Michalis Feidakis

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Affective or Emotion oriented computing constitutes an emerging research field that is still in its early stages. The lack of empirical results together with the complexity that attributes emotions, subjects research to a diversity of theories, models and tools. In the current paper we present a critical review of the state of the art on emotion measurement(More)
Many researchers argue that students must be meaningfully engaged in the learning resources for effective learning to occur. However, current online learners still report a problematic lack of attractive and challenging learning resources that engage them in the learning process. This endemic problem is even more evident in online collaborative learning(More)
The consideration of emotion in learning has been in the research agenda for quite long time and literature is offering a variety of studies that are evaluating the role of emotions in various learning contexts (class, test and exams, during studying at home, etc). In the current paper we first appose a critical review of prominent emotion taxonomies,(More)
The adoption of emotion awareness features in learning environments, has been put on the focus of the research agenda towards students' engagement and their authentic social interaction. In the current paper we provide a solution towards the provision of e-learning with emotion awareness features, which is based on self-reporting of emotions and affective(More)
This paper describes a system's implementation that evaluates the learner's affective state and based on computer intelligence, responds affectively. Prominent theories and models of emotions are reviewed and analysed, especially in respect to learning, together with emotion recognition technologies. Finally, we set open issues for future experimentation,(More)
This work presents a position paper that first reviews in depth the state of the art in Collaborative Learning Systems design with respect to emotion and then proposes a new conceptual framework that takes into account a five layer approach that considers physiological, emotional, sociological, technological and educational aspects in relation to learning.(More)
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,(More)
The enrichment of Computer Supported Collaborative (CSCL) Systems with emotion awareness features (detect emotion patterns and respond effectively) opens a window to the future of learner-to-computer interaction. In the current paper we present a system's design that attempts to evaluate the learner's affective state while he/she is taking part into(More)