北京邮电大学学报(社会科学版) ›› 2011, Vol. 13 ›› Issue (1): 104-109.

• 教育研究 • 上一篇    下一篇

基于Kmeans聚类算法的远程学习者效果分析

  

  1. 北京邮电大学 网络教育学院,北京100088
  • 收稿日期:2010-12-15 出版日期:2011-02-28 发布日期:2011-02-28

Effect Analysis of Distance Learners’ Action Based on Kmeans Clustering Algorithm

  1. School of Network Education,Beijing University of Posts and Telecommunications, Beijing 100088,China
  • Received:2010-12-15 Online:2011-02-28 Published:2011-02-28

摘要:

网络技术的迅速发展为远程教育中个性化学习提供了可能。首先使用Kmeans算法对学生的属性数据和相应课程的成绩进行了聚类数据挖掘,发现学习者群体的特点。然后,结合聚类结果的特性和差异,为课程资源建设及教学过程的改进提供帮助。

关键词: Kmeans算法;个性化教学, 远程学习, 远程教育

Abstract:

The rapid development of network technology in distance education makes it possible for personalized learningIn this paper, we use the Kmeans algorithm to cluster students based on attribute data and the corresponding student’s course achievement for data mining and find the characteristics of the learner groupsThen, the characteristics and differences of the clustering results can provide guidance for curriculum resources establishment and teaching process improvement

Key words: Kmeans algorithm, personalized teaching, distance learning, distance education

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