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Research Landscape of Adaptive Learning in Education: A Bibliometric Study on Research Publications from 2000 to 2022

Author

Listed:
  • Yuhui Jing

    (College of Educational Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China)

  • Leying Zhao

    (College of Educational Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China)

  • Keke Zhu

    (College of Foreign Languages, Zhejiang University of Technology, Hangzhou 310023, China)

  • Haoming Wang

    (College of Educational Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China)

  • Chengliang Wang

    (College of Educational Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China)

  • Qi Xia

    (Department of Curriculum and Instruction Faculty of Education, The Chinese University of Hong Kong, Hongkong 999077, China)

Abstract

Adaptive learning is an approach toward personalized learning and places the concept of “learner-centered education” into practice. With the rapid development of artificial intelligence and other technologies in recent years, there have been many breakthroughs in adaptive learning. Thus, it is important to gain insight into the evolution of related research and to track the research frontiers to further promote its development. This study used CiteSpace and VOSviewer to conduct a bibliometric analysis of 644 adaptive learning journal papers indexed in the WoS database from 2000 to 2022. This study presented a general view of the field of adaptive learning research over the last two decades using quantitative analysis. Currently, adaptive learning research is rapidly developing. In terms of the major research forces, a core group of authors including Qiao J. F., Han H. G. and Song Q has been formed; the major publishing country in this field is China; the core publishing journals include IEEE Transactions on Neural Networks and Learning Systems. Four major research topics in this field were identified using cluster analysis, namely the application of deep learning in educational data analysis, the development and application of adaptive learning model in AI education, the development and application of intelligent tutoring system in tutoring and teaching, cutting-edge modeling technology for feature modeling and knowledge tracing. Through evolution analyses, the logic of adaptive learning research’s development was determined; that is, technological changes have played a key role in the development of this field. Following the logic, we presented three frontiers of adaptive learning with burst terms: feature extraction, adaptation model and computational modeling. Adaptive learning is a core research topic for both computer science and educational technology disciplines, and it is also an important field where emerging technologies empowering education and teaching can play a part. The findings of the study clearly presented the current research status, evolutionary logic and research frontiers of this topic, which can provide references for the further development of this research field.

Suggested Citation

  • Yuhui Jing & Leying Zhao & Keke Zhu & Haoming Wang & Chengliang Wang & Qi Xia, 2023. "Research Landscape of Adaptive Learning in Education: A Bibliometric Study on Research Publications from 2000 to 2022," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3115-:d:1062177
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    References listed on IDEAS

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