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Research Status, Hotspots, and Evolutionary Trends of Intelligent Education from the Perspective of Knowledge Graph

Author

Listed:
  • Dingpu Shi

    (School of Computer and Information, Qiannan Normal University for Nationalities, Duyun 558000, China)

  • Jincheng Zhou

    (School of Computer and Information, Qiannan Normal University for Nationalities, Duyun 558000, China
    Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun 558000, China
    Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan, Duyun 558000, China)

  • Dan Wang

    (Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province, Duyun 558000, China
    Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan, Duyun 558000, China
    School of Mathematics and Statistics, Qiannan Normal University for Nationalities, Duyun 558000, China)

  • Xiaopeng Wu

    (Faculty of Education, Northeast Normal University, Changchun 130000, China)

Abstract

Intelligent education research has become a research hotspot in recent years. The Citespace software that operates a graph visualization function was used to clarify the current situation, hot spots, and evolutionary trends of intelligent education research development; the authors, institutions, and countries engaged in intelligent education research, as well as the basic knowledge structure, main keywords, citation clustering, dual-map overlay of journals and citation emergence of intelligent education research. The results show that the annual number of publications in the field has shown an upward trend since 2010, with strong communication among research institutions and countries, but weak communication among researchers. Among them, the United States is the center of the global collaborative network of intelligent education research. The basic knowledge structure of intelligence education research is mainly composed of Classroom Management, Evaluation Index, 5G Network, and Big Data Analytics. The dual-map overlay analysis of journals shows that the core areas of intelligence education are increasing, and the analysis of keywords and cited literature shows that Intelligence Tutoring System, AI system, Students and Education, Model, and System are high-frequency words with high-intensity burstness. In addition, research on intelligent education is characterized by multi-country, multi-field, and multi-disciplinary integration, and the adoption of Big Data, Distance Education Technology and Artificial Intelligence Technology to provide scientific support for teaching and learning will become the key research content in this field in the future.

Suggested Citation

  • Dingpu Shi & Jincheng Zhou & Dan Wang & Xiaopeng Wu, 2022. "Research Status, Hotspots, and Evolutionary Trends of Intelligent Education from the Perspective of Knowledge Graph," Sustainability, MDPI, vol. 14(17), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10934-:d:904229
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    References listed on IDEAS

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    2. Wenjing Yin & Naeem Jan, 2022. "An Artificial Intelligent Virtual Reality Interactive Model for Distance Education," Journal of Mathematics, Hindawi, vol. 2022, pages 1-7, February.
    3. Chaomei Chen & Loet Leydesdorff, 2014. "Patterns of connections and movements in dual-map overlays: A new method of publication portfolio analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(2), pages 334-351, February.
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    Citations

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    Cited by:

    1. Linchao Huang & Jincheng Zhou & Dan Wang & Fang Wang & Jiu Liu & Dingpu Shi & Xiaohong Chen & Duo Yang & Qingna Pan, 2023. "Visualization Analysis of Global Self-Regulated Learning Status, Hotspots, and Future Trends Based on Knowledge Graph," Sustainability, MDPI, vol. 15(3), pages 1-20, February.
    2. Duo Yang & Jincheng Zhou & Dingpu Shi & Qingna Pan & Dan Wang & Xiaohong Chen & Jiu Liu, 2022. "Research Status, Hotspots, and Evolutionary Trends of Global Digital Education via Knowledge Graph Analysis," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    3. Qingna Pan & Jincheng Zhou & Duo Yang & Dingpu Shi & Dan Wang & Xiaohong Chen & Jiu Liu, 2023. "Mapping Knowledge Domain Analysis in Deep Learning Research of Global Education," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    4. Xiaohong Chen & Jincheng Zhou & Jinqiu Wang & Dan Wang & Jiu Liu & Dingpu Shi & Duo Yang & Qingna Pan, 2022. "Visualizing Status, Hotspots, and Future Trends in Mathematical Literacy Research via Knowledge Graph," Sustainability, MDPI, vol. 14(21), pages 1-19, October.

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