Generative AI in higher education: A bibliometric review of emerging trends, power dynamics, and global research landscapes.

Autor/inn/en	Dai, Kun; Liu, Yabing; Zhang, Xiaofan
Titel	Generative AI in higher education: A bibliometric review of emerging trends, power dynamics, and global research landscapes.
Quelle	In: Computers and education: artificial intelligence, (2026) 10, Art. 100544, 12 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	2666-920X
DOI	10.1016/j.caeai.2026.100544
Schlagwörter	Künstliche Intelligenz; Wissenschaft; Hochschulsystem; Ausland; China; Großbritannien; USA
Abstract	The rapid evolution of Generative Artificial Intelligence (GenAI) is reshaping higher education (HE), offering transformative opportunities for academic engagement while posing significant challenges to academic integrity, ethical frameworks, and global research power dynamics. This study maps the recent (2022-2025) research landscape of GenAI in HE through a bibliometric analysis of 2762 articles from the Web of Science Core Collection. Employing multipolarity as an analytical lens, this study examines the power dynamics within this research domain reflected by publication records from different countries (or regions). Findings highlight surging global interest in GenAI in HE, with contributions led by the US, China, and the UK, alongside rising participation from non-Western scholars and institutions. By identifying the major topics, this study uncovers a more nuanced trajectory of GenAI-related discourse in HE. By examining publication status, contributors, and research topics, this study provides insights for stakeholders navigating the complexities of GenAI integration into HE and suggests trajectories for future research in this rapidly evolving field. (HRK / abstract übernommen).
Erfasst von	Hochschulrektorenkonferenz, Bonn
Update	2026/4