Mapping the Research Landscape of Artificial Intelligence in Education

Abstract

Generative Artificial Intelligence (GenAI) transforms education by enabling fast and unique content creation, generating adaptive learning, customizing teaching practices, and assisting the assessment process. However, the fast growing in number of publications introduces challenges in understanding the state of knowledge, dominant themes and identification of future direction. This study applies a bibliometric analysis to mapping the landscape of GenAI in educations. The data used in this study were retrieved from the Scopus database, resulting in 2,965 articles included based on systematic selection criteria. VOSviewer, a bibliometric analysis tool, was used for network visualization and analysis of co-authorship and keyword co-occurrence. The findings unveiled that over 90% of the included studies appeared between 2023 and 2025. The majority of the articles were retrieved from computer sciences, health professions, and social sciences. Ethical consideration is a central observation across these fields. The results provided an overview of GenAI in education and highlighted key themes in each field of study.

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