Affective computing
"How do you know that I don't understand?" A look at the future of intelligent tutoring systems
Computers in Human Behavior
ADBIS'09 Proceedings of the 13th East European conference on Advances in Databases and Information Systems
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User's psychophysiological state model allows taking into account learner's emotional and physiological states during technology-based learning. The capability of recognizing the "human factor" considerably improves the Human-Computer-Interaction process and the impact of learning as well. High efficiency of such e-learning systems is achieved due to adaptation ability to learners' real-time behavior during training session. This paper proposes an approach of modeling user's psychophysiological state in adaptive e-learning systems. Biofeedback sensors are used to get real-time data about user's psychophysiological state during training sessions. The research results on measuring and analyzing user's psychophysiological responses from biofeedback sensors are described.