Developing a Hands-on Data Science Curriculum for Non-Computing Majors

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This project aims to serve the national interest by addressing the particularly high national demand for data scientists, which is estimated to grow much faster than the average for all occupations between 2018 to 2028. Moreover, recent national challenges have highlighted the nation’s ongoing need for data scientists who can rapidly create actionable results from unprecedented amounts of data being generated in various fields. Computing and mathematics departments in colleges and universities across the U.S. have increased their efforts to provide data science content for their own undergraduate majors, but typically in their senior year. This project aims to develop a data science curriculum that can attract non-computing majors. Such an option does not require a long prerequisite chain of courses in programming, data structures, and introductory databases, as well as relevant mathematics. By directly addressing this challenge of broadening the early engagement of all students in data science, this project will create a hands-on curriculum that will make learning more readily-accessible to non-computing majors.The project’s overarching goal is to introduce a data science curriculum appropriate for non-computing disciplines by strengthening data science components in existing Computer Science Principles (CSP) courses and providing a follow-on Data Science Principles (DSP) course. The project’s intellectual merit stems from its two major deliverables. First is a web-based Data Science Learning Platform (DSLP) for students to obtain hands-on practice with processing and analyzing data without needing to write code. Second is a Data Science Curricular Module (DSCM) to teach data science concepts both in the DSP and CSP courses. These deliverables will be developed and refined over the course of the project. As part of the project’s broader impacts, the proposed DSCM will be taught to non-computing majors in CSP and DSP classes during the second and third year of the project. Additionally, to increase the project’s impact, results will be disseminated through publications and presentations delivered at conferences attended by both college and high school teachers. In particular, workshops will be organized for instructors at other institutions to facilitate the adoption of the project-developed curriculum to benefit students across the nation, thus helping to address the national demand for data scientists. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.