e-Article
Predicting Students' Performance in an Online Testing Environment Using Eye-movement Behavior and Cognitive Styles
Document Type
Conference
Author
Source
2023 International Conference on Artificial Intelligence and Education (ICAIE) ICAIE Artificial Intelligence and Education (ICAIE), 2023 International Conference on. :72-74 Mar, 2023
Subject
Language
Abstract
In order to provide personalized tutoring, quantifying the online testing process and understanding the cognitive process have attracted much attention. This study used students' cognitive style and eye movement data which collected in an online testing environment to predict their performance using C5.0 decision tree algorithm. The results indicate that it is practical and the predictive accuracy overs 87%. This study highlights the importance of eye movement data as physiological information in the field of education, to provide insights of personalized education evaluation and tutoring.