2C: Engaging students in data science with authentic data (Room 108)


Sheri E. Johnson (The Mount Vernon School), Merve Kursav (Dartmouth College), Scott Pauls (Dartmouth College), Christine Franklin (American Statistical Association)


Abstract

Our session will start with an exploration of the DIFFUSE module Examining the Racial, Environmental, and Economic Influences on COVID-19 Mortality in Louisiana. DIFUSE is an NSF-funded project aimed to support college instructors to incorporate data science modules into their curriculum. The modules are a flexible and reusable set of tools and methods for faculty to enrich learning objectives through hands-on exploration of data collection, analysis, and visualization. We selected this module to pilot in a private high school statistics classroom because it requires limited prerequisite data science knowledge. You will have time to explore the Environmental Studies 3 Module, create a hypothesis and analyze the data. The module is well aligned with the learning objectives of the course and requires students to (1) create hypotheses and causal conjectures linking demographic variables and environmental factors, (2) analyze and visualize data, and (3) communicate their results. In this study, we aimed to investigate changes in students’ knowledge, perceptions, attitudes, and skills after and before engaging with the data science module. Students completed a pre-and post-survey and we will share the results. We will provide you with examples of student work to review and also discuss how this lesson aligns with the recommendations of the Pre-K-12 GAISE II Report. We will gather your feedback through some brainstorming questions to learn your thoughts and reactions to both the module and student work.

 

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