Trends and Hotspots in Ai-Focused Teacher Training for Science Education: A Bibliometric Review

Abstract

This study examines the publication landscape and scholarly impact of research on Trends and Hotspot in AI-focused teacher training in science education through a bibliometric analysis of leading journals and conference proceedings. The findings reveal that the field remains emerging and widely dispersed across a limited number of high-impact international sources, with no single dominant journal. Key contributors include Education and Information Technologies, Education Sciences, Frontiers in Education, Journal of Science Education and Technology, and Research in Science Education, each contributing two publications. Among these sources, Frontiers in Education demonstrated the highest citation impact, suggesting strong scholarly engagement and influence within the field. In contrast, some high-ranking journals showed lower citation counts, likely due to the recency of the publication within the 2021-2025 period. The results also highlight the global nature of research production, with major publishers based in Switzerland, the Netherlands, and the United States, indicating strong academic infrastructures supporting this emerging area. Although conference proceedings contributed fewer studies, they played a significant role in early knowledge dissemination, particularly in rapidly evolving topics at the intersection of artificial intelligence education. Particularly, certain conference publications demonstrated substantial citation influence, emphasizing their importance in shaping early discourse. The analysis suggests that AI-focused teacher training in science education is a multidisciplinary and evolving field situated at the intersection of educational technology, science education, and computer science. While still consolidating its core knowledge base, the field shows increasing scholarly attention, methodological diversity, and global participation. These findings provide a clearer understanding of current research trends and offer a foundation for guiding future studies, policy development, and the integration of AI in teacher professional development programs.