AI and Computational Intelligence in Education: A Bibliometric Analysis

The rapid expansion of Artificial Intelligence (AI) and Computational Intelligence (CI) in educational research has reshaped how teaching, learning, and assessment are conceptualised. Despite this growth, existing studies have primarily focused on the application of AI in education. At the same time, scant attention has been given to the CI dimension, resulting in fragmented insights into how both paradigms jointly influence educational innovation. This study, therefore, presents a comprehensive bibliometric analysis of global scholarly production on AI and CI in education, identifying temporal trends, leading authors, institutions and countries, key journals, thematic foci, and collaborative networks. Data was extracted from the Scopus database, covering the period from 2012 to 2024. Using bibliometric software (e.g., VOSviewer, Bibliometrix), we analysed publications. Results indicate exponential growth in AI and CI research in education since 2015, with dominant contributions from China, the United States, and Australia, and high-impact journals such as Computers & Education, IEEE Transactions on Learning Technologies, and the International Journal of AI in Education. Thematic clusters coalesce around intelligent tutoring systems, machine learning in adaptive learning, deep learning, learning analytics, and educational data mining. However, the analysis reveals persistent research gaps, particularly the limited exploration of CI applications in resource-constrained educational contexts and ethical considerations surrounding AI integration. This bibliometric mapping offers scholars, practitioners, and policymakers a comprehensive overview of the field, suggesting future research and capacitybuilding directions.