Performing Meaningful Assessment in a Modernized Mathematical Statistics Course Sequence


Peter Freeman (Carnegie Mellon), Jennifer Green (Michigan State University), Erin Blankenship (University of Nebraska-Lincoln)


Abstract

Modernizing the content of the canonical calculus-based mathematical statistics sequence is necessary to improve the training of modern statisticians and data scientists. But how can we also modernize assessment in those courses and explore the impact of course-content changes on student learning? The GAISE recommendations highlight the importance of assessment both for evaluating and improving student learning and in the mathematical statistics sequence, we can achieve both goals by focusing on conceptual understanding. In this workshop, we will share examples of low- and high-stakes assessments we have used that challenge students to think in novel ways. We will also discuss strategies for designing assessments, and attendees will practice transforming their own assignments to include a focus on conceptual understanding. By the end of the session, participants will have lots of different assessments they can adapt and use to drive the modernization of their own courses!


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