Using Artificial Intelligence for Higher Education

An Overview and Future Research Avenues

Bibliographic Data

ID16916144
AuthorsJuan-Manuel Aguado-García (0009-0009-9850-6803, Universidad Rey Juan Carlos, corresponding author), Sara Alonso-Muñoz (0000-0001-8991-5781, Universidad Rey Juan Carlos), C De-Pablos-Heredero (0000-0003-0457-3730, Universidad Rey Juan Carlos)
Year2025
Volume15
Issue2
Publication date2025-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440251340352
OpenAlexW4410889402
LanguageEN
Citations received5
References cited72

Artificial intelligence plays an important role in higher education, helping to manage centres and students’ educational pathways, and acting as a valuable tool for both professors and scholars. However, its use in education is still at an early stage of development. Despite the notable increase in the number of publications and the growing interest in this area, there is a need to understand the rapid evolution of this domain. Hence, to fill this gap in the literature, this article employs a bibliometric approach based on co-occurrence analysis to identify what existing research and to understand current trends and emerging topics in the field of AI and higher education. To conduct this study, VOSviewer and SciMat softwares were used to analyse 181 papers retrieved from Web of Sciences and Scopus databases. Findings reveal that the conceptual structure consist of the impacts of AI on academic performance, particularly in relation to the use of chatbots such as ChatGPT and its multiple uses. To encompass the focus on students’ engagement and the potential for AI to enhance their self-regulated learning and active learning. Furthermore, aspects such as the integration of machine learning and robotics in higher education and student feedback are also considered. The emerging themes were found to be highly related to engagement strategies for the implementation of these technologies. Additionally, this paper provides future research avenues according to the results obtained, which could support scholars for the development of future studies, highlighting the lack of papers focussed on management and business issues in the implementation of AI tools and the need for personalisation. The training required to use these tools properly and the impact on students’ academic performance to monitor success are among the most outstanding practical implications of this study

Cognitive science · Engineering ethics · Management science · Mathematics education · AI and HR Technologies · Big Data and Business Intelligence · Engineering · Online Learning and Analytics · Psychology

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