首页    期刊浏览 2024年12月12日 星期四
登录注册

文章基本信息

  • 标题:Educational Data Mining and Learning Analytics: differences, similarities, and time evolution
  • 本地全文:下载
  • 作者:Laura Calvet Liñán ; Ángel Alejandro Juan Pérez
  • 期刊名称:International Journal of Educational Technology in Higher Education
  • 印刷版ISSN:1698-580X
  • 电子版ISSN:2365-9440
  • 出版年度:2015
  • 卷号:12
  • 期号:3
  • 页码:98-112
  • DOI:10.7238/rusc.v12i3.2515
  • 语种:English
  • 出版社:Springer Verlag
  • 摘要:

    Technological progress in recent decades has enabled people to learn in different ways. Universities now have more educational models to choose from, i.e., b-learning and e-learning. Despite the increasing opportunities for students and instructors, online learning also brings challenges due to the absence of direct human contact. Online environments allow the generation of large amounts of data related to learning/teaching processes, which offers the possibility of extracting valuable information that may be employed to improve students’ performance. In this paper, we aim to review the similarities and differences between Educational Data Mining and Learning Analytics, two relatively new and increasingly popular fields of research concerned with the collection, analysis, and interpretation of educational data. Their origins, goals, differences, similarities, time evolution, and challenges are addressed, as are their relationship with Big Data and MOOCs.

  • 关键词:Online Learning ;Educational Data Mining ;Learning Analytics ;Big Data ;aprendizaje en linea ;minería de datos educativos ;análisis de datos sobre aprendizaje ;macrodatos
国家哲学社会科学文献中心版权所有