Mapping the Landscape of AI in Mathematics Education
Keywords:
Artificial Intelligence, Bibliometric, Mathematics EducationAbstract
This study presents a comprehensive analysis of the evolving landscape of Artificial Intelligence (AI) applications in Mathematics Education through a bibliometric analysis. Data for this research was gathered from the Scopus database, using the keywords "Artificial Intelligence" and "Mathematics Education" with the document types limited to articles published in English without restricting the publication timeline. The work systematically explores the development, thematic, methodological trends, geographical distribution, and citation impact of scholarly output in the interdisciplinary sphere of AI and Mathematics Education. The findings uncover a significant growth in literature over the years, indicating a heightened interest and increasing recognition of the importance of AI in enhancing teaching, learning, and assessment in Mathematics Education. The study also illuminates dominant research themes, influential publications, prolific authors, and active institutions contributing to this research domain. Our bibliometric analysis offers a valuable perspective for scholars, educators, and policymakers interested in understanding the trajectory of AI's role in Mathematics Education and provides a solid basis for future research directions in this vibrant and dynamic field.References
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