Document Type
Original Study
Keywords
Artificial intelligence, AI, Higher education, Bibliometric analysis, University governance, New institutional theory
Abstract
This article maps the field of artificial intelligence in higher education (HEI-AI) from an institutional and management perspective. We draw on 52,270 peer-reviewed articles and reviews indexed in Web of Science and Scopus between 1959 and 2025. Using the bibliometrix package and its biblioshiny interface in R, we combine descriptive indicators with science-mapping techniques, including co-authorship and co-citation networks, keyword co-occurrence, thematic mapping and thematic evolution. The initial corpus of 94,845 records was cleaned by merging the two databases, removing duplicates and restricting the sample to full-length journal articles and reviews that explicitly address AI in higher education.
The results show a long period of slow growth followed by an exponential expansion after 2023, closely aligned with the diffusion of generative AI tools such as ChatGPT. At the country level, China dominates in publication volume, while the United States leads in citation impact. Countries such as France contribute fewer but highly cited papers and function as additional intellectual hubs. Conceptual and thematic analyses indicate a gradual shift towards more technical and data-driven work, centred on artificial intelligence, teaching and learning in tertiary education, and learning analytics, prediction, classification and performance metrics. Interpreted through neo-institutional theory, these patterns point to legitimacy-oriented AI adoption, coercive and mimetic isomorphism, and the growing influence of bibliometric indicators on organisational fields. The paper argues that HEI-AI should be understood as a strategic management and governance issue rather than only a pedagogical innovation, and it outlines implications for institutional AI strategies, policy design and future research on organisational adaptation in higher education. AI is not just technology; it is a process that redefines the institutional structure.
How to Cite This Article
Taştan, Kürşat and Taştan, Nalan Sabır
(2025)
"Artificial Intelligence in Higher Education: A Bibliometric and Science-Mapping Analysis from an Institutional and Management Perspective,"
Khazar Journal of Humanities and Social Sciences: Vol. 28:
Iss.
4, Article 3.
Available at:
https://kjhss.khazar.org/journal/vol28/iss4/3
Receive Date
14 September 2025
Accept Date
29 December 2025
Publication Date
12-31-2025