NSF AI Disclosure Required
NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
EAGER: Narrating the experiences of low-income engineering students and their traditional and chosen families
NSF
About This Grant
This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by conducting research that will inform practices to strengthen the retention and graduation of high-achieving, low-income students. Low-income students struggle to navigate engineering programs, leading to increased underrepresentation of the population. This struggle is, in part, because of the difficulties or strains low-income students encounter in their daily lives and the ways those strains influence their feelings of belonging. Past research finds it increasingly important to understand what role low-income engineering students’ traditional (e.g., assigned at birth; parents, siblings, etc.) and chosen families (e.g., the family they choose; peers, teachers, etc.) play in easing the strains on low-income students. Ultimately, low-income students' familial support may influence their ability to succeed in engineering. Similar research has found that the strains impacting low-income students, and other strains, may impact the students’ families too, making families’ ability to support their low-income students more strenuous. This project explores what strains families of low-income students experience and what impact those strains ultimately have on students' feelings of belonging. Understanding this impact on student belonging can help researchers and practitioners better support low-income students and their families, likely leading to greater enrollment and persistence in engineering programs. The overall goal of this project is to increase STEM degree completion of talented, low-income undergraduates in engineering degree programs by investigating the research question: In what ways do the bequeathed strains of socioeconomically disadvantaged students' families impact socioeconomically disadvantaged students' engineering belonging? This exploratory project will collect and retell the stories of twelve low-income students' experiences in engineering, as well as up to ten of each of their family members. These students will be recruited from pre-existing S-STEM programs. Story collection and retelling will focus on low-income students' experiences in engineering, with particular emphasis on identifying who supported their belonging trajectories and how. Family members will provide supplemental narratives that describe what it is like to support a low-income student including what joys and strains come with that support. A case study narrative approach encapsulates both the stories of students and their families, allowing for both a student- and population-level analysis of participants' stories. Resulting narratives and cases will be used to identify what strains families of low-income students experience and, ultimately, how such strains influence the belonging of the students they support. This work supports broader discussions regarding the inclusion of low-income students in engineering. 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.
Focus Areas
Eligibility
How to Apply
Up to $299K
2027-01-31
One-time $749 fee · Includes AI drafting + templates + PDF export
AI Requirement Analysis
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.