Knowledge Mapping for the Study of Artificial Intelligence in Education Research: Literature Reviews


  • Thitinan Chankoson
  • Fenglei Chen
  • Zhiting Wang
  • Mengqi Wang
  • Khunanan Sukpasjaroen



This study aims to provide a systematic and complete knowledge map for researchers working in the field of research on the application of artificial intelligence in education. In addition, it is designed to help researchers quickly understand author collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends, and research frontiers of scholars from a library informatics perspective. In this study, a bibliometric approach was used to quantitatively analyze the retrieved literature with the help of the bibliometric analysis software CiteSpace. The analysis results are presented in tables and visual images in this paper. The results of this study indicate that collaborative relationships among scholars need to be improved and collaborative research relationships among research institutions are more fragmented. This study also points out the shortcomings of this study: Chinese educational researchers and practitioners still have a relatively vague understanding of some fundamental issues in the process of integration and development of AI and education. Therefore, this paper uses quantitative research methods such as bibliometrics and visualization pictures to systematically and intuitively reveal the research progress and trends on the application of artificial intelligence in education based on the published literature and to provide a reference for further research on this topic in the future.


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