Generative AI in higher education: A bibliometric review of emerging trends, power dynamics, and global research landscapes
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.
Identifier Metadata
| Identifier | 110.0894/CON.2026.00865 |
| Canonical | mdoi:110.0894/CON.2026.00865 |
| Resolver URL | https://mdoi.org/110.0894/CON.2026.00865 |
| Resource URL | Open resource |
| Document URL | Open document |
| Content Type | Article |
| Authors | Kun Dai, Yabing Liu, Xiaofan Zhang |
| Year | 2026 |
| Depositor | Convergence Chronicles Organisation |
| Prefix | 110.0894 |
| Registered | July 29, 2026 |
| Updated | July 29, 2026 |
| Status | Active |
| Visibility | Public |
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