Student Gains in Conceptual Understanding in Introductory Statistics with and without a Curriculum Focused on Simulation-Based Inference
Year: 2018
Type: article
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.
Authors: Beth Chance, Stephanie Mendoza, Nathan Tintle
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W3126094328