【作 者】：
熊潞颖， 郭幸君， 蒋 琪， 郑勤华
【关 键 词 】：
学业拖延； 学习分析； 聚类； 社会网络分析
【栏 目】：
网络教育
【中文摘要】：
拖延行为可以反映学生的自我管理情况。研究基于“365大学”平台的课程数据，定义并分析了在线学习者在学业拖延方面的行为表现，并结合K-means聚类算法和社会网络分析方法对学习者学业行为类型和学习行为变化进行分析。研究结果显示，在课程中存在七种不同类型的学习行为，其中有一种为恶性拖延行为。同时，学习行为之间的转化可以划分为三个子群，分别为尝试性行为集中子群、连续性行为集中子群和优秀成绩行为子群，这三个子群分别显示出不同的行为变化规律。研究对该在线课程提出了课程内容和平台设计两方面的建议，以改进平台的学习支持服务，提高课程质量。
【英文摘要】：
Procrastination is an important indicator of self-regulation. This paper defines and analyzes the academic procrastination behaviors of online learners based on the course data of a Chinese MOOC platform. In addition, k-means clustering algorithm and social network analysis are applied to analyze learners' academic behavior types and learning behavior changes. The result suggests that there are seven different types of learning behaviors in the course, one of which is malignant procrastination. Meanwhile, the transformation between learning behaviors can be divided into three subgroups, namely, the tentativebehavior subgroup, the consecutive behavior subgroup and the excellent performance behavior subgroup, which demonstrate different behavior changes. Suggestions are put forward on the content and platform design of the online course for improving the learning support service of the platform and the course quality as well.