IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p3115-d1062177.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/3115/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/3115/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author-based citation analysis?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    2. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    3. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    4. Donthu, Naveen & Kumar, Satish & Pattnaik, Debidutta, 2020. "Forty-five years of Journal of Business Research: A bibliometric analysis," Journal of Business Research, Elsevier, vol. 109(C), pages 1-14.
    5. Andreas Strotmann & Dangzhi Zhao, 2012. "Author name disambiguation: What difference does it make in author‐based citation analysis?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(9), pages 1820-1833, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xianru Shang & Zijian Liu & Chen Gong & Zhigang Hu & Yuexuan Wu & Chengliang Wang, 2024. "Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-21, December.
    2. Carlo Dindorf & Eva Bartaguiz & Freya Gassmann & Michael Fröhlich, 2022. "Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review," IJERPH, MDPI, vol. 20(1), pages 1-23, December.
    3. Hanane Rhomad & Karima Khalil & Khalid Elkalay, 2023. "Water Quality Modeling in Atlantic Region: Review, Science Mapping and Future Research Directions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 451-499, January.
    4. Kristina Galjanić & Ivan Marović & Nikša Jajac, 2022. "Decision Support Systems for Managing Construction Projects: A Scientific Evolution Analysis," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    5. Mike Thelwall, 2020. "Mid-career field switches reduce gender disparities in academic publishing," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1365-1383, June.
    6. Chengliang Wang & Xiaojiao Chen & Teng Yu & Yidan Liu & Yuhui Jing, 2024. "Education reform and change driven by digital technology: a bibliometric study from a global perspective," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    7. Wirapong Chansanam & Chunqiu Li, 2022. "Scientometrics of Poverty Research for Sustainability Development: Trend Analysis of the 1964–2022 Data through Scopus," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    8. Dangzhi Zhao & Andreas Strotmann, 2020. "Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 255-270, July.
    9. Kim, Jinseok & Diesner, Jana, 2015. "The effect of data pre-processing on understanding the evolution of collaboration networks," Journal of Informetrics, Elsevier, vol. 9(1), pages 226-236.
    10. Mi Zhou & Biyu Bian & Weiming Zhu & Li Huang, 2021. "A Half Century of Research on Childhood and Adolescent Depression: Science Mapping the Literature, 1970 to 2019," IJERPH, MDPI, vol. 18(18), pages 1-20, September.
    11. Ciriaco Andrea D’Angelo & Nees Jan Eck, 2020. "Collecting large-scale publication data at the level of individual researchers: a practical proposal for author name disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 883-907, May.
    12. Zaheer Allam & Ayyoob Sharifi & Simon Elias Bibri & Didier Chabaud, 2022. "Emerging Trends and Knowledge Structures of Smart Urban Governance," Sustainability, MDPI, vol. 14(9), pages 1-29, April.
    13. Jinseok Kim & Jinmo Kim & Jason Owen-Smith, 2019. "Generating automatically labeled data for author name disambiguation: an iterative clustering method," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 253-280, January.
    14. Liu, Meijun & Hu, Xiao, 2021. "Will collaborators make scientists move? A Generalized Propensity Score analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    15. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    16. Irfan Ullah & Muhammad Safdar & Jianfeng Zheng & Alessandro Severino & Arshad Jamal, 2023. "Employing Bibliometric Analysis to Identify the Current State of the Art and Future Prospects of Electric Vehicles," Energies, MDPI, vol. 16(5), pages 1-24, February.
    17. Xuan Zhen Liu & Hui Fang, 2014. "Scientific group leaders’ authorship preferences: an empirical investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 909-925, February.
    18. Ridoy Deb Nath & Mohammad Ashraful Ferdous Chowdhury, 2021. "Shadow banking: a bibliometric and content analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-29, December.
    19. Freeman, Richard B. & Huang, Wei, 2014. "Collaborating With People Like Me: Ethnic Co-authorship within the US," IZA Discussion Papers 8432, Institute of Labor Economics (IZA).
    20. Uyen-Phuong Nguyen & Philip Hallinger, 2020. "Assessing the Distinctive Contributions of Simulation & Gaming to the Literature, 1970-2019: A Bibliometric Review," Simulation & Gaming, , vol. 51(6), pages 744-769, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3115-:d:1062177. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.