Abstract: In teaching introductory and intermediate statistics at the undergraduate level, the content and pedagogy of “simulation-based inference” (e.g., bootstrapping and randomization tests) have been advocated (e.g., Cobb, 2007) with the goal of improving student understanding of statistical inference, as well as the statistical investigation process as a whole. Preliminary assessment data has been largely positive (e.g., Tintle et al., 2011; Tintle et al., 2012; Chance et al., 2016, Chance et al., in press). This talk will provide rationale and examples of the pedagogy and content approaches we advocate in first and second courses in statistics. Then, we will describe our assessment efforts based on data from scores of institutions across the country. In particular, we use multilevel models to explore the impact of student-level, instructor-level, and institution-level variables on pre/post measures of conceptual understanding for various curricula.
Zoom Meeting: https://illinois.zoom.us/j/81872836690?pwd=OEVHTmtvdHBObXE1MmtmaUFqNldpUT09
Meeting ID: 818 7283 6690