文章基本信息

标题：A Model of Affect and Learning for Intelligent Tutors
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作者：Yasmín Hernández ; Gustavo Arroyo-Figueroa ; L. Enrique Sucar 等
期刊名称：Journal of Universal Computer Science
印刷版ISSN：0948-6968
出版年度：2015
卷号：21
期号：7
页码：912-934
出版社：Graz University of Technology and Know-Center
摘要：A model of affect and learning for intelligent tutoring systems is proposed. The model considers both how a student feels and what a student knows, and then customizes how instruction is presented and how learning and performance are reinforced. The model was designed based on teachers' expertise, which was obtained through interviews and interaction with an educational game on number factorization learning. The core of the model is a dynamic decision network, which generates tutorial actions balancing affect and knowledge. The student's affect representation relies on a Bayesian network and theoretical models of emotion and personality. A controlled user study to evaluate the impact of the model on learning was performed. Current results are encouraging since they show significant improvement in learning when the model of affect and learning is incorporated.