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ICALT
2010
IEEE

Modelling Affect in Learning Environments - Motivation and Methods

11 years 7 months ago
Modelling Affect in Learning Environments - Motivation and Methods
Emotions have a functional relevance to learning and achievement. Not surprisingly then, affective diagnoses are an important aspect of expert human mentoring. Computerbased learning environments aim to model such social dynamics to make learning with computers more immersive, engaging and hence, more effective. This paper draws on the recent surge of interest in studying emotions in learning, highlights available techniques for measuring emotions and surveys recent efforts to automatically measure emotional experience in learning environments. Finally, a contextsensitive dataset is used to develop an automatic system for modeling six pertinent emotions. This paper attempts to bring together the motivation, methodological issues, and modeling approaches for affect inference in learning environments in order to contribute to an understanding of the problem and the current state-of-art. Keywords - Emotion, Affective Computing, Computer-based Learning
Shazia Afzal, Peter Robinson
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where ICALT
Authors Shazia Afzal, Peter Robinson
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