多元分析框架下的MOOC学习行为分析

郭欣悦
（北京大学 教育学院， 北京 100871）

【摘 要】MOOC学习行为分析研究已从描述性研究转向以大数据为证据、学习行为模型和分析框架为理论基础的深入研究阶段。MOOC课程数量激增，平台的功能愈发强大，学习者学习行为的印记被多种数据形式记录，分析学习绩效、学习行为产生的原因及相关性已有了研究环境和研究基础。本文结合中国大学MOOC平台上的X课程，梳理学习者学习行为类型，运用系统的观点和方法，从学习行为、行为分析维度、数据来源及类型、分析目的等要素及相互关系分析的视角，构建了多元学习分析框架，根据框架中的学习行为及影响要素，分析了X课程数据，对学习行为的整体趋势进行了分析，得出了目前MOOC课程学习中学习者持续力不强、学习投入不足、参与度不高的结论。在此基础上讨论了改善学习支持服务、优化课程设计的思路。
【关键词】学习行为；MOOC；多元框架；学习行为分析
【中图分类号】G51 【文献标识码】A 【文章编号】2096-1510（2017）04-0021-08

Analyzing MOOC Learning Behavior under A Multi-Analysis Framework
GUO Xinyue
（Graduate School of Education, Peking University, Beijing 100871, China）

Abstract: The study of MOOC learning behavioral analysis has gone from descriptive phase to intensive research, which treats large data as evidence on the basis of the learning behavior model and analytical framework. With the proliferation of MOOC courses and optimization of platform, learners’ learning behaviors are recorded in a variety of forms. It has already had research environment and existing base to analyze learning performance, causes and correlation of learning behaviors. Based on the X course from China’s Universities MOOC platform, this paper tends to define the types of learners’ behaviors and formulated a multiple analytical framework in the perspectives of behavioral analysis, learning behavioral dimension, data sources, data types as well as analytical purposes and correlation analysis. According to the influencing factors of framework, this paper analyzes the data from X course and the overall trend of learning behaviors. It is concluded that current MOOC learners’ persistence is not strong, learners’ engagement in learning is insufficient and that learners’ learning participation is not high. Based on such problems, this paper tends to propose some ideas for improving learning support service and optimizing curriculum design.
Keywords: learning behavior; MOOC; multiple framework; learning behavioral analyses

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