Abstract* Background Research on Artificial Intelligence (AI) and Intelligent Tutoring Systems (ITS) in mathematics education has expanded rapidly over the past two decades, reflecting broader advances in machine learning, learning analytics, and generative AI. However, a comprehensive overview of publication trends, thematic structures, and collaborative patterns specific to mathematics education remains limited. Methods This study employed a bibliometric approach guided by the PRISMA protocol to systematically analyze research on AI and ITS in mathematics education published between 2001 and 2025. A total of 237 peer-reviewed journal articles and conference papers indexed in Scopus were identified, screened, and included. Bibliographic data were analyzed using the Bibliometrix R package to examine annual publication growth, author productivity, international collaboration networks, and thematic evolution through keyword co-occurrence and thematic mapping techniques. Results The findings indicate that research output grew slowly during the early 2000s but increased markedly after 2019, aligning with the global surge in interest in machine learning, large language models, and generative AI. Author productivity followed a typical long-tail distribution, with a small group of core authors contributing consistently over time. International collaboration was evident but uneven, dominated by a limited number of countries. Thematic analysis revealed two enduring pillars of the field: pedagogical approaches in mathematics education and technology-driven instructional systems. Emerging themes, including federated learning and adversarial machine learning, point to rising attention to privacy, security, and robustness in adaptive learning environments. STEM education and generative AI have also gained prominence in recent years. Conclusions The evolution of research on AI and ITS in mathematics education reflects a clear paradigm shift from traditional instruction toward adaptive, data-driven, and intelligent learning systems. While technological innovation continues to accelerate, the findings highlight the critical role of teachers’ pedagogical readiness in ensuring that AI-enhanced mathematics education remains effective, inclusive, and sustainable.
Kuncoro et al. (Fri,) studied this question.