JUCS - Journal of Universal Computer Science 19(11): 1638-1660, doi: 10.3217/jucs-019-11-1638
A Dual-Modal System that Evaluates User's Emotions in Virtual Learning Environments and Responds Affectively
Michalis Feidakis‡, Thanasis Daradoumis‡, Santi Caballe§, Jordi Conesa§, David Gañán§‡ University of Aegean, Mytilini, Greece§ Open University of Catalonia, Barcelona, Spain
Corresponding author: Michalis Feidakis ( mfeidakis@aegean.gr ) © Michalis Feidakis, Thanasis Daradoumis, Santi Caballe, Jordi Conesa, David Gañán. This article is freely available under the J.UCS Open Content License. Citation:
Feidakis M, Daradoumis T, Caballe S, Conesa J, Gañán D (2013) A Dual-Modal System that Evaluates User's Emotions in Virtual Learning Environments and Responds Affectively. JUCS - Journal of Universal Computer Science 19(11): 1638-1660. https://doi.org/10.3217/jucs-019-11-1638 |  |
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
emotion, mood, Affect, emotion Awareness, recognition, reporting, Measurement, detection, affective Computing, feedback, sentiment Analysis, opinion Mining, collaborative Learning, CSCL