Examining the Expansion and Collaborative Patterns of Artificial Intelligence in Education: A Bibliometric Study

Abstract

This research aims to evaluate the existing body of literature on the application of artificial intelligence (AI) in the field of education. Using a bibliometric analysis of 1,192 scholarly articles indexed in the Scopus database, the study maps the scholarly network in this field, identifies publication trends, influential contributors, core research themes, and areas that require further investigation. The findings reveal a significant exponential growth in publications since 2010, establishing AI in education as a vibrant field. Prolific contributors include individual authors, institutions like the Education University of Hong Kong, and countries such as China and the US. Network analyses highlight extensive collaborations through co-authorship within and between regions, while core themes focus on AI’s transformative role in pedagogy and learning experiences. Although the study is limited to Scopus-indexed publications, the insights from the bibliometric maps provide valuable implications for strengthening collaborative ties and addressing under-represented areas. This in-depth and systematic analysis offers a unique contribution to the field, informing future research directions in AI-enhanced education.