CAREER: Developing a Human-Centered Theoretical Framework for Augmented Reality Interfaces

Augmented reality (AR) overlays digital information onto the real world, and its use in workplaces, healthcare, and daily life is growing rapidly. Despite this, few guidelines exist for how AR should be designed or how people learn to use it safely and effectively. Without clear design standards, AR systems risk confusing or endangering users, particularly in high-stakes environments like hospitals or industrial settings. This project addresses that gap by partnering with public libraries to offer free, hands-on AR experiences for community members, particularly those with little prior exposure to technology. The project will broaden public access to emerging technology and train the next generation of researchers to engage meaningfully with diverse communities. This project develops a validated design framework for AR displays by synthesizing knowledge from industry, academia, and policy. Data collected from a broad and diverse user population will ensure the framework is generalizable across contexts. The project also establishes the theoretical foundation needed for AR systems to adapt to individual user needs in real time, with the goal of improving safety and usability in complex environments. This framework will serve as a resource to guide future human-centered AR research and development. This project advances NSF’s mission by building the scientific foundation needed to make emerging technologies safer and more accessible for all Americans. 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. NSF Award ID: 2543412 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Martha Smith | Institution: Auburn University, AUBURN, AL | Award Amount: $482,441 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2543412 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2543412.html