NSF Award
2424954
This project contributes to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at the University of Utah. The University of Utah is the flagship, doctoral-granting, research-intensive institution leading the Responsible AI initiative in the state of Utah. Over its six-year duration, this project seeks to fund two-year scholarships for 31 unique full-time students who are pursuing graduate degrees at the Master and Doctoral levels in NSF-supported STEM fields of Cognitive/Neuroscience, Geography, Sociology, Anthropology, Economics, and Human Developmental Sciences, and Statistics. The project aims to build an interdisciplinary talent pool of graduate students seeking careers with data science and analytics skills to meet workforce needs in the United States. Using a cohort-based model and proseminar format, the project intends to adapt mentorship strategies to promote success, develop workshops to democratize data access and analysis, and engage in industry partnerships to promote the professional formation of graduate students. A significant outcome of this project is the contribution of new knowledge to gaps in our understanding of the academic, social, and institutional factors that promote the success of diverse low-income graduate students in data science programs. The broader impacts of this project include the dual goals of increasing access to advanced degree opportunities for low-income graduate students and serving the diverse needs of the regional and national workforce. <br/><br/>The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. The three specific aims of the program include: 1) preparing students with hands-on skills in data science, statistics, visualization, and data management, 2) using an asset-based approach to support the holistic success of low-income graduate students, with targeted outreach to, and support for, student veterans and 3) providing graduate students with career placement guidance, internships, and job preparation. We expect to find that holistic mentorship supports graduate student resilience and addresses emotional regulation throughout their graduate trajectories in response to stressors. The project seeks to also lead to new knowledge about workforce development for data science career placement among graduate students including student veterans. This project intends to leverage a Federal Research Data Center to empower students to identify, use, and link large datasets to address the grand challenges of today and the future. Scholars should benefit from interdisciplinary "methods labs" that seek to advance innovation in research question development and from emergent applications for artificial intelligence (AI) in big data sets. A professional evaluator brings the expertise needed to provide formative feedback iteratively so adjustments can be made to ensure timely progression toward the project’s aims. The project team leaders intend to disseminate findings via traditional (conference and journal) and electronic (podcasts and social media) modes of communication, including a scholars web portal. Consistent with other narrative approaches that feature student success at the University of Utah, the project team aims to produce short documentaries for dissemination to be featured via social media and on the Scholars website. 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 talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students.<br/><br/>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.
