Facial coding as a mean to enable continuous monitoring of student's behavior in e-Learning

This paper introduces an e-learning platform for the management courses based on MOOCs, able to continuously monitoring student’s behavior through facial coding techniques, with a low computational effort client-side and provide useful insight for the instructor. The system exploits the most recent developments in Deep Learning and Computer Vision for Affective Computing, in compliance with the European GDPR. Taking as input the video capture by the webcam of the device used to attend the course it: (1) perform continuous students’ authentication based on face recognition, (2) monitor the students’ level of attention through head orientation tracking and gaze detection analysis, (3) estimate emotions student’s emotion during the course attendance. The paper describes the overall system design and reports the results of a preliminary survey, which involved a total of 14 subjects, aimed at investigating user acceptance, in terms of intention to continue using such a system.