Science University Research Symposium (SURS)

An Eye-Tracking Study on the Cognitive Effects of AI Assistance in Academic Reading and Writing Tasks

Publication Date

Fall 2025

College

College of Sciences & Mathematics

Department

Psychological Science, Department of

SURS Faculty Advisor

Lingfei Luan

Presentation Type

Poster Presentation

Abstract

According to a study conducted by the Digital Education Council, 86% of university students use Artificial Intelligence (AI) to assist with their academic work, and one in four university students uses it daily (Campbell Academic Technology Services, 2025). AI has become ingrained in the lives of college students, yet little is known about how it impacts their academic work. The present study aims to understand how AI affects college students' cognitive processes and comprehension.

To complete this study, participants are required to complete a reading and writing assignment while they are connected to a BIOPAC system, used for physiological eye-tracking. Participants are randomly assigned to a control group (reading and writing without AI) or an experimental group (reading and writing with AI). Eye-tracking metrics, including mean fixation duration, total fixation count, and the amount of deviations, are recorded while participants read informational texts.

Data will be analyzed using paired-samples t-tests and inter-rater reliability scoring for the participants’ written work. It is hypothesized that AI assistance will reduce cognitive load, as well as decrease critical-thinking quality in writing. By comparing performance across both conditions, this study aims to reveal whether relying on AI makes academic tasks easier but potentially less engaging. Unlike previous studies that rely on surveys or self-reports, this study uses physiological eye-tracking data to capture cognitive engagement in real-time. This provides a more objective view of how students interact with AI while using it for reading and writing.

As AI continues to evolve, it is important to understand how it affects the way students engage with their work. Understanding AI’s effects on comprehension and engagement is essential in developing teaching practices. Results from this research may help administrators create policies regarding AI usage without compromising the process of authentic learning.

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