Abstract
The capability of recognizing the „human factor” considerably improves the Human-Computer-Interaction process and the impact of learning as well. High efficiency of a learner psychophysiological model based e-Learning systems is achieved due to adaptation ability to learners’ real-time emotional behavior during training session. In the paper an approach for building adaptive Learning systems with a model of learner’s psychophysiological state is discussed. 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. Idea of “dual adaptation” is presented. Case study of the conducted by author research experiments is presented.
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Rikure, T., Novickis, L. (2010). Building a Learner Psychophysiological Model Based Adaptive e-Learning System: A General Framework and Its Implementation. In: Grundspenkis, J., Kirikova, M., Manolopoulos, Y., Novickis, L. (eds) Advances in Databases and Information Systems. ADBIS 2009. Lecture Notes in Computer Science, vol 5968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12082-4_5
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DOI: https://doi.org/10.1007/978-3-642-12082-4_5
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