Preparing Academically Talented, Low-Income STEM Students for Our Data-Intensive World

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With funding from the NSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program, this project will support high-achieving, low-income students with demonstrated financial need at St. Olaf College in Minnesota. Throughout its five years of funding, this project will provide 30 low-income students with approximately 85 annual scholarships. The Scholars will be undergraduates who are pursuing bachelor's degrees in mathematics or computer science. In addition to scholarships, this project will provide Scholars with critical academic and personal support, will enhance their skills in data science and statistics, and will expand their quantitative competency. As a result, it is expected that the Scholars will have expanded academic and career possibilities. This S-STEM project will recruit students during their first year of college and support them for up to three years. In addition to scholarships of up to $7,000 per year, a key component of the project is development of a new course that bridges the gap between the traditional first course in statistics (which is social sciences-based) and the first course in statistical modeling. This new course will introduce students to statistical computing and the core principles of data science, as they access and analyze real data to answer questions that they find to be personally compelling. The project also features Supplemental Instruction and extensive tutoring. The project will coordinate its efforts with St. Olaf College's TRIO programs, including the McNair Scholars Program. Participating students will also be recruited to join St. Olaf's Center for Interdisciplinary Research (DMS-1045015), which undertakes quantitative analyses guided by faculty from disciplines outside of the mathematical sciences. An advisory board consisting of individuals from area industries will help identify internship opportunities for Scholars and will support their entry into data-intensive careers after graduation. The project will assess the effectiveness of instruction and academic support strategies intended to increase persistence in data-intensive STEM fields. These findings will contribute to the national conversation about how best to support the success of STEM students from low income backgrounds.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.