Eberly Center

Developing an assessment for concepts in introductory statistics and data science

Burckhardt, P., Elliott, P., Evans, C., Lin, K., Luby, A., et al.

Dietrich College is revising its general education curriculum to emphasize data literacy across disciplines. As we revise our statistics and data science courses to improve student learning, it’s important to measure their learning and experimentally assess new teaching methods and course designs. We present an approach faculty can use to design better assessment tools to revise their courses and test interventions. We illustrate this approach with results from introductory statistics.  In Spring 2018, we conducted 33 think-aloud interviews in which students narrated their reasoning as they answered draft questions. The interview results helped us revise unclear questions, suggested topics for new questions, showed when students used irrelevant details to choose answers, and revealed student misconceptions of which we were previously unaware. In Fall 2018, we are administering the revised assessment to two introductory statistics courses. We will present results from think-aloud interviews and preliminary analyses of assessment data.

Philipp Burckhardt, Statistics & Data Science DC

Peter Elliott, Statistics & Data Science DC

Ciaran Evans, Statistics & Data Science DC

Kevin Lin, Statistics & Data Science DC

Amanda Luby, Statistics & Data Science DC

Sangwon Hyun, Statistics & Data Science DC

Christopher Peter Makris, Statistics & Data Science DC

Mikaela Meyer, Public Policy & Management Heinz

Josue Orellana, Center for the Neural Basis of Cognition DC

Gordon Weinberg, Statistics & Data Science DC

Jerzy Wieczorek, Mathematics and Statistics Colby College

Ronald Yurko, Statistics & Data Science DC

Rebecca Nugent, Statistics & Data Science DC

Alex Reinhart, Statistics & Data Science DC