this requirement by first refining the core instructional design of an immersive system based on research-backed principles, then iteratively building a comprehensive profile of trainee characteristics and performance. This profile, in conjunction with instructor-tailored rulesets, enables the automatic customization of training and instruction to better suit individual needs.