2026 ASEE Annual Conference & Exposition

WIP: Studying Quantitative Cognitive and Performance Metrics in AR/VR Training for Manufacturing – Toward a Load-Optimized Immersive Design Framework

Presented at Engineering Design Graphics Division (EDGD) Technical Session 3

This work in progress describes a study aimed at improving AR/VR-based training in manufacturing through cognitive load optimization. The objective is to enhance task performance, retention, and training effectiveness by applying Cognitive Load Theory (CLT) to immersive interface design.
The relevance to engineering graphics lies in the development of intuitive, adaptive visual interfaces that reduce extraneous cognitive load. Poorly designed overlays and navigation structures in immersive environments can hinder comprehension and increase error rates. This study explores how design choices in AR/VR graphics affect user cognition and performance.
Training modules are developed in Unity and deployed on Meta Quest 3 (VR) and HoloLens (AR). Interface variables include overlay complexity, feedback modality (visual vs. visual/audio), navigation structure, and adaptivity. Participants with varying manufacturing experience are randomly assigned to different conditions. Data collection includes NASA-TLX scores (subjective load), eye-tracking and pupillometry (physiological load), and performance metrics (completion time, accuracy, error rate, retention). Statistical analyses involve ANOVA, regression, and correlation tests.
Preliminary results suggest that simplified and adaptive interfaces reduce cognitive load and improve performance. Multimodal feedback and personalized training sequences show promise in enhancing training efficiency and retention without compromising safety.
Future work will examine long-term retention, integration with live dashboards, and automated content generation. The ultimate goal is to deliver scalable, evidence-based AR/VR solutions that accelerate onboarding, improve operational safety, and support workforce development in manufacturing.

Authors

Alexander Jarrett Martin North Carolina A&T State University
Dr. Nelson A. Granda http://orcid.org/https://0009-0003-4582-2155 North Carolina Agricultural and Technical State University (CoST) [biography]

Nelson A. Granda Marulanda is an Assistant Professor in the Applied Engineering Technology department at the North Carolina Agricultural & Technical State University. Nelson has a BS in Electrical Engineering from the University of Puerto Rico at Mayaguez, a Masters in Manufacturing Engineering from the Polytechnic University of Puerto Rico, and a Ph.D. in Industrial and Systems Engineering from The University of Tennessee Knoxville. Before becoming a professor, he worked for several years in the Eolic and Aerospace industry. Nelson’s research interest revolved around Sustainable Development through the triple bottom line and System Thinking approach. Nelson believes that education is the key to achieving a sustainable world.
Joao Paulo Jacomini Prioli http://orcid.org/0000-0001-5756-8455 North Carolina Agricultural and Technical State University [biography]

Dr. Joao Prioli is an Assistant Professor at North Carolina A&T State University. He received his Ph.D. and M.S. in Industrial and Systems Engineering from Wayne State University and holds a B.S. in Electrical Engineering from the University of Uberlândia. His research focuses on advancing automation solutions to support the circular economy, with a particular emphasis on smart manufacturing, CAD-based disassembly, and human-robot collaboration. His work explores data-driven modeling and automated disassembly processes to enable sustainable production and resource recovery.
Dr. James David Kribs http://orcid.org/0000-0002-2493-2588 North Carolina A&T State University (CoE) [biography]

My research aims to understand the concepts and mechanisms of lifted jet combustion, electrohydrodynamics, aerodynamics, composite structures, and engineering education . I use advanced techniques and technologies to explore these topics. My students and

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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