Generative artificial intelligence empowers mathematics teaching: value, misconceptions and strategies - Kamarudin, Nurzatulshima; Yang, Liu (Faculty of Educational Studies, UPM, 2025)
Breakthroughs in generative artificial intelligence have injected new momentum into mathematics education and triggered a rethinking of the nature of mathematics instruction. This article focuses on mathematics and systematically analyzes the educational value of generative artificial intelligence: reconstructing the goal system of mathematics education, promoting the development of critical thinking, and driving the transformation of mathematics classrooms. It also exposes current misconceptions: that artificial intelligence technology can replace teacher functions, that AI thinking capabilities are overestimated, and that long-term educational impact is neglected. It proposes practical strategies for mathematics instruction: promoting students' critical thinking through contextual creation; encouraging active inquiry to cultivate students' higher-order thinking skills; and acting as a proxy teacher to assist teachers in precise instruction.