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題名 Using Bayesian Networks for Student Modeling
作者 Liu, Chao Lin
劉昭麟
貢獻者 資科系
日期 2006-01
上傳時間 21-七月-2015 16:43:11 (UTC+8)
摘要 This chapter purveys an account of Bayesian networks-related technologies for modeling students in intelligent tutoring systems. Uncertainty exists ubiquitously when we infer students` internal status, for example, learning needs and emotion, from their external behavior, for example, responses to test items and explorative actions. Bayesian networks offer a mathematically sound mechanism for representing and reasoning about students under uncertainty. This chapter consists of five sections, and commences with a brief overview of intelligent tutoring systems, emphasizing the needs for uncertain reasoning. A succinct survey of Bayesian networks for student modeling is provided in Bayesian Networks, and we go through an example of applying Bayesian networks and mutual information to item selection in computerized adaptive testing in Applications to Student Models. We then touch upon influence diagrams and dynamic Bayesian networks for educational applications in More Graphical Models, and wrap up the chapter with an outlook and discussion for this research direction. © 2006, Idea Group Inc.
關聯 Cognitively Informed Systems: Utilizing Practical Approaches to Enrich Information Presentation and Transfer, 283-310
資料類型 book/chapter
DOI http://dx.doi.org/10.4018/978-1-59140-842-0.ch013
dc.contributor 資科系-
dc.creator (作者) Liu, Chao Lin-
dc.creator (作者) 劉昭麟-
dc.date (日期) 2006-01-
dc.date.accessioned 21-七月-2015 16:43:11 (UTC+8)-
dc.date.available 21-七月-2015 16:43:11 (UTC+8)-
dc.date.issued (上傳時間) 21-七月-2015 16:43:11 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76796-
dc.description.abstract (摘要) This chapter purveys an account of Bayesian networks-related technologies for modeling students in intelligent tutoring systems. Uncertainty exists ubiquitously when we infer students` internal status, for example, learning needs and emotion, from their external behavior, for example, responses to test items and explorative actions. Bayesian networks offer a mathematically sound mechanism for representing and reasoning about students under uncertainty. This chapter consists of five sections, and commences with a brief overview of intelligent tutoring systems, emphasizing the needs for uncertain reasoning. A succinct survey of Bayesian networks for student modeling is provided in Bayesian Networks, and we go through an example of applying Bayesian networks and mutual information to item selection in computerized adaptive testing in Applications to Student Models. We then touch upon influence diagrams and dynamic Bayesian networks for educational applications in More Graphical Models, and wrap up the chapter with an outlook and discussion for this research direction. © 2006, Idea Group Inc.-
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Cognitively Informed Systems: Utilizing Practical Approaches to Enrich Information Presentation and Transfer, 283-310-
dc.title (題名) Using Bayesian Networks for Student Modeling-
dc.type (資料類型) book/chapteren
dc.identifier.doi (DOI) 10.4018/978-1-59140-842-0.ch013-
dc.doi.uri (DOI) http://dx.doi.org/10.4018/978-1-59140-842-0.ch013-