Bibliometric Analysis of Artificial Intelligence in STEM Education

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.

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Institutions

Publication Details

Journal
Higher Education Studies
Published
2024-12-01
DOI
https://doi.org/10.5539/hes.v15n1p69
Citations
5
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
3.90
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article

Bibliometric Analysis of Artificial Intelligence in STEM Education

Thada Jantakoon, Kitsadaporn Jantakun, Thiti Jantakun
5 citations
Higher Education Studies
Engineering Education and Technology
3.90
article

Bibliometric Analysis of Artificial Intelligence in STEM Education

Thada Jantakoon, Kitsadaporn Jantakun, Thiti Jantakun
article en
5 citations

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.

Higher Education StudiesVol. 15(1)
Roi et Rajabhat University (TH), Rajabhat Maha Sarakham University (TH)
Openalex Percentile: Top 5%
Engineering Education and Technology
3.90
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Bibliometric Analysis of Artificial Intelligence in STEM Education — Thada Jantakoon, Kitsadaporn Jantakun, et al. · Higher Education Studies (2024) | TGRS Research Map | TGRS