Facial Expression Analysis in Computer-Assisted Learning Environments During Reading and Problem-Solving Processes

Abstract

This study aims to analyze students’ facial expressions during reading and problem-solving tasks in a computer-assisted learning environment, focusing on their relationship with gender, academic performance, and time. Due to its exploratory nature, the research was conducted using a single-group post-test design. The study group consisted of 40 university students (23 female and 17 male). Participants were asked to read a scientific text and then solve a multiple-choice test. During the task, students’ facial expressions were recorded through the computer’s webcam and analyzed in real-time by a facial expression recognition algorithm measuring valence, arousal, and intensity. The collected data were analyzed using t-tests and regression analysis. Female students exhibited lower valence and higher intensity in their facial expressions compared to male students. No significant relationship was found between facial expressions and academic performance or reading duration. However, valence levels were observed to decrease as problem-solving time increased. These findings contribute to the literature on emotional state analysis in educational settings.