Mapping the Knowledge Structure and Thematic Evolution of Artificial Intelligence Applications in Higher Education with CiteSpace (2015–2025)

Authors

Hui Zhang Universiti Tun Abdul Razak (UNIRAZAK)
Muiyee Cheok

Keywords:

artificial intelligence, CiteSpace, generative AI, higher education, thematic evolution

Abstract

Artificial intelligence is reshaping teaching, learning, assessment, and institutional practices in higher education. This study maps the knowledge structure and thematic evolution of the field through a scientometric analysis of 376 English-language articles and reviews indexed in the Web of Science Core Collection from 2015 to 2025. CiteSpace 7.0.1 was used to examine publication growth, reference co-citation clusters, timeline patterns, and citation bursts. The results show limited activity before 2021, followed by rapid expansion in 2024 and 2025. The co-citation network demonstrated clear clustering (Q = 0.7111; S = 0.7551) and identified nine major themes, including artificial intelligence technologies, systematic reviews, self-regulated learning, software programming, and artificial intelligence capability. Thematic development shifted from general AI systems and adoption toward generative AI, ChatGPT-supported learning, student perceptions, and learning outcomes. These findings clarify the field’s intellectual foundations and highlight the growing importance of learner-centred and institutionally embedded AI applications.

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Published

27-07-2026

Issue

Volume 5, Issue 2, December 2025

Section

Articles

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Published by University Tun Abdul Razak (UNIRAZAK)