Abstract

This presentation examines the specialized knowledge for teaching statistics mobilized by K–3 teachers during a Lesson Study process focused on the development of informal inferential reasoning. The study adopts a qualitative, interpretive case study design in which a group of early primary teachers collaboratively design, implement, and reflect on lessons aimed at fostering informal inferential reasoning in young students. Using the Statistics Teacher Specialized Knowledge (STSK) framework as the primary analytical lens, the research characterizes the knowledge subdomains, including KoT, KSS, KPS, KFLS, KST, and KSLS, that emerge across the Lesson Study cycle. Data sources include transcripts of collaborative meetings, lesson recordings, planning documents, and reflective notes. A distinctive methodological feature of the study is the incorporation of a large language model through zero-shot prompt engineering as a complementary tool in the qualitative coding process, whose outputs are compared with specialist coding using inter-rater agreement metrics. Preliminary findings indicate a strong presence of pedagogical content knowledge, particularly knowledge of students’ thinking and of teaching strategies, and reveal meaningful articulations between statistical content knowledge and pedagogical knowledge in teachers’ discourse. The study also opens questions about the potential and limitations of language models as analytical aids in educational research.