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  • 标题:Comparing Student Model Accuracy with Bayesian Network and Fuzzy Logic in Predicting Student Knowledge Level
  • 本地全文:下载
  • 作者:Muhammad Danaparamita ; Ford Lumban Gaol
  • 期刊名称:International Journal of Multimedia and Ubiquitous Engineering
  • 印刷版ISSN:1975-0080
  • 出版年度:2014
  • 卷号:9
  • 期号:4
  • 页码:109-120
  • DOI:10.14257/ijmue.2014.9.4.12
  • 出版社:SERSC
  • 摘要:The use of computer has widely used as a tool to help student in learning, one of the computer application to help student in learning is in the form of Intelligent Tutoring System. Intelligent Tutoring System used to diagnose student knowledge state and provide adaptive assistance to student. However, diagnosing student knowledge level is a difficult task due to rife with uncertainty. Student Model is the key component in Intelligent Tutoring System to deal with uncertainty. Bayesian Network and Fuzzy Logic is the most widely used to develop student model. In this paper we will compare the accuracy of student model developed with Bayesian Network and Fuzzy Logic in predicting student knowledge level.
  • 关键词:Student Model; Intelligent Tutoring System; Fuzzy Logic; Bayesian Network
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