Seri Mutiara Primary School, Johor Bahru, Malaysia

Abstract: Educational digital transformation has become the core agenda of global basic education reform, and artificial intelligence technology is reshaping the teaching paradigm of mathematics classrooms at an unprecedented speed. Taking primary school mathematics teaching in Malaysia as the research context, this study systematically explores the theoretical basis, practical paths, and rational boundaries of AI-empowered primary mathematics teaching based on national policy frameworks including the National Artificial Intelligence Roadmap (2021–2025), Digital Education Policy, and the Ministry of Education Strategic Plan (2024–2030). This paper proposes a three-in-one AI teaching application framework of “intelligent diagnosis – precise adaptation – dynamic feedback” and elaborates on three dimensions: the construction of personalized learning paths, the reconstruction of contextual teaching scenarios, and the upgrading of teaching evaluation systems. The research finds that AI technology can effectively resolve three core contradictions in traditional mathematics teaching: the conflict between unified teaching progress and individual student differences, the barrier between abstract mathematical concepts and concrete cognitive understanding, and the imbalance between result-oriented evaluation and process-oriented teaching attention. Nevertheless, technological application must adhere to the fundamental principle of “assistance rather than substitution” and prioritize the development of students’ mathematical thinking. Combining front-line teaching practices and localized cases in Malaysia, this study provides operable practical paths for primary school mathematics teachers to transform from “technology users” to “intelligent facilitators” in the digital era.

Keywords: artificial intelligence; primary school mathematics; educational digitalization in Malaysia; personalized learning; teacher professional development