• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 教学研究与改革 • 上一篇    下一篇

数据驱动研究范式下的MOOC教学研究问题初探

谢正,李建平   

  1. (国防科技大学文理学院,湖南 长沙 410073)
  • 收稿日期:2018-07-10 修回日期:2018-09-15 出版日期:2018-11-26 发布日期:2018-11-25
  • 基金资助:

    国家自然科学基金(61773020)

Study on data-driven research methods for MOOC

XIE Zheng,LI Jianping   

  1. (College of Arts and Sciences,National University of Defense Technology,Changsha 410073,China)
  • Received:2018-07-10 Revised:2018-09-15 Online:2018-11-26 Published:2018-11-25

摘要:

MOOC教育打破了传统教育的时空界限和学校围墙,跨区域推动了高校共享优质学习资源。在MOOC发展过程中,课程平台积累的在线学习数据为开展数据驱动式的MOOC教学研究提供了基础。采用定性与定量相结合、数据科学与教育理论相结合的方式,综合应用统计学与网络科学等理论方法,分析学习行为,挖掘有效学习因素,度量学习有效性,探索有效方法评价课程效用与开展个性化定制教学,对国家推进精品在线开放课程建设以及“互联网+教育”发展等方面具有紧迫的实践意义。

关键词: 大规模开放在线课程, 学习行为分析, 互联网教育

Abstract:

MOOC learning, a new form of education in the information era, breaks through the spacetime limits and the boundary of schools, and promotes sharing of high quality study resources among universities. In the developing process of MOOCs, massive online learning data have been collected, and analyzing these data can provide support for research on MOOC. Combining qualitative and quantitative methods, data science and theory of education,  statistics and network science, we analyze learning behavior patterns, measure the effectiveness of learning behaviors, establish an effectiveness evaluation model for MOOCs, and explore customized teaching methods. Our data-driven methods have a practical significance for  the national project of constructing excellent online courses, and help to improve “Internet+Education” quality.

Key words: MOOC, learning behavior analysis;Internet+Education