Culturally Sustaining Evaluation of AI-Generated Curricula in Mathematics Teacher Education

Source abstract

This chapter examines how mathematics teacher education can prepare pre-service teachers to critically evaluate the cultural, pedagogical, and epistemic quality of AI-generated curriculum materials. It presents a design case based on a four-phase instructional module developed for an undergraduate mathematics methods course at a public university in Central Anatolia, Türkiye. The chapter introduces the Cultural-Cognitive Task Evaluation (CCTE) framework, including a nine-dimension task-quality guide and an AI-provenance and reliability checklist, as an instructional heuristic rather than a validated instrument. It explains the theoretical basis of the framework, documents the module's development across three course offerings, and provides course artifacts and a worked example tracing an AI-generated task from prompt to revision. This chapter, per the authors, does not claim measured learning gains or comparative effectiveness; instead, it offers a transparent design rationale and identifies priorities for future validation and empirical research.