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Despite growing research on AI in education, gaps remain in understanding its impact, emerging trends, and scholarly contributions. This study aims to analyze the research landscape on AI adoption and acceptance in higher education through bibliometric analysis. The study relies on data from the Scopus database (2015–2024) and uses VOSviewer for visualization. The findings reveal a significant rise in research on AI in higher education, reflecting increasing academic interest over the years. Geographically, a few leading countries dominate AI research, while contributions from emerging research hubs continue to grow. In terms of publication types, journal articles and conference papers are most prevalent, whereas books and reviews remain limited, highlighting the need for more comprehensive studies. Key research topics include AI’s role in education, particularly in student engagement, machine learning, e-learning, and interactive tools.

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Artificial Intelligence in Higher Education: A Bibliometric Analysis of Acceptance and Adoption Studies

  • 章节

  • 发表日期：

    2026年

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  • Suleiman Ibrahim Shelash Mohammad,
  • Anber Abraheem Shlash Mohammad,
  • Asokan Vasudevan,
  • Khaleel Ibrahim Al-Daoud,
  • Annie Wang Pei Ling,
  • Dheifallah Ibrahim Mohammad,
  • Abdullah Ibrahim Mohammad,
  • Sam Toong Hai,
  • Muhamad Saufi Che Rusuli

摘要

Despite growing research on AI in education, gaps remain in understanding its impact, emerging trends, and scholarly contributions. This study aims to analyze the research landscape on AI adoption and acceptance in higher education through bibliometric analysis. The study relies on data from the Scopus database (2015–2024) and uses VOSviewer for visualization. The findings reveal a significant rise in research on AI in higher education, reflecting increasing academic interest over the years. Geographically, a few leading countries dominate AI research, while contributions from emerging research hubs continue to grow. In terms of publication types, journal articles and conference papers are most prevalent, whereas books and reviews remain limited, highlighting the need for more comprehensive studies. Key research topics include AI’s role in education, particularly in student engagement, machine learning, e-learning, and interactive tools.