UROP Project

The Framing of Queer Victimization in News Media

news media, LGBTQ+, framing, victimization, news media analysis

Research Mentor: Sam Sutton, she/her
Department, College, Affiliation: Criminology and Criminal Justice, Criminology and Criminal Justice
Contact Email: ses25a@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Preference for Criminology and Criminal Justice or Sociology, Open to Political Science, Social Work, or Other Social Sciences
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

This project is focused on understanding how written news media frames events surrounding the victimization of queer individuals through the theoretical mechanism of frame building. To do this, articles will be pulled from five different news sources that span across political ideologies over the course of a nine-year time span. This time span allows for political powers in charge to shift over time as well as provides additional context to the new articles whose sources don't change their ideological stance. After articles are identified as being part of the desired sample, they are then read through carefully and are individually coded based on a set of criteria. After all the identified articles are coded, basic analyses will be run to understand these frames and subsequent messaging.

Research Tasks: Use search engines and a set criterion to identify articles for inclusion in the study
Read and code articles in an objective way
Possibly assist with finding sources for a literature review

Skills that research assistant(s) may need: Comfortability with the Microsoft Suite, primarily Excel
Critical Thinking, Time-Management, Detail Oriented
Recommended: Basic Stata Understanding

Older Adults and Generative AI

Older Adults, Seniors, AI, Artificial Intelligence, Video, Learning, Digital Skills, Community, Design, Digital Literacy

Research Mentor: Ms. Sihan Jian, She, her, hers
Department, College, Affiliation: Educational Psychology and Learning Systems, Education, Health, and Human Sciences
Contact Email: sj23a@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Open to all majors.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: If travel is needed off campus, I will provide the ride.
Remote or In-person: Partially Remote
Approximate Weekly Hours: 8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

The project aims to develop educational videos that help older adults understand and use generative AI tools (e.g., ChatGPT, Google Gemini) effectively in their daily lives. The videos will introduce practical ways generative AI can support everyday tasks and activities while helping older adults develop the knowledge and skills needed to use these technologies safely and effectively.


Research Tasks: For the first phase of the project, the undergraduate research assistant will help develop educational videos that introduce older adults to the basics of generative AI and practical ways to use these tools in their daily lives. The assistant will help create accessible and engaging content that responds to older adults’ needs. The videos will be piloted with older adults, and their feedback will be used to iteratively refine the content and instructional approach.

The project may also include occasional in person workshops at senior centers or community organizations. The assistant may support online and in person data collection through surveys, interviews, field notes, and documentation of workshop activities and participant feedback.

Skills that research assistant(s) may need: Required:
1. Video production experience: Experience creating and editing videos. Interested students are encouraged to share a portfolio or samples of previous work (e.g., a video link or personal website) when reaching out to me.
2. Patience and willingness to work with older adults
3. Openness and responsiveness to feedback
Recommended:
1. Prior volunteer or work experience with older adults

Disentangling mobility, cognitive function, and digital behaviors to understand social isolation and dementia risk

Cognitive decline; social isolation; digital phenotyping; GPS tracking; spatial behavior

Research Mentor: Amber DeJohn, she/her
Department, College, Affiliation: Geography, Social Sciences and Public Policy
Contact Email: amber.dejohn@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 3
Relevant Majors: Computer science; information technology; social sciences (geography, sociology, etc), social work
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-7 hours a week, more if there's a data collection event. , Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Tuesday, September 1
  Start Time: 4:30
  End Time: 5:00
  Zoom Link: https://fsu.zoom.us/j/94404614934

Project Description

This is an NIH-funded study exploring how spatial-digital behaviors are associated with social isolation and cognitive function. We will be using passive tracking and traditional surveys to monitor how and where older adults spend their time, ultimately sequencing and clustering these behaviors using machine learning tactics.

Research Tasks: Depending on the student's major, they will assist with data collection, input, and/or analysis. Data collection tasks might include conducting cognitive screenings, helping participants install applications on their phones, monitoring AWS backend (for those with required skillset), etc. Students may also assist with inputting or cleaning collected data. Analysis may include preliminary mapping or more advanced analysis.

Skills that research assistant(s) may need: Recommended: comfortable talking on the phone or in-person with older adults
Required: experience using excel
Recommended: any and all coding experience (e.g., python) is welcome and appreciated, but not expected.

Contaminant Avoidance Adaptability

threat, contamination, avoidance, pathogen, adaptive

Research Mentor: Dr. David S. March,
Department, College, Affiliation: Psychology, Arts and Sciences
Contact Email: march@psy.fsu.edu
Research Assistant Supervisor (if different from mentor): Patrick J. Oefelein
Research Assistant Supervisor Email: oefelein@psy.fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Psychology
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: In-person
Approximate Weekly Hours: 5-10, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

Contaminants are objects, organisms, or individuals that may serve as vectors of harmful pathogens. Avoiding them therefore requires a cost-benefit calculation that weighs the potential costs of infection against the potential benefits of approaching or interacting with a contamination source, such as food, shelter, useful information, or social connection. This calculation is inherently asymmetric since in many contexts, the potential fitness costs of infection are substantially greater than the benefits associated with any single opportunity for resource acquisition. Yet people do not evaluate these costs and benefits objectively or in a vacuum. Their judgments are shaped by factors that alter either the perceived likelihood and cost of infection or the subjective value of the resource at stake, including current hunger or need, resource scarcity, risk tolerance, prior experience, and broader environmental conditions.
 
