From Learning Management System to Affective Tutoring system: a preliminary study

TL;DR

This study explores combining performance, behavioral, and emotional indicators from LMS data and webcam images to identify students facing difficulties, highlighting the importance of emotions in academic success.

Contribution

It introduces a preliminary approach integrating digital traces and emotional analysis to enhance student support systems in educational settings.

Findings

Positive emotions correlate with better academic outcomes

Emotional engagement can differentiate high and low achievers

Data from LMS and webcams provide valuable insights

Abstract

In this study, we investigate the combination of indicators, including performance, behavioral engagement, and emotional engagement, to identify students experiencing difficulties. We analyzed data from two primary sources: digital traces extracted from th e Learning Management System (LMS) and images captured by students' webcams. The digital traces provided insights into students' interactions with the educational content, while the images were utilized to analyze their emotional expressions during learnin g activities. By utilizing real data collected from students at a French engineering school, recorded during the 2022 2023 academic year, we observed a correlation between positive emotional states and improved academic outcomes. These preliminary findings support the notion that emotions play a crucial role in differentiating between high achieving and low achieving students.