AI in mathematics classrooms: a synergistic strategy for diversity and inclusivity

Despite growing emphasis on inclusive education, mathematics classrooms still exhibit disparities arising from cognitive, linguistic, socioeconomic, and systemic barriers, marginalizing diverse students and limiting equitable learning opportunities. Artificial intelligence (AI) presents considerable potential for addressing these challenges. This study investigates how AI technologies can be harnessed to create mathematics classrooms that are inclusive and adaptive to individual student needs. Anchored in Universal Design for Learning (UDL) and the Substitution, Augmentation, Modification, Redefinition (SAMR) frameworks, the study explores how AI functionalities can facilitate personalized learning, responsive instruction, and equitable participation. The study employs a hybrid conceptual–structured narrative review approach, synthesizing existing literature through structured searching, screening, thematic coding, and conceptual integration. The synthesis examines AI functionalities, inclusive pedagogical affordances, implementation challenges, ethical and equity concerns, and future directions. On this basis, the study develops the Synergistic AI-Inclusive Mathematics Education (SAIME) framework, conceptualizing UDL as an inclusion-oriented design foundation, SAMR as a technological transformation pathway, and teacher-mediated pedagogy and ethical safeguards as essential conditions for equitable outcomes in access, participation, and achievement. It concludes that AI can contribute meaningfully to inclusive mathematics education when its technological affordances are purposefully aligned with inclusive pedagogy, ethical and equity safeguards, and equitable learning goals.