Mapping the Evolution of Artificial Intelligence in Teacher Professional Development: A Bibliometric Analysis of Pedagogical Transformation
TL;DR
A comprehensive bibliometric analysis of research at the intersection of AI-focused TPD and classroom pedagogy identifies three dominant research clusters, which highlight a growing shift from technical adoption toward research exploring teachers’ readiness, ethical awareness, and pedagogical innovation when integrating AI.
Abstract
The integration of Artificial Intelligence (AI) into education is rapidly transforming teaching methods and educators’ professional roles. However, while the literature on AI in education has expanded significantly, prior bibliometric studies have primarily focused on broad technological perspectives, higher-education contexts, or student-centred learning. Moreover, limited attention has been devoted to how AI specifically shapes Teacher Professional Development (TPD) and its contribution to enhanced teaching practices. Thus, this study addresses this gap by conducting a comprehensive bibliometric analysis of research at the intersection of AI-focused TPD and classroom pedagogy. Accordingly, a total of 110 peer-reviewed publications (2018-2025) were analysed using descriptive bibliometrics, citation performance indicators, and science-mapping techniques, including co-authorship and keyword co-occurrence networks. Additionally, findings reveal a sharp acceleration in scholarly interest from 2022 onwards, indicating a rapidly maturing field driven by global educational digitalisation. The United States (US), Hong Kong, and Saudi Arabia emerge as leading contributors, while journals such as Education Sciences and Computers and Education: Artificial Intelligence serve as influential publication outlets. Specifically, thematic mapping identifies three dominant research clusters: (1) AI-enhanced teacher learning and competencies, (2) Generative AI (GenAI) applications in professional practice, and (3) pedagogical transformation through data-driven and intelligent systems. Overall, this study highlights a growing shift from technical adoption toward research exploring teachers’ readiness, ethical awareness, and pedagogical innovation when integrating AI. Likewise, the findings provide a valuable evidence base to guide future TPD initiatives aimed at strengthening AI-aligned teacher capabilities and improving instructional quality.