Application of Data Mining in Higher Education System

机译：数据挖掘在高等教育系统中的应用

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Students' performance in university courses is of great concern to the higher education management where several factors may affect their performance. This paper addresses the capabilities of data mining and its application in higher education by offering a data mining model to learn the main attributes that may affect students' performance in courses. During the mining process, the CRISP framework and classification method for data mining is used for mining students' related academic data over the previous year. The findings can be used to understand students' learning, and then help teachers with managing their class.

机译：学生在大学课程中的表现是高等教育管理部门非常关注的问题，其中几个因素可能会影响他们的表现。本文通过提供数据挖掘模型来学习可能影响学生在课程中表现的主要属性，从而解决数据挖掘的功能及其在高等教育中的应用。在挖掘过程中，使用CRISP数据挖掘框架和分类方法来挖掘上一年学生的相关学术数据。调查结果可用于了解学生的学习情况，然后帮助教师管理班级。

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来源
《International Forum of Knowledge as a Service(2010知识服务国际论坛）》|2010年|p.203-206|共4页
会议地点 Xiamen(CN)
作者
Xiaoying Huang; Yafen Li; Pu Wang;
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作者单位

College of Electronic Information and Control Engineering Beijing University of Technology Chaoyang District, Beijing, China;

College of Electronic Information and Control Engineering Beijing University of Technology Chaoyang District, Beijing, China;

College of Electronic Information and Control Engineering Beijing University of Technology Chaoyang District, Beijing, China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Students' performance; Higher education; Data Mining; CRISP; Classification;

机译：学生表现;高等教育;数据挖掘; CRISP;分类;

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Application of Data Mining in Higher Education System

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