基于数据挖掘的在线学习评价系统

Lingyan Wang, Jun Yu Li, Lulu Ding, Pengkun Li
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引用次数: 11

摘要

本文讨论了数据挖掘技术在E-Learning评价系统中的应用。首先收集和分析学生的学习行为数据。然后,在数据挖掘技术的支持下,研究学习行为与学习效果之间的关系,并在Weka平台上使用J4.8算法建立决策树模型。最后对该模型进行了评估,其准确率接近86.7%。因此,所提出的方法可用于E-Learning评价系统中对学生的学习行为进行评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
E-Learning Evaluation System Based on Data Mining
The application of data mining in E-Learning evaluation system is discussed in this paper. Students' learning behavior data are first collected and analyzed. Then, with the support of data mining technology, the relationship between learning behavior and learning effect is studied and the decision tree model is established by using J4.8 algorithm on the Weka platform. Finally, the model is assessed and the accuracy rate of it can reach almost 86.7%. Thus the method proposed can be used in E-Learning evaluation system to evaluate students' learning behavior.
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