Mapping the Frontier: A Bibliometric Analysis of AI in Tertiary Education

Hendra Sahputra Batubara, Nizwardi Jalinus, Fahmi Rizal, Ronal Watrianthos

Abstract


This article presents a bibliometric analysis of research on artificial intelligence (AI) applications in higher education over the past decade. Through computer-assisted analysis of 412 documents from the Web of Science core collection, we shed light on publication trends, productivity patterns, and conceptual development. Despite this exponential growth in research output, there remains significant uncertainty about the long-term impact of AI on pedagogical practices, learning outcomes, and the overall structure of higher education systems. The results show an annual production increase of 31.8% in research publications on AI in higher education, signaling scientific recognition of the disruptive potential. The concentration in renowned specialist journals on the topic of technology-supported learning is offset by the distribution of these journals across 206 multidisciplinary sources. With 10 publications, the Chinese University of Hong Kong is the leading contributing institution. China leads in the number of publications on AI in higher education, with 62 articles, followed by the United States with 45 and the United Kingdom with 29. These regional anchors are driving progress in the field. Although there is strong collaboration, the research output remains spread across 1,182 scientists without established leaders, reflecting the diverse and emerging nature of the field. Topic modeling and keyword analysis mean an increasing examination of the connections to education systems, training, labor markets, and learning analyses. This highlights the tensions surrounding data ethics, academic integrity, and the disruption of the workforce as algorithms permeate admissions, advising, and teaching. Our examination of the anatomy of this rapidly growing field provides indispensable perspectives for guiding innovation. As techniques advance from theory to reality, continued empirical research to explore risks and opportunities will be critical to upholding humanistic educational values.

 

https://doi.org/10.26803/ijlter.23.10.4


Keywords


Bibliometrics; Artificial Intelligence; Higher Education; Educational Technology; WOS

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References


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