The ability to extract knowledge and insights from large datasets is increasingly important in science and the workforce. This project intends to address this need by educating scientists and mathematicians with computational skills needed to use large datasets to solve complex problems. Over five years, this project will provide four-year scholarships to fifteen low-income, high-achieving STEM undergraduate students with demonstrated financial need. The selected Scholars will be majors in biochemistry, biology, chemistry, environmental science, mathematics, physics, or statistics and data science. The project will develop four new courses to help students develop strong computational thinking and data visualization skills. Three new courses will introduce students early in their college career to interesting scientific problems that require analysis of complex data. A fourth new course will pair local businesses or non-profit clients with teams of third-year students and their faculty mentors. The teams will work to solve a client problem that requires computational approaches. Although only some students will receive scholarships, all math and science majors will have access to the new courses and support activities, including a career colloquium, undergraduate research, and a new Math and Science Problem Solving Lab. This access broadens the potential impact of this work to all STEM undergraduates at the University of Evansville.
The project's research goal is to assess the impact of an interdisciplinary, computation-focused learning community on low-income students. Data will be collected from formative and summative assessments of Scholars' academic performance, retention in STEM, and progression to STEM careers. This assessment will use an embedded, mixed-methods study design to understand participant views throughout their college years. The summative data from Scholars will be compared to that of non-participating STEM majors. This analysis will contribute to understanding how participation in a combination of activities including career events, undergraduate research, and computational problem-solving affect students' career goals and self-efficacy. This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income, academically high-achieving students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future scientists, engineers, and technicians, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.
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.
