摘要
Moodle作为一款优秀的开源在线学习平台,在国内外教学中得到了广泛的应用,但借助其开展深度学习分析的研究并不多见。本文以Moodle平台中一门混合式课程的在线学习活动为例,通过统计、可视化、聚类、社会网络分析等方法,从学习资源利用、学习活动参与、学习时间分布、师生互动模式、易错试题等方面展开了较为全面的分析,在此基础上总结了在线学习的若干特点和规律,并针对后续教学调整和优化提出了若干建议。
As a good open-source online learning platform, Moodle is widely used at home and abroad. However, the deep research on learning analytics based on Moodle is rarely found. In this paper, a blended course is taken as an example to analyze the online learning activities on Moodle platform.Multiple methods including statistics, visualization analysis, cluster analysis and social network analysis are used to carry out the research. It analyzes students＇ online learning behaviors from five different aspects,which includes the utilization of learning resources, participation of learning tasks, allocation of learning time, patterns of users＇ interaction and fallible questions in examination. Finally, the characteristics and laws of online learning in this course are summarized, and some advice for adjusting and optimizing instruction in the future is put forward.
出处
《电化教育研究》
CSSCI
北大核心
2016年第12期46-51,共6页
E-education Research
基金
浙江省教育科学规划2015年度课题"大数据背景下的在线学习分析技术与应用研究"(课题编号:2015SCG358)
浙江师范大学教育学一级学科基地年度课题"基于大数据的在线学习分析研究"(课题编号:ZJJYX201403)
