A Bibliometric analysis of publications on higher education students’ awareness of artificial intelligence
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https://doi.org/10.26809/joa.3045Keywords:
Artificial intelligence, AI awareness, AI literacy, Higher education students, Bibliometric analysisAbstract
This study examines how higher education students’ awareness, literacy, attitudes and perceptions of artificial intelligence (AI) have been investigated in the scholarly literature. The objective is to map the development, main actors and thematic structure of this emerging field and to identify gaps for future research and practice.
A bibliometric review was conducted using publications indexed in the Web of Science Core Collection and Scopus. The search string “artificial intelligence” AND “awareness” AND (“university student*” OR “higher education student*” OR “undergraduate student*”) was applied to titles, abstracts and keywords. After merging databases, removing duplicates and limiting the timespan to 2014–2025, the final corpus comprised 235 documents. Performance indicators (annual production, document types, sources, authors, institutions, countries) and science-mapping techniques (collaboration networks, keyword co-occurrence, thematic map and trend topics) were applied in R with the bibliometrix/Biblioshiny environment.
The results show very limited activity until 2019, followed by exponential growth from 2023 onwards, with most publications produced in a small set of countries and STEM-oriented disciplines. A few journals and universities account for a substantial share of the output, while international co-authorship remains modest. Thematic analyses reveal motor themes around AI awareness and human-centred concerns, and around students in engineering and computing education, whereas critical and non-STEM perspectives are less developed.
The study positions student AI awareness research in the exponential-growth stage of disciplinary development and provides the first field-level map focused specifically on higher education students, offering an evidence base for future empirical work, curriculum design and policy discussions.
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