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《Modern Educational Technology》 2018-06
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Online Learning Behavior Analysis Model and Its Application in Network Learning Space

WU Lin-jing;LAO Chuan-yuan;LIU Qing-tang;CHENG Yun;MAO Gang;School of Educational Information Technology, Central China Normal University;School of Educational Information Technology, Huanggang Normal University;School of Teacher Education, Zhejiang Normal University;  
For the problem that the data in network learning space is not fully tapped and utilized, this article proposed an online learning behavior analysis model based on data mining technology. In this model, online learning behaviors were classified into four categories: independent learning behavior, system interaction behavior, resource interaction behavior and social interaction behavior. Based on these four categories, correlation analysis, classification analysis and clustering analysis were applied to analyze the data and provide suggestions for the stakeholders in network learning space. Taking data from one network learning space as a case, we found that:(1)Independent learning behaviors were strong predictors and had the strongest correlation with learning performance. The frequency of asking for help had the weakest correlation with other behaviors, and it was not suitable to consider it as a key indicator in analyzing learner behaviors.(2)The accuracy of performance prediction was 84.62% with K-nearest Neighbor Classification based on the strong correlated learning performance.(3)clustering analysis indicated that learners could be divided into four typical categories in terms of learning behavior model. As a result, different strategies could be offered to students of different types to promote individualized teaching and learning.
【Fund】: 国家自然科学基金项目“网络学习资源深度聚合及个性化服务机制研究”(项目编号:71704062)、“数字化课堂环境下教学行为分析及优化策略研究”(项目编号:71603098);; 教育部人文社科规划基金项目“基于场景感知的户外体验式学习环境构建方法研究”(项目编号:17YJA880104);; 华中师范大学基本科研业务费专项资金项目“基于大数据的慕课评论语义分析及应用研究”(项目编号:CCNU18QN022)资助
【CateGory Index】: G434
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