A bibliometric analysis on artificial intelligence in mathematics education

Abstract

The research on artificial intelligence in mathematics education has attracted much attention from researchers since the last decade. Thisstudy aims to provide holistic information about artificial intelligence in mathematics education research using bibliometric analysis. Data for the analysis were extracted from the Scopus database from 1986 –2023. The analysis, conducted using R-packages (Bibliometrix) and VOSviewer software, identifies the relevant nations, affiliations, journals, articles, and keywords on artificial intelligence in mathematics education research. The study reveals that 565 documents have been published in 354 journals,with an average annual growth rate of 11.27%. These documents, on average, have received 14.61 citations each. The research field has engaged a total of 1,847 authors, with an average of 3.26 authors contributing to each document. Additionally, 17.17% of these publications involved international co-authorship, indicating a moderate level of global collaboration. Our findings reveal a growing interest in using artificial intelligence as an educational tools and methods, particularly in the United States andChina, which lead in publication output and citations. The analysis also reveals emerging trends and research gaps. The keywords such as "virtual reality," "sustainable development," and "COVID-19" reflect recent research focus on artificial intelligence in mathematics education research. Meanwhile, the keywords such as "mathematical literacy," “assessment,” and "gamification" identified as underexplored areas, suggesting potential opportunities for future research on artificial intelligence in mathematicseducation research.