Bibliometric Analysis of Artificial Intelligence in STEM Education

Thiti Jantakun, Kitsadaporn Jantakun and Thada Jantakoon

Higher Education Studies, 2025, vol. 15, issue 1, 69

Abstract: This study conducts a bibliometric analysis of artificial intelligence (AI) in STEM education research from 2020 to 2024. The study uses citation analysis to examine publication trends, country contributions, top authors, cited journals, and influential articles in this field. Data was collected from the Dimensions database using the keywords "artificial intelligence" AND "stem education." The analysis reveals a significant increase in publications and citations in 2024 compared to previous years. The United States emerges as the leading country in the number of documents (9) and citations (103). China follows with five documents but no citations. The most cited authors include Nesra Yannier, Kenneth R. Koedinger, and Scott E. Hudson, each with 55 citations. The International Journal of Artificial Intelligence in Education is the most cited journal, with 55 citations. The most influential article, "Active Learning is About More Than Hands-On- A Mixed-Reality AI System to Support STEM Education," received 55 citations. Carnegie Mellon University stands out as the most cited institution, with 55 citations. The findings highlight the growing importance of AI in STEM education research, focusing on personalized learning, advanced analytics, and instructional automation, inspiring us all with the potential of AI to transform the future of education. This bibliometric analysis provides valuable insights for researchers, educators, and policymakers interested in the intersection of AI and STEM.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ibn:hesjnl:v:15:y:2025:i:1:p:69

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