The question
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.
How we work
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.
What this work enables
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.
Papers in this area 21
Conference Papers 4
- Investigating Cognitive Engagement from Training to Application Under Varied Workload Manipulations in Virtual Reality (opens in new tab) 2025
- Comparing Instruction Methods for DailyBuddy: A Mobile App for Improving Daily Living Skills for Adults with Autism (opens in new tab) 2025
- Eye-Hand Coordination Training: A Systematic Comparison of 2D, VR, and AR Display Technologies and Task Instructions 2024
- Emergent Individual Factors for AR Education and Training (opens in new tab) 2023
Workshop Articles 6
- Experiencing Gravitational Red-Shifting in Virtual Reality (opens in new tab) 2024
- Exploring Factors Associated with Retention in Computer Science Using Virtual Reality (opens in new tab) 2022
- Exploring the Impact of Belonging on Computer Science Enrollment Using Virtual Reality (opens in new tab) 2020
- CubeVR: Digital Affordances for Architecture Undergraduate Education using Virtual Reality In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces, Workshop on K-12 Embodied Learning through Virtual & Augmented Reality (KELVAR) (opens in new tab) 2019
- Towards a 3D Virtual Programming Language to Increase the Number of Women in Computer Science Education (opens in new tab) 2017
- Smart Learning Desk: Towards an Interactive Classroom 2016
Posters & Late-Breaking 3
- HoloNote: Exploring Augmented Reality Notifications for Ergonomic Feedback in Laparoscopic Training (opens in new tab) 2026
- A Virtual Reality System for Gender Swapping to Increase Empathy against Stereotype Threats in Computer Science Job Interviews (opens in new tab) 2023
- Integrating Building Information Modeling with Augmented Reality for Interdisciplinary Learning (opens in new tab) 2016
Invited Papers 3
- 3D Interaction for Computer Science Educational VR Game (opens in new tab) 2019
- 3D Spatial Gaming Interaction to Broad CS Participation (opens in new tab) 2018
- Use of 3D Human-Computer Interaction for Teaching in the Architectural, Engineering and Construction Fields 2018
Other Referred Papers 1
- Vertically Integrated Projects (VIP) Programs: Multidisciplinary Projects with Homes in Any Discipline In ASEE Annual Conference & Exposition, Columbus, Ohio 2017
Pre-Prints 3
- Leveraging fNIRS to Evaluate Workload for Adaptive Training in Virtual Reality (opens in new tab) 2026
- The Impact of Simple, Brief, and Adaptive Instructions within Virtual Reality Training: Components of Cognitive Load Theory in an Assembly Task (opens in new tab) 2025
- Multimedia and immersive training materials influence impressions of learning but not learning outcomes (opens in new tab) 2024