Engagement estimation based on synchrony of head movements: application to actual e-learning scenarios

Ryosuke Kawamura, Yuushi Toyoda, Koichiro Niinuma

Abstract: In video-based learning, engagement estimation is important for increasing learning efficiency. Changes to the appearances of learners (facial expression or posture such as closing eyes, looking away) obtained by a Web camera are often used to estimate engagement due to the ease of installing the camera. In this work, firstly we collected data in an actual e-learning scenario at a Japanese cram school and found that the appearances of each learner hardly changed. Secondly, we propose an engagement estimation method based on synchrony of head movements, which occur frequently when students take notes. An analysis of our method using collected data revealed an F-score of 0.79, which is higher than the methods based on changes of appearance. This result indicates that our method has possibility to be more effective for engagement estimation in actual learning scenarios.