Emergent statistical modeling: elementary school students’ transitioning from modeling of data to modeling for statistical reasoning

As data proliferates in all aspects of human activity, nurturing young students’ statistical reasoning has become an essential educational pursuit. A central challenge is that formal engagement with statistical practices relies on notation systems and representational forms that are typically introduced only later in schooling, if at all. Building on the emergent modeling theoretical framework, which emphasizes learners’ progressive use of informal resources in developing more formal reasoning, this study examines how emergent modeling can unfold in statistical contexts. The paper conceptualizes what emergent statistical modeling may entail with particular attention to how students develop coordination between pattern and variation. An illustrative case study of a pair of sixth-grade students is presented, tracing their modeling progression across a sequence of real-world data exploration and probability modeling activities. The analysis highlights a consequential transition in the students’ use of invented models, from serving as models of a specific phenomenon to functioning as models for more general statistical reasoning. The case serves as a proof of concept for how young students can express sophisticated statistical considerations while working exclusively within informal notation systems, and for how such instructional contexts can make these transitions visible and analyzable.