A Dual-Modal System that Evaluates User's Emotions in Virtual Learning Environments and Responds Affectively

Michalis Feidakis (University of Aegean, Greece)

Thanasis Daradoumis (University of Aegean, Greece)

Santi Caballe (Open University of Catalonia, Spain)

Jordi Conesa (Open University of Catalonia, Spain)

David Gañán (Open University of Catalonia, Spain)

Abstract: Endowing learning systems with emotion awareness features (capture user's affective state and provide affective feedback), seems quite promising. This paper describes a system implementation that provides emotion awareness, both explicitly, by self-reporting of emotions through a usable web tool, and implicitly, via sentiment analysis. Prominent theories, models and techniques of emotion, emotion learning, emotion detection and affective feedback are reviewed. We also present findings from our experiment with university students, validating the explicit mechanism in real education settings. Finally, we set open issues for future experimentation, contributing to the research agenda.

Keywords: Affect, CSCL, affective Computing, collaborative Learning, detection, emotion, emotion Awareness, feedback, mood, opinion Mining, recognition, reporting, Measurement, sentiment Analysis

Categories: K.3.1, L.1.3, L.1.4, L.2.0, L.3.0, L.3.1, L.3.5, L.3.6, L.6.2