While core data science frameworks outline the content and skills that an undergraduate data science curriculum should include (Anderson et al., 2014; De Veaux et al., 2017; Danyluk et al., 2019), efforts to design introductory, interdisciplinary courses that foster broad data fluency are still emerging (Çetinkaya-Rundel & Ellison, 2020; Havill, 2019; Khuri et al., 2017). This NSF IUSE-CUE project was motivated by a desire for a computational social science-informed introduction to data science across multiple institutions to broaden student data science fluency. The resulting course, Computational Thinking with Data and Society, has been taught to over 300 students across five institutions nationwide, ranging from two-year to four-year colleges. In this poster, we first examine the design and implementation of one such course iteration at a large public R1 institution in California. We analyze anonymized student course data like Jupyter notebook assignments and weekly course feedback surveys. We focus on how the course effectively provides students with foundational programming concepts in preparation for future course work while simultaneously engaging students with social science lessons to target a myriad of data science applications.
Second, we share findings about the process of collaboratively designing an introductory undergraduate curriculum across institutions. At the project’s current stage, many lessons, projects, and assignments have been created and taught over the course’s multiple iterations to different cohorts of students. Due to the diversity of curricular materials developed, we began a curriculum, content and skill mapping project to catalogue and formalize what students are learning in each lecture, lab and discussion section. This process helps us review and improve all course materials, to identify the specific content areas for every aspect of the course, and to generate public-facing, modular versions of the course that can be readily shared to instructors nationwide.
http://orcid.org/0000-0002-3194-6822
University of California, Berkeley
[biography]
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