MRI: RUI: Acquisition of Eye Tracking Equipment to Support Research at UAA

University Of Alaska Anchorage Campus, Anchorage AK

Investigators

Abstract

Proposal #: 11-26896 PI(s): Hoanca, Bogdan; Mock, Kenrick Institution: University of Alaska at Anchorage Title: MRI: RUI: Acquisition of Eye Tracking Equipment to Support Research at UAA Project Proposed: This project, acquiring two eye tracking systems, (along with wireless sensors for creating a biometric profile for a computer user), enables new and innovative research directions in user authentication, assistive software for teaching mathematics, context aware document retrieval, and student attentiveness. These new, state-of-the-art eye trackers will replace two lower quality eye trackers, freeing one up for student use. The eye trackers will be located in a controlled-access, public use laboratory available to several researchers at the University of Alaska at Anchorage. The enhanced capabilities of the new eye trackers will permit greater range of motion for more natural user interaction and higher accuracy for better biometrics. Consequently, the work will permit transformational research into more natural and transparent user authentication and computer security based on a comprehensive set of biomarkers, assistive research into mathematical learning techniques for persons with disabilities, enhanced, biomarker-based intelligent search and document categorization through online user profiling, and enhanced assessment of learning efficacy. Aside from brain activity, eye patterns are one of the most direct windows into a person?s understanding and mental activity. Broader Impacts: The broader impacts include the involvement of 4-6 undergraduate students per year in eye tracking research by the co-PIs, with possibly another 4-6 undergraduates per year from other faculty. Four broader impacts are apparent. First, if widely deployed, the proposed authentication scheme has the potential to thwart phishing attacks, and even man in the middle attacks, for e-commerce users. Second, advanced assistive technology for mathematics will allow physically disabled people to perform math manipulations on par with able-bodied people. Third, by tracking what a user actually reads, user profiling will result in better, faster searches for relevant information automatically. Finally, high quality eye tracking should provide the UAA faculty with insight into the direct connections between learning and eye patterns