Mapping the Generative AI Research in Higher Education: 2022–2024 Insights

Abstract

ABSTRACT This study analyses over 4000 publications, including those from 2024, indexed in the Scopus database, aiming to describe the landscape of the growing body of research exploring the role of generative AI in higher education. We followed an inclusive approach to publication formats and languages, incorporating not only traditional peer‐reviewed articles but also conference proceedings and preprints. Our analysis focuses on two key dimensions—general characteristics of publications, including publication types, journals, subject areas, countries, languages, and collaboration patterns—and content analysis, covering topics, methodologies, and sentiment. Among the main findings, we identify that the majority of studies focus on individual‐level analysis, with a lack of comparative institutional‐ and national‐level perspectives. Clear regional clusters of AI research have emerged, but a significant gap remains in the form of comparative studies. Topic‐wise, there is a visible shift from the technical capabilities of AI systems to their practical implementation, ethical concerns, and integration into educational frameworks. Finally, although the field anticipates the use of advanced research methods, most studies still rely on isolated case studies, surveys and simple experimental designs.

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