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  • 标题:AI in Online-Learning Research: Visualizing and Interpreting the Journal Publications from 1997 to 2019
  • 本地全文:下载
  • 作者:Gwo-Jen Hwang ; Yun-Fang Tu ; Kai-Yu Tang
  • 期刊名称:The International Review of Research in Open and Distributed Learning
  • 印刷版ISSN:1492-3831
  • 出版年度:2022
  • 卷号:23
  • 期号:1
  • 页码:104-130
  • DOI:10.19173/irrodl.v23i1.6319
  • 语种:English
  • 出版社:AU Press
  • 摘要:This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI) algorithms. Results indicate that, from 1997 to 2009, AIoL research focused on the combination of intelligent tutoring systems and distance learning. In 2010–2014, AIoL research emphasized learner-oriented learning. In 2015–2019, learner-system interactions to facilitate personalized, adaptive, and collaborative learning became the main focus. “Intelligent tutoring systems” have played the most important role in AIoL, followed by “profiling and prediction,” and “adaptive systems with personalization.” Accordingly, the roles and research trends as well as several suggestions for future research in the field of AIoL are provided as a reference for researchers and policy makers.
  • 关键词:artificial intelligence;online learning;literature review;trend analysis;visualization
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