Adaptive Contextual Learning in Microelectronics through Immersive Virtual Reality

Every individual has a unique way of learning. Recent advances in virtual reality (VR) technology—particularly the integration of eye-tracking and motion sensors—now make it possible to create personalized learning experiences by capturing where students look and how they perform tasks in real time. However, most educational VR tools still do not fully account for these individual differences. This project investigates how real-time interaction data in VR can be used to provide adaptive learning, driven by artificial intelligence (AI), to enhance students’ understanding of complex scientific concepts, specifically in the area of semiconductor fabrication. By emphasizing personalized support in semiconductor education, this project aims to enhance STEM learning and strengthen the domestic semiconductor workforce. The overarching aim is to ensure that Americans—regardless of individual ways of learning—can meaningfully engage with emerging technologies. This project investigates how adaptive, AI driven, support in VR environments can enhance students’ understanding of semiconductor fabrication, a complex STEM domain that requires both procedural knowledge (e.g., how to perform a task) and conceptual understanding (e.g., why and how it works). The research examines two key variables: (1) the type of knowledge being constructed—procedural versus conceptual—and (2) individual cognitive capacity, particularly visual-verbal working memory. The central hypothesis is that gaze-based adaptive scaffolding—such as prompts triggered when learners lose focus—can be especially beneficial for students with lower working memory capacity during tasks that require integrating verbal and visual information. Using a quasi-experimental design, the project team develops and evaluates the effectiveness of adaptive VR instructional modules that provide real-time personalized feedback versus non-adaptive VR on learning outcomes such as recall, recognition, and knowledge transfer. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.