S-STEM: Attracting and Cultivating AI Scholars through Multi-faceted Mentoring, Research Experiences, and Cohort Building
- Institution
- University of North Texas, TX
- Principal investigator
- Xiaohui Yuan
- Funding
- $2.0M
- Duration
- 2025–2030
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Abstract
This S-STEM project at the University of North Texas (UNT) will contribute to the national need for well-educated computing professionals by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need. Over a six-year duration, 30 scholars in three cohorts, pursuing degrees in the Department of Computer Science and Engineering at the UNT, will receive support for up to three years. The goal of this project is to increase the retention and graduation rates by 20%. To achieve this goal, the project team will develop, adapt, and integrate a suite of programs to recruit, support, and prepare students to enter the workforce by leveraging strong support from the institution and industrial partners. Existing programming at the UNT will provide students with multi-faceted mentoring, cohort, and research experiences. The project will identify (1) the influential factors to students' decision to pursue a computing degree and continuing to graduation; (2) the effect of AI-focused programs and multi-faceted mentoring on the academic success and persistence of students; and (3) effective strategies to prepare students ready for a successful career in a STEM field. This project is funded by NSF's Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of academically talented low-income 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. 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.
Research team
- Xiaohui YuanPI
- David M Keathly
- Xuan Guo
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