Mapping the Landscape of AI Implementation in STEM and STEAM Education: A Bibliometric Analysis

The purpose of this paper is to explore the applications, research trends and research gaps of AI in STEM and STEAM education through bibliometric analysis. Despite the increasing application of AI technology in education, systematic research on its specific role and developmental trends in STEM and STEAM education is still relatively lacking. In this paper, literature data on the application of AI in STEM/STEAM education between 2014 and 2024 were collected using the Web of Science database, and analyzed using the Bibliometrix R package and VOSviewer to identify the research hotspots, development trends, and future research gaps in the field. The results of the study show that the research on the application of AI in STEM/STEAM education has shown a significant growth trend since 2019, especially in China and the United States. Keyword analysis shows that emerging topics such as generative AI, personalized learning and AI literacy have gradually become the focus of research in recent years. At the same time, the study also reveals that the existing literature has paid less attention to AI in the field of arts education, and that the long-term impact and cross-disciplinary integration of AI technologies in STEM and STEAM education still need to be further explored. The research in this paper provides new perspectives for a deeper understanding of the potentials and challenges of AI in STEM and STEAM education and suggests directions for future research.