Contributed Paper C211
Secondary teachers’ understanding of statistical modeling after teaching a simulation-based statistical inference course
AuthorsMichael Huberty (University of Minnesota, USA)
Nicola Justice (Pacific Lutheran University, USA)
Andrew Zieffler (University of Minnesota, USA)
Robert delMas (University of Minnesota, USA)
PresenterMichael Huberty (United States)
Simulation-based methods for teaching statistical inference have been touted as effective for helping students develop authentic understanding of statistical modeling and inference. This research used problem-solving interviews designed to explore teachers' understanding of statistical models and the connections between model, study design, data, and inference. The interviews were conducted with four secondary teachers who were teaching an undergraduate-level simulation-based introductory statistics course to secondary students. The results suggest that these teachers were able to use the simulation-based methods effectively, yet had several misconceptions that may stem from their non-simulation-based statistics education. This research has implications for the professional development of instructors who plan to teach statistics using simulation-based methods.