- Prof Dev
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.
A fundamental aspect of statistical inference is representing real world data with statistical models. This paper analyzes students’ articulations of statistical models and modeling during their first steps in making informal statistical inferences (ISIs). An integrated modeling approach (IMA) was designed and implemented to help students understand the relationship between sample and population, and reasoning about models and modeling. In this case study, we explore the articulations made by three pairs of primary school students about what a model is and how they use models to understand random samples and make ISIs.