AI in mathematics education: A bibliometric analysis of global trends and collaborations (2020-2024)
Hassan Hossein-Mohand, Hossein Hossein-Mohand, Verónica Albanese, María del Carmen Olmos-Gómez
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.