Assessment of the Emotional States of Students during e-Learning

Emotions are assumed to have a great impact on our behaviour and also on our learning behaviour. In a face-to-face learning environment emotions can be expressed by (non-)verbal behaviour as way of speaking, facial expressions or words with an emotional loadings. In this paper we research the possibility to assess the emotional state of learners by analysis of nonverbal behaviour as speech analysis and analysis of facial expressions. We developed tools to extract features from sound and video recordings and used classifiers as SVM to label emotional states. We used discrete emotional states but also the well-known 2D valence and arousal score as a continuous score of the emotional state. From our experiments it proves that students show overt emotions under special conditions with strong emotional triggers. Our system was able to assess strong emotions up to some level.