Co-Teaching with AI: Shift Pedagogy, Opportunities, and Challenges in Mathematics Education

Abstract

The growing use of artificial intelligence (AI) in education has shifted attention from technology adoption to changes in teaching practice, particularly in mathematics classrooms where instruction depends on diagnosis of misconceptions, responsive support, and pedagogical decision-making. Although existing studies report benefits such as personalised learning, real-time feedback, adaptive instruction, and support for lesson design, they also identify concerns related to teacher agency, curriculum alignment, preparedness, and ethics. Yet this literature remains fragmented, with limited synthesis of how AI functions within teaching processes. This study addressed that gap through a PRISMA-guided systematic literature review of 31 studies published between 2022 and 2025, identified through Scopus, Web of Science, ERIC, and Google Scholar. The included studies covered varied contexts and research designs and were analysed using thematic synthesis. Coding and interpretation were organised around four dimensions: pedagogical shifts, instructional opportunities, implementation challenges, and ethical concerns. The review found that AI is increasingly positioned as a teaching support that influences how teachers plan, adapt, and mediate instruction. Across the studies, teachers were described as taking on expanded roles in facilitating learning, coordinating AI-supported activities, interpreting student data, and monitoring the appropriateness of AI-generated outputs. AI was associated with opportunities for more responsive and differentiated instruction, but these were shaped by teacher readiness, pedagogical fit, and institutional support. The review also identified continuing challenges related to over-reliance, workload, limited contextual flexibility, bias, privacy, transparency, and accountability.