Keywords
mathematics teacher education
adaptive learning
conversational agents
ethical considerations
How to Cite
Abstract
Artificial intelligence (AI) is significantly reshaping mathematics teacher education by introducing innovative tools that enhance instructional design, promote personalization, and increase student engagement. This integrative review synthesizes recent research to identify key trends, opportunities, and challenges associated with AI integration in mathematics teacher education. Findings indicate a growing but inconsistent adoption among educators, highlighting the potential of conversational tools such as ChatGPT and adaptive learning systems to support personalized and inclusive instruction. AI-driven responsive teaching simulations, innovative task design, and advanced assessment practices further illustrate opportunities for enhancing preservice teachers' adaptive, student-centered teaching competencies. Beyond efficiency gains, AI tools also foster teacher agency and reflective practice in the design of adaptive and equitable mathematics instruction. Nevertheless, considerable challenges persist, including widespread teacher AI literacy gaps, ethical concerns surrounding data privacy, algorithmic bias, and transparency, as well as pedagogical risks related to automation and superficial learning. Additionally, persistent usability and design limitations complicate effective AI implementation. The review underscores the importance of developing targeted professional development frameworks, promoting theory-driven research, and establishing comprehensive policy guidelines. Recommendations emphasize embedding critical reflection and AI literacy within teacher training, advancing human–AI collaborative frameworks, and ensuring clear ethical standards. This synthesis provides educators, policymakers, and researchers with a robust, evidence-based foundation to effectively leverage AI's transformative potential while safeguarding educational integrity in mathematics teacher education.
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