Navigating the AI-Enhanced STEM education landscape: a decade of insights, trends, and opportunities

Background Artificial intelligence (AI) has assumed an increasingly pivotal role in STEM education. However, a comprehensive review that captures the current landscape and research trends in this domain remains conspicuously absent. Purpose: In response, this study undertakes an exhaustive examination of 186 scholarly articles, all centered on the application of AI in STEM education.Methods This study used a bibliometric analysis to undertake an examination of the 186 articles. These articles, from the Web of Science Core Collections, spanned the time frame between 2013 and 2023.Results and conclusion This study found that: (1) the field had traversed two distinct phases, discernible in the annual publication trends—an initial exploratory phase followed by a rapid development phase; (2) the utilization of AI in STEM education unfolded along four key pathways: the refinement of exploratory STEM teaching through design principles, the seamless integration of emerging AI technologies into STEM education, the practical application of novel AI tools within STEM classrooms, and investigations into AI’s potential to enhance student motivation and academic performance in STEM disciplines; (3) 13 primary themes were identified, encapsulating diverse subjects ranging from early childhood education and 3D printing to the ARCS motivation model and collaborative learning strategies; and (4) relatively limited prevalence of long-term collaborations was identified, with research activities predominantly concentrated in Asia, Europe, and the Americas. This review serves as an essential resource for scholars. We also discuss the implications for educational practices, research, and policymaking within the STEM education landscape.