This paper is from Session 3B: Randomisation and bootstrapping: the quick way to inference
which comes under Topic 3: Statistics education at the post-secondary level
Paper 3B2 (Monday 9th, 16:00-17:30)
Student Gains in Conceptual Understanding in Introductory Statistics With and Without a Curriculum Focused on Simulation-Based Inference
Presenter
- Beth Chance (Cal Poly San Luis Obispo, United States)
Co-authors
- Nathan Tintle (Dordt College, United States)
- Stephanie Mendoza (California Polytechnic State University, United States)
Abstract
Using “simulation-based inference” (SBI) such as randomization tests as the primary vehicle for introducing students to the logic and scope of statistical inference has been advocated with the potential of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Moving beyond the individual class activity, entirely revised introductory statistics curricula centering on these ideas have been developed and tested. In this presentation we will discuss three years of cross-institutional tertiary-level data in the United States comparing SBI-focused curricula and non-SBI curricula (roughly 15,000 students). We examine several pre/post measures of conceptual understanding in the introductory algebra-based course, using hierarchical modelling to incorporate student-level, instructor-level, and institutional-level covariates.