Statistical modeling to promote students’ aggregate reasoning with sample and sampling.

Proceedings of the Tenth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL10)
Aridor, K., & Ben-Zvi, D.
University of Auckland.
Rotrua, New Zealand

Helping students develop an aggregate view of data is a key challenge in statistics education. It has been suggested that modeling pedagogy can address this challenge (Lehrer & Schauble, 2004). In this paper we present a case study – part of a UK-Israel research project – that aims to examine how students’ reasoning about modeling of a real phenomenon can support the emergence of aggregate view of data, in the context of making informal statistical inferences. We focus on the emergent reasoning of two fifth-graders (aged 10) involved in statistical data analysis and modeling activities using TinkerPlots2. We describe the students’ articulations of aggregate view of data as they: 1) explore a small sample; 2) plan and construct a model that represents the investigated phenomenon and make predictions about ‘some wider universe’; and 3) generate random samples from this model to examine its representativeness. This paper aims to contribute to the study of models that young students can understand and use to develop their aggregate view of data. Keywords: Exploratory data analysis, informal statistical inference, aggregate view of data, statistical model, statistical modeling. 

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education