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Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007)
Using machine learning to predict learner emotional state from brainwaves
Niigata, Japan
July 18-July 20
ISBN: 0-7695-2916-X
Alicia Heraz, University of Montreal, Canada
Ryad Razaki, University of Montreal, Canada
Claude Frasson, University of Montreal, Canada
Intelligent Tutoring Systems (ITS) learner model has progressively evolved. Initially composed of a cognitive module it was extended with a psychological module and an emotional module. The learner model still remains non-exhaustive. Methods of data collection on the cognitive and emotional state of the learner often lack precision and objectivity. In this paper we introduce an emomental agent. It interacts with an ITS to communicate the emotional state of the learner based upon his mental state. The mental state is obtained from the learner's brainwaves. The agent learns to predict the learner?s emotions by using machine learning techniques.
Citation:
Alicia Heraz, Ryad Razaki, Claude Frasson, "Using machine learning to predict learner emotional state from brainwaves," icalt, pp.853-857, Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007), 2007
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