AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024)

Hassan Hossein-Mohand; Hossein Hossein-Mohand; Veronica Albanese; María del Carmen Olmos Gómez

doi:10.29333/ejmste/15915

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Hassan Hossein-Mohand ¹ , Hossein Hossein-Mohand ¹ , Veronica Albanese ¹ ^* , María del Carmen Olmos Gómez ¹

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¹ Universidad de Granada, Granada, SPAIN^* Corresponding Author

Abstract

This bibliometric study analyzes the scientific production on the use of artificial intelligence (AI) in mathematics education between 2020 and 2024. Based on a sample of 384 documents extracted from 155 international sources, the study evaluates emerging trends, collaboration patterns among authors and countries, and the main themes related to the use of AI in mathematics education. The analysis was conducted using the Biblioshiny tool in RStudio, generating network maps and thematic graphs that visualize the relationships between keywords and international collaborations. The results show that China and the United States lead in terms of scientific productivity and international collaboration. A growing interest in the use of generative AI emerges, including deep learning and ChatGPT, in educational contexts for the purpose of assessment of learning. The present study provides a clear overview of current dynamics in AI research in mathematics education, highlighting opportunities for interdisciplinary collaboration.

Keywords

mathematics education
artificial intelligence
machine learning
collaboration networks
emerging trends

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Review Article

EURASIA J Math Sci Tech Ed, Volume 21, Issue 2, February 2025, Article No: em2576

https://doi.org/10.29333/ejmste/15915

Publication date: 02 Feb 2025

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Article Downloads: 50

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How to cite this article

APA

Hossein-Mohand, H., Hossein-Mohand, H., Albanese, V., & Olmos Gómez, M. D. C. (2025). AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024). Eurasia Journal of Mathematics, Science and Technology Education, 21(2), em2576. https://doi.org/10.29333/ejmste/15915

Vancouver

Hossein-Mohand H, Hossein-Mohand H, Albanese V, Olmos Gómez MDC. AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024). EURASIA J Math Sci Tech Ed. 2025;21(2):em2576. https://doi.org/10.29333/ejmste/15915

AMA

Hossein-Mohand H, Hossein-Mohand H, Albanese V, Olmos Gómez MDC. AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024). EURASIA J Math Sci Tech Ed. 2025;21(2), em2576. https://doi.org/10.29333/ejmste/15915

Chicago

Hossein-Mohand, Hassan, Hossein Hossein-Mohand, Veronica Albanese, and María del Carmen Olmos Gómez. "AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024)". Eurasia Journal of Mathematics, Science and Technology Education 2025 21 no. 2 (2025): em2576. https://doi.org/10.29333/ejmste/15915

Harvard

Hossein-Mohand, H., Hossein-Mohand, H., Albanese, V., and Olmos Gómez, M. D. C. (2025). AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024). Eurasia Journal of Mathematics, Science and Technology Education, 21(2), em2576. https://doi.org/10.29333/ejmste/15915

MLA

Hossein-Mohand, Hassan et al. "AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024)". Eurasia Journal of Mathematics, Science and Technology Education, vol. 21, no. 2, 2025, em2576. https://doi.org/10.29333/ejmste/15915