Preservice mathematics teachers’ noticing in AI-based simulations: transitions among attending, interpreting, and shaping

Abstract

Teacher noticing is a key component of teacher competence, referring to how teachers attend to, interpret, and shape classroom interactions to gain access to students’ thinking. However, less is known about how these dimensions are coordinated during ongoing interaction. This study addresses this gap by conceptualising noticing as an iterative and interactional process and examining transitions among noticing dimensions within AI-based simulations. Seventeen preservice mathematics teachers participated in a three-week intervention involving text-based interactions with AI-simulated students and mentor feedback. Data were analysed using qualitative coding and Epistemic Network Analysis. Findings show that noticing was organised through recurring transitions among attending, interpreting, and shaping. Strong connections between interpreting and shaping suggest that PTs’ interpretations frequently informed subsequent inquiry moves that generated new opportunities for noticing students’ thinking. Differences across weeks further indicate the situated and context-sensitive organisation of noticing within AI-based interactions. The study contributes to demonstrating how AI-based simulations can support and make visible the iterative coordination of noticing dimensions in teacher education.