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大规模私有型在线课程学习行为及其影响因素研究——以国家开放大学网络课程学习为例 被引量:49

Learning behaviors in Massive Private Online Courses and their influencing factors: data from the Open University of China
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摘要 本文采用描述性分析和相关性分析对国家开放大学学习平台2015年秋季学期运行的57门MPOC(Massive Private Online Course)课程中54,228位学生产生的5,600多万条学习行为记录进行分析,结合教学过程跟踪和师生访谈,深入了解国家开放大学学生在线学习情况和课程交互情况,分析学生学习行为特点及其影响因素。通过分析发现,MPOC课程中学习者的活跃程度差异较大,多数学生只关注和考核直接相关的作业和测验,存在突击完成学习任务的情况,但也有部分学习时长和活跃程度都比较突出的学生,这些学生普遍集中在教学团队分工和教学组织合理、支持服务到位的课程中。分析还发现,教师教学和支持服务能有效地促进学生提交作业、完成测验和论坛发帖等人际、人机交互,而在提高学生资源浏览量和使用率方面效果不明显。同时,有效的管理机制和优秀的课程设计也是调动学生在线学习的重要因素。最后,基于分析结果,结合教学实际经验,从课程建设、教学和服务、管理机制三方面对国家开放大学网络课程给予相应的可操作性建议,希望能更好地落实课程教学,完善MPOC教学模式,为学生提供高质量的在线教学和良好的在线学习体验。 This study collected data from 54,228 distance learners enrolled in 57 Massive Private Online Courses(MPOCs)at the Open University of China(OUC)in the autumn term of 2015.Descriptive and correlation analyses were made of over 56 million learning behavior logs collected.Also drawing upon data from other sources,including tracking teaching processes,interviews with both staff and students,and the overall course engagement of OUC students,the study set out to identify features of student learning behaviors and their influencing factors.Findings show that MPOC learners varied considerably in their engagement.Most students only cared about assignments and texts directly related to course assessment and took learning activities as a rush job.In contrast,students of well-organized and well-supported courses tended to spend more time online and be more engaged.Findings also suggest that teachers’instruction and learner support effectively facilitated interpersonal and human-machine interaction in terms of assignment submission,test completion and forum participation but barely increased the use of learning resources.Effective management mechanisms and adequate course design were also found to be influencing factors.Implications of these findings for OUC were discussed in relation to course development,instruction and learner support,and management.
出处 《中国远程教育》 CSSCI 北大核心 2017年第4期23-32,共10页 Chinese Journal of Distance Education
基金 北京市教育科学"十二五"规划2015年度重点课题"基于教育大数据的大规模私有型在线课程教学绩效评估系统及其应用研究"(课题批准号:AJA15233) 国家开放大学"十二五"规划2014-2015年度青年课题"远程教育学习者网络学习行为分析及支持服务研究--以国家开放大学学习网为例"(课题批准号:G14A0031Q)的研究成果
关键词 MPOC MOOC 学习行为 学习分析 国家开放大学 网络课程 Massive Private Online Courses Massive Open Online Courses learning behavior learning analytics the Open University of China online course
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  • 1鲁川,林杏光.现代汉语语法的格关系[J].汉语学习,1989(5):11-15. 被引量:64
  • 2王海东.远程教育"无显著差异现象"研究评述[J].开放教育研究,2005,11(1):69-73. 被引量:10
  • 3李振亭,陈中.从视觉文化的角度论网络教学视频的应用[J].中国电化教育,2006(11):83-85. 被引量:18
  • 4王佑镁.在线教学设计标准及其评价应用研究[J].中国电化教育,2007(7):60-63. 被引量:11
  • 5黄荷.今日谈:大数据时代降临[J].半月谈,2012,(17).
  • 6Siemens,GlstInternational Conferenceon Learning Analyticsand Knowledge 2011 [EB/OL].<https ://tekri.athabascau.ca/ analytics/about.〉.
  • 7Johnson,L.,Adams,S.,andCummins,M.(2012).TheNMCHorizon Report: 2012 Higher EducationEdition.Austin,Texas:TheNewMediaConsortium.
  • 8Baepler,P.& Murdoch, C. J.(2010). Academic Analytics andData Mining in Higher Education. International Journal forthe Scholarship of Teaching and Learning, 4(2). 170-178.
  • 9Chen.E.,Heritage,M.&Lee,J.Identifying and MonitoringStudents, Learning Needs With Technology[J].Journal of Education for Students Placed at Risk,2010(3):309-332.
  • 10Romero& Ventura. Educational Data Mining;A Survey from1995 to 2005[J]. Expert Systems with Applications.2007,(33):125-146.

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