Scholarship project supporting undergraduate and graduate students at the interface between biology and data science

This project will contribute 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 Hawai'i at Manoa (UHM), a Native Hawaiian-serving institution. Over its 5-year duration, this project will fund scholarships for up to three years to 67 unique full-time students (30 undergraduates, 22 Masters and 15 PhD students) who are pursuing degrees in S-STEM-eligible bioscience disciplines.

Hawai'i’s unique biodiversity and ecosystem, its unique human diversity, and the pressing challenges it faces in health equity, sustainability and conservation make the State a rich environment for bioscience research and careers. These careers are becoming increasingly reliant on the use and analysis of large datasets, creating the need for enhanced professional preparation in data science (DS) to improve the competitiveness and employability of bioscience graduates.

However, financial constraints limit participation of low income, marginalized, and minoritized students in STEM degrees and, critically, in enrichment programs that build skills in areas such as data analytics. This project integrates scholarship support and an inclusive Data Science Community of Practice (COP) program to address these significant challenges.

The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. This scholarship project will work at the interface between biological sciences and data science to promote student access, inclusion and competitiveness through two Specific Aims: (1) Provide transformative financial support for academically talented undergraduate (UG) and graduate (GR) bioscience students with unmet need at UHM.

Financial constraints are exclusionary in terms of both student access and success, since low-income students who work extensively to finance their studies suffer from time poverty and decreased ability to participate in enrichment experiences that promote retention and attainment. The project will provide tuition scholarships to 67 unique bioscience undergraduates and graduate students with GPAs>3.0 and unmet financial need. (2) Deploy an evidence-based, context specific intervention comprising a transdisciplinary Data Science Community of Practice.

Students will join the Hawai'i Data Science Institute (HI-DSI) ‘Data Fellows’ enrichment program at UHM to build skills in data science and to thrive as part of an inclusive program with strong faculty and peer mentoring. The project intends to research the efficacy of the planned intervention on students’ knowledge, skills and self-efficacy in data science and measure improvements in student retention and graduation rates associated with project participation.

Project accomplishments and research findings will be disseminated through both the scientific literature and conference presentations and to institutional, regional and national stakeholders through outreach materials and social media. 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.

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.