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2E: Exploring student approaches to model construction in a simulation-based inference curriculum


With Jason Dolor, Kit Clement, Andrew Zieffler, Jennifer Noll, & Dana Kirin (Portland State University)


Abstract

Experts in the field of statistics education have highlighted the merits of a simulation-based approach to teaching inference in introductory statistics, but doing so puts a renewed emphasis on understanding the statistical model used to simulate data. Unfortunately, many students have limited experience working with statistical models. In this session, we will present an activity from an introductory statistics curriculum taught using the approach of modeling and simulation. During the session, we want participants to have an opportunity to work through and discuss the modeling aspect of a statistical process and come to understand its role in deepening students’ statistical knowledge. We will be sharing student work on modeling a statistical inference problem using TinkerPlots to see what aspects of the context students value when they generate their personal models and then discuss what challenges and opportunities might emerge from implementing a modeling activity for current and future statistics teachers.