XR Training & Education

Overview

We have been looking at computer science education, wind and fluids engineering, and US Navy training systems to improve learning. We have used different approaches, including cognitive load theory.

One example of how we conduct research is through controlled training studies, where we measure the outcomes. For the Office of Naval Research, we followed people from initial training into task performance in virtual reality, manipulating workload to see how cognitive engagement carries from one to the other. More recently, in a paper accepted to IEEE ISMAR 2026, we used a wind-simulation environment built for engineering education — where moving a building changes the simulated airflow around it — to study how people naturally interact with these learning environments in both augmented and virtual reality.

Our work has shown how to measure training using traditional human-factors metrics and psychophysiological measures (EEG and fNIRS), and what those measures mean for training. One of the most powerful messages, found in one of our soon-to-be-published papers, is that self-assessment questionnaires such as NASA-TLX, while useful in many cases, miss important information about learning that fNIRS does not.