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Affective Modeling and Recognition of Learning Emotion: Application to E-learning

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Author(s): Yanwen Wu | Tingting Wang | Xiaonian Chu

Journal: Journal of Software
ISSN 1796-217X

Volume: 4;
Issue: 8;
Start page: 859;
Date: 2009;
Original page

Keywords: learning emotion | affective modeling | facial expression recognition | E-learning | emotion incentive

ABSTRACT
     Affective computing has been the focus of artificial intelligence for several years. The amalgamation of affective computing and facial expression recognition technique has lead to the possibility of harmonious human-computer interaction in E-learning. But the fact of E-learning is that emotional absences between computer and E-learner are serious. This paper researches into the learning emotions that E-learner may present. We define three basic learning emotions: absorbed, neuter and fatigue and discuss the features of every defined learning emotion. Layered approach for modeling emotions and facial expression recognition technique are adopted to describe and recognize the defined learning emotions. We also make a demonstrability research, as results indicate, characteristic parameters are exactly identified and face expressions of E-learner are accurately recognized. After E-learner’s emotion state is recognized and confirmed, in the future research, it is possible to take corresponding emotion incentive pleasures of E-learners’ given emotion state to decrease the emotional absences in E-learning.
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