Artificial intelligence in pre-service teacher education: Bibliometrics analysis

Abstract

This study conducts a comprehensive bibliometric analysis to evaluate how research on artificial intelligence (AI) integration in pre-service teacher education has evolved from 2020 to 2025. Using Bibliometrix 5.0 in R, I analyzed 3,623 papers from Web of Science (1,823) and Scopus (1,800). The data reveal that following ChatGPT’s launch in 2022, publications increased dramatically, with Scopus exhibiting an annual growth rate of 41.38% compared to Web of Science’s 18.83%. Germany and Finland demonstrate the highest citation impact per article, while China shows the lowest citation density despite high publication volume. Generative AI and ChatGPT emerge as the most frequently discussed topics. Thematic mapping reveals a paradigmatic shift from traditional TPACK models toward emerging AI-TPACK frameworks. However, a significant gap persists between technical AI concepts and their practical implementation in educational settings. Web of Science statistics show that new “motor themes” are developing in education, but Scopus has not yet found a distinct core topic. For future research, I recommend enhanced interdisciplinary collaboration, integration of AI literacy curricula in teacher preparation programs, and development of more inclusive AI policies. Overall, this analysis provides researchers, educators, and policymakers with comprehensive insights into this rapidly evolving field.

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