UROP Research Mentor Project Submission Portal: Submission #1075
Submission information
Submission Number: 1075
Submission ID: 19971
Submission UUID: 0eece7c8-ce53-46a8-8494-bfe98643e2d9
Submission URI: /urop-research-mentor-project-submission-portal
Submission Update: /urop-research-mentor-project-submission-portal?token=ejLfwpTpQta1G22NiTg05xGclBIawN_uwq1-DVJPWlY
Created: Mon, 08/04/2025 - 03:35 PM
Completed: Tue, 08/05/2025 - 05:18 PM
Changed: Thu, 10/16/2025 - 01:06 PM
Remote IP address: 128.186.137.62
Submitted by: Anonymous
Language: English
Is draft: No
Webform: UROP Project Proposal Portal
Submitted to: UROP Research Mentor Project Submission Portal
Research Mentor Information
Dinara Ibrayeva
she/her
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Graduate Student
Dr. Patrice Iatarola
Education, Health, and Human Sciences
ELPS
Additional Research Mentor(s)
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Overall Project Details
***Understanding the Impact of Losing Merit-Based Financial Aid on College Students: A Multi-Method Study
Higher Education, Education Policy, Literature Review, AI tools for Research.
No
2
Ideal for students interested in education policy, economics, sociology, social work, political science, psychology, creative writing, or those with an interest in using research for access and success in higher education.
On FSU Main Campus
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Partially Remote
5
Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
This project supports a dissertation investigating the consequences of losing financial aid among undergraduate students. The project consists of three interconnected essays, each using a different methodological lens:
Descriptive and Regression-Based Quantitative Essay – This essay analyzes data to describe who loses financial aid and estimate the correlates of continued enrollment and academic success after aid loss.
Quasi-Experimental Essay – This essay applies causal inference methods (e.g., difference-in-differences or regression discontinuity) to estimate the effect of financial aid loss on students’ academic momentum, retention, and graduation outcomes.
Qualitative Case Study – This essay explores how students make sense of losing aid, drawing on in-depth interviews and institutional context to understand their strategies and challenges.
Undergraduate researchers will assist in building the literature review foundation for all three essays, focusing on: 1) Financial aid policies and merit-based funding; 2) Academic momentum and persistence; 3) Equity and access in higher education; 4) Student coping mechanisms and institutional support.
The project integrates FSU-approved and funded Generative AI (GenAI) and literature organizer tools, including Co-Pilot, Zotero, Grammarly, and Scite, to streamline and enhance the literature review and synthesis process. Students will use these tools to annotate, tag, summarize, and organize key findings from academic and policy sources. The training will be provided on the ethical use of those tools.
Descriptive and Regression-Based Quantitative Essay – This essay analyzes data to describe who loses financial aid and estimate the correlates of continued enrollment and academic success after aid loss.
Quasi-Experimental Essay – This essay applies causal inference methods (e.g., difference-in-differences or regression discontinuity) to estimate the effect of financial aid loss on students’ academic momentum, retention, and graduation outcomes.
Qualitative Case Study – This essay explores how students make sense of losing aid, drawing on in-depth interviews and institutional context to understand their strategies and challenges.
Undergraduate researchers will assist in building the literature review foundation for all three essays, focusing on: 1) Financial aid policies and merit-based funding; 2) Academic momentum and persistence; 3) Equity and access in higher education; 4) Student coping mechanisms and institutional support.
The project integrates FSU-approved and funded Generative AI (GenAI) and literature organizer tools, including Co-Pilot, Zotero, Grammarly, and Scite, to streamline and enhance the literature review and synthesis process. Students will use these tools to annotate, tag, summarize, and organize key findings from academic and policy sources. The training will be provided on the ethical use of those tools.
Mentees will:
Conduct guided literature searches on topics related to financial aid loss, college student outcomes, and higher education policy.
Use Zotero to organize citations, tag themes, and attach annotations.
Use Scite_ to evaluate article influence and categorize citation contexts (supporting, contrasting, or mentioning), as well as critically assess the output generated by this tool.
Use GenAI tools (like Co-Pilot) to produce annotations and check their accuracy.
Assist in formulating research questions.
Assist in coding and categorizing themes across the three essays, mapping out conceptual frameworks, and identifying research gaps
Participate in brief skill-building sessions on AI tools for Research.
Conduct guided literature searches on topics related to financial aid loss, college student outcomes, and higher education policy.
Use Zotero to organize citations, tag themes, and attach annotations.
Use Scite_ to evaluate article influence and categorize citation contexts (supporting, contrasting, or mentioning), as well as critically assess the output generated by this tool.
Use GenAI tools (like Co-Pilot) to produce annotations and check their accuracy.
Assist in formulating research questions.
Assist in coding and categorizing themes across the three essays, mapping out conceptual frameworks, and identifying research gaps
Participate in brief skill-building sessions on AI tools for Research.
No prior research experience is necessary.
A foundation in academic writing is recommended.
A curiosity for AI tools in research is a huge plus!
Some initial guidance on what I already know about AI-supported literature reviews will be provided at the beginning; however, please note that this will be a joint journey of mentor and mentees discovering the advancements in the field as we progress.
A foundation in academic writing is recommended.
A curiosity for AI tools in research is a huge plus!
Some initial guidance on what I already know about AI-supported literature reviews will be provided at the beginning; however, please note that this will be a joint journey of mentor and mentees discovering the advancements in the field as we progress.
I believe undergraduate research is an opportunity not just to build technical skills, but to help students grow as independent thinkers and contributors to meaningful and ethical scholarship in the era of AI. In working with UROP students, I will focus on creating a respectful and inclusive environment where curiosity is encouraged, questions are welcomed, and learning is a collaborative process.
I meet students where they are, regardless of prior research experience. Early in the project, I provide structured guidance to help them engage with key tools and concepts. As their confidence grows, I encourage them to take greater ownership of their learning, diving deeper into literature, experimenting with generative AI, and making connections between the three parts of the project.
I prioritize open communication, meeting regularly to offer feedback, troubleshoot challenges, and reflect on progress. Mentorship, to me, is a two-way relationship. While I share knowledge and provide direction, I also learn from students’ questions, insights, and the unique perspectives they bring to the work.
I want this experience to feel empowering and valuable beyond the scope of the project. Whether students go on to pursue honors theses, graduate school, or careers in education and policy, I hope they leave with stronger research skills, greater confidence in their voice, and a clearer sense of their ability to contribute to academic and public conversations. My goal is for students to see themselves not just as learners, but as knowledge builders who can shape the future of their fields.
I meet students where they are, regardless of prior research experience. Early in the project, I provide structured guidance to help them engage with key tools and concepts. As their confidence grows, I encourage them to take greater ownership of their learning, diving deeper into literature, experimenting with generative AI, and making connections between the three parts of the project.
I prioritize open communication, meeting regularly to offer feedback, troubleshoot challenges, and reflect on progress. Mentorship, to me, is a two-way relationship. While I share knowledge and provide direction, I also learn from students’ questions, insights, and the unique perspectives they bring to the work.
I want this experience to feel empowering and valuable beyond the scope of the project. Whether students go on to pursue honors theses, graduate school, or careers in education and policy, I hope they leave with stronger research skills, greater confidence in their voice, and a clearer sense of their ability to contribute to academic and public conversations. My goal is for students to see themselves not just as learners, but as knowledge builders who can shape the future of their fields.
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- Day: Thursday, September 4
Start Time: 2:00
End Time: 2:30
Zoom Link: https://fsu.zoom.us/j/93249671969
UROP Program Elements
Yes
Yes
Yes
Yes
Yes
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2025
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