Inducing optimal emotional state for learning in intelligent tutoring systems

Abstract

Emotions play an important role in cognitive processes and specially in learning tasks. Moreover, there are some evidences that the emotional state of the learner correlated with his performance. Furthermore, it's important that new Intelligent Tutoring Systems involve this emotional aspect; they may be able to recognize the emotional state of the learner, and to change it so as to be in the best conditions for learning. In this paper we describe such an architecture developed in order to determine the optimal emotional state for learning and to induce it. Based on experimentation, we have used the Naive Bayes classifier to predict the optimal emotional state according to the personality and then we induce it using a hybrid technique which combines the guided imagery technique, music and images. © Springer-Verlag 2004 References.