北京邮电大学学报(社科版) ›› 2018, Vol. 20 ›› Issue (2): 91-96.

• 教育研究 • 上一篇    下一篇

基于改进的聚类和关联规则挖掘的学生成绩分析

  

  1. 北京邮电大学 信息与通信工程学院,北京100876
  • 收稿日期:2018-01-10 出版日期:2018-04-30
  • 基金资助:
    北京邮电大学教学改革项目(2017JY02)

Score Analysis of Undergraduate Students Based on Improved Clustering #br# and Association Rules Mining

  1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications,
    Beijing 100876, China
  • Received:2018-01-10 Online:2018-04-30

摘要: 针对北京邮电大学通信工程专业学生的学习状况分析和培养方案的改进需求,提出一种基于改进的聚类和关联规则挖掘的成绩分析方法,借助数据挖掘手段对学生在校期间的各课程成绩进行相关性分析。以2009—2011级通信工程专业本科生的课程成绩作为样本数据,应用该挖掘方法得到课程之间的关联规则网络,从而分析课程间的衔接关系、判断课程的重要程度以及评价各课程的教学效果。另外,以2011级学生的高考成绩数据作为样本,挖掘高考成绩与大学成绩间的关联规则,分析学生入学前成绩对入学后表现的影响。应用本文所述方法得到的挖掘结果能够为教学方案的设计和改进提供一定参考信息,对提高学生学习质量具有良好作用。

关键词: 成绩分析, 数据挖掘, 聚类, 关联规则

Abstract: In order to analyze the learning quality of undergraduate students in communication engineering major in Beijing University of Posts and Telecommunications (BUPT) and improve the training program, a score analysis method based on improved clustering and association rules mining is presented, and data mining methods are used to analyze the correlation among the students′ performance in different courses Taking the scores of classes of 2009~2011 undergraduates in communication engineering major in BUPT as the sample data, the proposed mining method is used to obtain the network of association rules so as to analyze the connection among courses, to determine the key courses and to evaluate the effectiveness of teaching Meanwhile, taking the National College Entrance Examination (NCEE) scores of class 2011 as a sample, association rules between NCEE scores and university scores are mined in order to analyze students′ performance after the entrance The results can provide some insights for the improvement of teaching methods, which is quite important to improve students′ learning quality

Key words: score analysis, data mining, clustering, association rules

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