MAPPING RESEARCH TRENDS IN ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A BIBLIOMETRIC ANALYSIS - Mohd, Norhazren Izatie; Tajul Ariffin, Hamizah Liyana; Kamaruddin, Tantish; Mohamad Shukery, Nurshikin; Ismail, Fuziah; Omar, Siti Rahmah; Kamarden, Hamidah; Abd Rahman, Nur Hidayah; Mustaffa, Nur Emma (INTERNATIONAL JOURNAL OF MODERN EDUCATION (IJMOE), 2025)
The integration of Artificial Intelligence (AI) in higher education has undergone rapid evolution, prompting a growing body of scholarly interest that necessitates a comprehensive overview of research patterns and trends. This study aims to map and analyse global research developments in the field of AI within higher education through a bibliometric approach. Despite the increasing relevance of AI in shaping educational practices, a lack of consolidated analysis remains regarding how this domain has matured over time, who the major contributors are, and what thematic directions currently dominate research. To address this gap, we collected bibliographic data from the Scopus database, yielding a final dataset of 1,570 documents published between 2020 and 2025. Using Scopus Analyzer, OpenRefine for data cleaning, and VOSviewer for visualisation, we systematically examined publication trends, top contributing authors, countries, institutional collaborations, keyword co-occurrences, and citation patterns. Our findings reveal a significant surge in publications from 2023 onwards, with the United States, China, and India emerging as leading contributors. The most cited works focus on generative AI applications, such as ChatGPT, alongside ethical, pedagogical, and policy implications. Keyword analysis reveals dominant themes centred around "artificial intelligence," "higher education," "ChatGPT," and "teaching and learning." Co-authorship mapping indicates strong international collaboration, particularly among Western and Asian research institutions. The results highlight the dynamic and interdisciplinary nature of AI research in higher education, underscoring the growing global academic interest in exploring its transformative potential. This study provides a foundational reference for educators, policymakers, and researchers aiming to understand the trajectory and future direction of AI applications in the academic landscape.