11. Integrating Eye-Tracking into Education: A Case Study in Student Presentations

Conference: Women in Statistics and Data Science 2025
11/13/2025: 11:45 AM - 1:15 PM EST
Speed 

Description

Eye-tracking technologies have become increasingly valuable in educational research, offering insight into students' attention, cognitive processing, and behavioral patterns. This poster presents a practical overview of how eye-tracking can be integrated into educational settings, with attention to workflow design, implementation challenges, and analytical
strategies. We illustrate this approach through a case study in a university-level presentation course. During students' final presentations, we recorded their eye movements using wearable eye-tracking glasses. This data is being analyzed alongside personality profiles (Big Five
Inventory) and academic performance indicators, including instructor-assigned presentation scores and students' self-reported sense of success. Our study focuses on key gaze metrics, such as fixation duration and visual attention patterns, to explore how individual differences may shape communication style and presentation outcomes. We also gathered student reflections on their experience with the technology such as how comfortable they felt, whether it affected their confidence or performance, and their willingness to use such tools again. This poster outlines the research process from equipment setup and calibration to ethical protocols, consent, and data preprocessing. We highlight strategies for interpreting gaze-based indicators and share insights into maintaining ecological validity while ensuring methodological control. Finally, we reflect on how eye-tracking data can complement qualitative and self-reported measures to provide a more nuanced understanding of student behavior. Our goal is to offer a practical framework for researchers and educators interested in using eye-tracking to support pedagogical innovation and educational insight.

Keywords

Education

Eye-tracking

Big 5 personality

Eye-mind hypothesis 

Presenting Author

Samyukta Vakkalanka, Georgetown University

First Author

Samyukta Vakkalanka, Georgetown University

Target Audience

Beginner

Tracks

Knowledge
Women in Statistics and Data Science 2025