Research on the Construction of a Teaching Skills Training Model for Mathematics Teachers in the AI Era Based on Grounded Theory

The rapid advancement of artificial intelligence (AI) technology is comprehensively transforming the field of mathematics education, making the adaptive transformation of teachers’ teaching skills a key challenge. Based on grounded theory, this study interviewed 24 secondary school mathematics teachers and conducted classroom observations to construct a “Dual-Driven Three-Stage” model for training mathematics teachers’ teaching skills in the AI era. The research shows that: (1) The development of mathematics teachers’ skills is jointly driven by technological innovation momentum (e.g., the upgrading of AI tools) and professional internal drive (e.g., the continuous pursuit of teaching effectiveness); (2) Their growth path presents staged characteristics, including the Tool Adaptation Stage, the Teaching Integration Stage, and the Innovation Leadership Stage. Furthermore, accumulating more than 40 hours of AI application experience is identified as a critical milestone for breaking through stage barriers; (3) Given the logically precise nature of mathematics itself, teachers should cultivate the ability to “critically use AI tools” to meet the specific needs of mathematics teaching. Accordingly, a multi-level and multi-agent skill training plan has been formulated to provide theoretical support and operational guidance for the innovation of teacher education and school-based training activities.