Visualizing the knowledge mapping of artificial intelligence in education: A systematic review

Artificial Intelligence (AI) plays a vital role in the growth and progress of education. Therefore, there is a need to scientifically explore the application of Artificial Intelligence in Education (AIED) and systematically analyze the development trends and research hotspots of AIED to provide reference for researchers. In this study, 1356 articles (2016–2023) in WOS were selected for further research, utilizing knowledge graph analysis. Using both VOSviewer and CiteSpace, which facilitated triangulating the data across software platforms to ensure the reliability of the results, the main highly co-cited literature and keywords were thoroughly analyzed. The key highlights of the results are: Firstly, the study reveals three major themes in the field of AI education, namely, medical theme, educational theme, and ChatGPT theme. Secondly, important literature and nodes in the field of AIED were identified. Thirdly, the study demonstrates the main technologies in the field of AIED, including Natural Language Processing, Machine Learning, Deep Learning, and Generative Artificial Intelligence. Finally, the burst analysis illustrates the hotspots and themes of the AIED at different stages. This study enriches the understanding of the fundamental knowledge and research frontiers essential to the application of AIED, which helps identify the patterns and trends for future research and teaching practices.