| 基于K-means聚类算法的远程学习者效果分析 |
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| 引用本文： | 侯月姣,李青,王晓军,李晓丽.基于K-means聚类算法的远程学习者效果分析[J].北京邮电大学学报(北京邮电大学学报),2011,13(1):104-109. |
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| 作者姓名： | 侯月姣 李青 王晓军 李晓丽 |
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| 作者单位： | 北京邮电大学网络教育学院; |
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| 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。
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| 关 键 词： | K—means算法 个性化教学 远程学习 远程教育 |
Effect Analysis of Distance Learners' Action Based on K-means Clustering Algorithm |
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| HOU Yue-jiao,LI Qing,WANG Xiao-jun,LI Xiao-li.Effect Analysis of Distance Learners' Action Based on K-means Clustering Algorithm[J].Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition),2011,13(1):104-109. |
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| Authors: | HOU Yue-jiao LI Qing WANG Xiao-jun LI Xiao-li |
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| Institution: | HOU Yue-jiao,LI Qing,WANG Xiao-jun,LI Xiao-li(School of Network Education,Beijing University of Posts and Telecommunications,Beijing 100088,China) |
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| 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. |
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| Keywords: | K-means algorithm personalized teaching distance learning distance education |
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