Emotions Recognition Agent for On-Line Learning Systems

Claude Frasson and Soumaya Chaffar, University of Montreal; Mohammed A. Razek, Al-Azhar University; Magalie Ochs, University of Montreal

The effectiveness of intelligent tutoring systems, for instance on-line learning systems, can be improved when the learner’s emotions are taken into account. A necessary condition for this is how the system recognizes the learner’s current emotional state. Traditional methods for doing this are based on measuring physical parameters, most typically the facial expression or muscle tension; however, they are neither comfortable for the user nor useful in a distributed environment such as the Internet. Furthermore, filling out a long questionnaire is a time-consuming task. In contrast, we present an extremely simple method that can be used instead, the Emotion Recognition Agent (ERA), which exploits the natural relation between emotions and colors. We have performed experiments demonstrating both the simplicity and the accuracy of our ERA method which employs machine learning techniques for determining a user’s emotion given colors sequence.

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