IJIET 2020 Vol.10(5): 394-398 ISSN: 2010-3689
doi: 10.18178/ijiet.2020.10.5.1396

The Hotspots and Trends of Adaptive Learning: A Visualized Analysis Based on CiteSpace

Miaomiao Zhang and Rui Zhang

Abstract—Using the visual analysis of CiteSpace, and adopting the visual analysis and content analysis as main research methods, research on hot spots and development trends of adaptive learning were revealed. The literatures were collected from 2000 to 2018. The study of adaptive learning technology in foreign countries focus on higher education, and it is suggested to expand the scope of the research. The application of adaptive learning technology in education should be strengthened in China. The updating and integration of learning style scale should be considered and the open learner model is a new trend in future. In order to achieve the sharing of resources and domain models or the reusability and portability of the system, unified standards should be established. In addition, we should pay attention to the application of learning science theory closely related to adaptive learning. Adaptive personalized support service with big data, artificial intelligence, context recognition and emotion capture are a new trend in this field.

Index Terms—Adaptive learning, CiteSpace, co-word analysis, visual analysis.

Miaomiao Zhang is with the School of Education Information Technology, Capital Normal University, Wuhan, China (e-mail: 599153085@qq.com).
Rui Zhang is with the Educational Information Technology Collaborative Innovation, Center Capital Normal University, Wuhan, China (e-mail: 1837693345@qq.com).

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Cite: Miaomiao Zhang and Rui Zhang, "The Hotspots and Trends of Adaptive Learning: A Visualized Analysis Based on CiteSpace," International Journal of Information and Education Technology vol. 10, no. 5, pp. 394-398, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (Since 2019), INSPEC (IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net