基于行为序列分析对在线学习参与模式的探索

发布时间：2018-10-21 12:09

【摘要】：该文基于开放大学2131名学生在课程Moodle平台上的日志数据,通过相关分析、滞后序列分析和聚类分析对在线学习行为序列和参与模式进行了实证探索。研究发现,15个Moodle平台日志记录行为所形成的122个行为序列中,有36个行为序列与成绩显著相关,其中包括四个测试行为相关序列与成绩呈中度相关。研究采用滞后序列分析发现六个发生概率达到显著性水平的行为序列,并构建出在线学习行为转换模式。通过聚类分析,研究将学生样本根据其行为序列特征划分五种类型,并定义出五种在线参与模式:低投入式、浅层次投入式、绩效投入式、循序渐进式和随机参与式。文章最后从行为序列分析的价值、有效的行为序列与模式以及对在线学习行为转换特征的反思等方面对研究结果进行了讨论与总结。该文期望该研究能够为在线学习的分析、评估与促进提供有益的研究视角和研究支持。
[Abstract]:Based on the log data of 2131 students of Open University on the Moodle platform, this paper empirically explores online learning behavior sequences and participation patterns through correlation analysis, lag sequence analysis and clustering analysis. It was found that 36 of the 122 behavioral sequences formed by logging on 15 Moodle platforms were significantly correlated with achievement, including four test behavioral correlation sequences that were moderately correlated with achievement. Using lag sequence analysis, six behavioral sequences with significant occurrence probability were found, and an online learning behavior transformation model was constructed. Through clustering analysis, the students' samples are divided into five types according to their behavioral sequence characteristics, and five online participation models are defined: low input, shallow input, performance input, step-by-step and random participation. Finally, the paper discusses and summarizes the research results from the value of behavior sequence analysis, effective behavior sequence and pattern, and reflection on the characteristics of online learning behavior transformation. This paper hopes that this study can provide useful research perspective and support for the analysis, evaluation and promotion of online learning.
【作者单位】：北京师范大学远程教育研究中心;国家开放大学;
【基金】：2014年度教育部人文社会科学研究规划基金/青年基金项目“基于学习分析的远程学习者在线学习参与度评估模型与分析工具研究”(项目编号:14YJC880028)研究成果
【分类号】：G434

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