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  • 标题:Educational Data Mining for Supporting Students' Courses Selection
  • 本地全文:下载
  • 作者:Thi Yen Tran ; Ba Lam To
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2019
  • 卷号:19
  • 期号:7
  • 页码:106-110
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:At the beginning of each semester, students must choose courses in the course list to study. Many students are confused about choosing the most suitable courses. Some students want to choose courses to improve academic achievement and improve grades. Some other students want to choose courses to avoid being academic warning, academic probation, academic suspension or academic dismissal. Academic advisors and students' knowledge also partly support the selection of courses for students. However, this support depends on the experience of the academic advisor and the students' knowledge. This paper aims to build a model to support students’ courses selection using educational data mining. The proposed model is experimented with educational data from Faculty of Civil Engineering, Ho Chi Minh City University of Transport, Vietnam during the period of 2013-2016. Experimental results bring many positive results for supporting courses selection.
  • 关键词:Educational Data Mining; Apriori; J48; K-Means
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