學術產出-專書/專書篇章

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 Using Bayesian networks for student modeling
作者 劉昭麟
Liu, Chao-Lin
貢獻者 資科系
日期 2008-05
上傳時間 6-二月-2023 14:32:04 (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.
關聯 Agent-Based Tutoring Systems by Cognitive and Affective Modeling, (a reprinted chapter from the 2006 IGI book), Idea Group Inc., pp.97-113
資料類型 book/chapter
DOI http://dx.doi.org/10.4018/978-1-59904-768-3.ch005
dc.contributor 資科系
dc.creator (作者) 劉昭麟
dc.creator (作者) Liu, Chao-Lin
dc.date (日期) 2008-05
dc.date.accessioned 6-二月-2023 14:32:04 (UTC+8)-
dc.date.available 6-二月-2023 14:32:04 (UTC+8)-
dc.date.issued (上傳時間) 6-二月-2023 14:32:04 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/143317-
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.
dc.format.extent 113 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Agent-Based Tutoring Systems by Cognitive and Affective Modeling, (a reprinted chapter from the 2006 IGI book), Idea Group Inc., pp.97-113
dc.title (題名) Using Bayesian networks for student modeling
dc.type (資料類型) book/chapter
dc.identifier.doi (DOI) 10.4018/978-1-59904-768-3.ch005
dc.doi.uri (DOI) http://dx.doi.org/10.4018/978-1-59904-768-3.ch005