On predicting learning styles in conversational intelligent tutoring systems using fuzzy decision trees
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- 作者：Keeley Crocketta ; K.Crockett@mmu.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Annabel Lathama ; A.Latham@mmu.ac.uk" class="auth_mail" title="E-mail the corresponding author ; Nicola Whittonb ; N.Whitton@mmu.ac.uk" class="auth_mail" title="E-mail the corresponding author
- 关键词：Intelligent tutoring systems ; Conversational agents ; Architectures for educational technology system ; Fuzzy decision trees
- 刊名：International Journal of Human - Computer Studies
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：97
- 期：Complete
- 页码：98-115
- 全文大小：1346 K
文摘
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An enhanced Fuzzy Learning Styles Predictor module is proposed.
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Fuzzy decision trees are used to automatically predict individual learning style.
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Modelling behaviour of learners during tutorials increases the predictive accuracy.
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Transparent set of rules allow clear identification of leaner behaviour.
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Better prediction of learning styles leads to improved adaptation.