Pupil Diameter Reveals Elementary Students' Cognitive Load Manifestation in Physiological Computing (Poster 7)

• In Event: AERA Poster Session Wednesday 4:20 p.m.
  In Poster Session: Technology, Instruction, Cognition, and Learning (TICL) Poster Session

Abstract

Eye-tracking metrics, specifically pupil diameter, have become helpful in educational research for inferring cognitive load, attention, and learning behavior. This mixed-method study examines the manifestation of students' cognitive load while independently solving a programming task, focusing on eye-tracking metrics based on pupil diameter, programming score, and qualitative video analysis. Data was collected using Tobii Spark, a screen-based eye-tracker, and analyzed with Tobii Pro Lab software. Qualitative video analysis of three students' problem-solving processes and their average pupil diameter during problem-solving supported the assumption that when a student appeared to have struggled with the programming task, they had a higher cognitive load, thus leading to a higher average pupil diameter, and vice versa.

Authors

• Fatema Nasrin, University of Alabama

• Idowu David Awoyemi, University of Alabama

• Feiya Luo, University of Alabama

• Ruohan Liu, Seattle University

• Chris S. Crawford, University of Alabama