Empowering Adaptive Learning in VR Assembly Training Using Real-time Performance Tracking

Abstract

Virtual Reality (VR) provides unique opportunities for creating immersive, per-sonalized and responsive learning environments through advanced features like hand and eye tracking. However, traditional VR training often lacks the flexibility to accommodate diverse learning styles. Personalization of training is crucial in industrial assembly, where user profiles and levels of expertise vary greatly. This paper introduces a novel solution for adaptive learning in VR focused on assembly knowledge training, using hand and eye tracking to deliver real-time feedback and individually adjusted learning paths. We applied our approach to two realistic assembly cases to evaluate its practical application. We hope to inspire future research further to explore and refine this adaptive approach, contributing to developing more flexible and effective VR-based training solutions for the manufacturing industry.