Contributed Paper C211
Secondary Teachers’ Understanding of Statistical Modeling After Teaching a Simulation-Based Statistical Inference Course
AuthorsMichael Huberty (USA)
Nicola Justice (USA)
Andrew Zieffler (USA)
Robert delMas (USA)
PresenterMichael Huberty (United States)
In the last decade, 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 had one year of experience teaching an undergraduate-level simulation-based introductory statistics course (the CATALST curriculum). The results suggest that teachers were able to use the simulation-based methods effectively yet had several misconceptions that we posit carried over from their minimal formal non-simulation-based statistical education. This research has implications for the professional development of instructors who plan to teach using simulation-based methods.