In the current work, we are interested in whether resource deprivation changes this tradeoff, particularly when deprivation occurs during early development or is experienced chronically in the present. One possibility is that adaptation to resource-scarce environments increases the subjective cost of foregoing an available resource. Under scarcity, passing up food, shelter, social support, or other opportunities may itself become consequential enough to justify accepting greater contamination risk. Resource deprivation may therefore shift the cost-benefit calculation away from pathogen avoidance and toward resource acquisition, not necessarily because contaminants are perceived as less dangerous, but because the competing benefits of approach become more valuable. If so, individuals with greater histories or current experiences of resource deprivation should be more willing to tolerate contamination risk when doing so provides an opportunity to acquire a valued resource.

A UROP student will work prepare the stimuli used in the study and collect behavioral and survey data from participants in the lab. Once data collection is complete, the UROP student may be involved in applying insights from the study to explain behaviors like risk tolerance, contamination threat evaluations, and group interactions.

Research Tasks: Stimuli creation, study creation/coding, data collection, data cleaning, supplementary literature search and review.

Skills that research assistant(s) may need: Basic familiarity with Windows++ (required)
Basic knowledge of image editing/cropping (required)
Basic statistical programming experience/knowledge (recommended, and can be taught)
Quick and eager to learn new skills

Examining Hospital Boards

Boards, hospitals, governance

Research Mentor: Dr. Sasmira Matta, she/her
Department, College, Affiliation: Management, Business
Contact Email: smatta@wertheim.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Open to all majors, though am looking for someone who is excited to built their technical and empirical toolkit and who will be ready and willing to get into the weeds of data location
Project Location: Wertheim College of Business 402 West Gaines Street
Research Assistant Transportation Required: FSU Shuttles
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10 depending on the week and the research assistant's other responsibilities, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Tuesday, September 1
  Start Time: 12:00
  End Time: 12:30
  Zoom Link: https://fsu.zoom.us/j/91935154900
• Day: Wednesday, September 2
  Start Time: 12:00
  End Time: 12:30
  Zoom Link: https://fsu.zoom.us/j/91474781180

Project Description

This research project is interested in understanding the composition of hospital boards with respect to their expertise and gender. In one part, we will build and analyze data to understand the role of expertise on a hospital boards and whether it has an effect on quality outcomes within the hospital. In another part, we will try to think about whether non-profit organizations like hospitals, mimic boards of publicly traded companies.

Research Tasks: -Data collection (web scarping, manual collection)
-Data synthesis (putting datasets together, developing coding abilities)
-Literature reviews

Skills that research assistant(s) may need: Ideally a research assistant will have some basic technical skills. However, I am open to working with a student who is motivated to build upon skills that may be transferable for graduate school and/or a job.

Speech Silences

Language, Conversation, Psychology

Research Mentor: Michael Kaschak,
Department, College, Affiliation: Psychology, Arts and Sciences
Contact Email: mkaschak@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: In-person
Approximate Weekly Hours: 6, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

My students and I are interested in exploring how people interact with each other. The focus of this project will be on the silences that occur at various points during speech. How do we decide how long to pause? How do we interpret these pauses? How are the production and interpretation of pauses affected by personal characteristics such as anxiety? These are the sorts of questions that we are asking.

Research Tasks: Students will help with literature reviews, data collection, data coding and analysis, and the design/preparation of new studies.

Skills that research assistant(s) may need: No specific skills required.

State Marine Aquaculture Policy

Policy, Aquaculture, Mariculture, Marine

Research Mentor: Lillie Bradshaw, She/Her
Department, College, Affiliation: Biological Science, Arts and Sciences
Contact Email: lb22l@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Biology/Biological Sciences, Oceanography, Geography, Environmental Science, Natural resources/conservation.
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

Marine aquaculture in the United States is currently a relatively small seafood sector, but there is tremendous potential for growth and interest in advancing the industry through supportive federal and state policy. However, there is no comprehensive national legislation focused on marine aquaculture, and most production is occurring in state waters guided by diverse state-level policies and regulations. State and federal agencies, researchers, and industry members need increased access to state marine aquaculture regulations and policies across the U.S. to gain a better understanding of how these different policy approaches may be enabling or impeding the development of the industry. This work will focus on mariculture policy data collection for US States and Territories and is a part of a larger project working to update the State Marine Aquaculture Policy Dashboard, an online tool aimed at increasing the accessibility and usability of state marine aquaculture data. Training will be provided in mariculture policy, data collection, database management, and data analysis.


Research Tasks: Data Collection: The UROP student will be trained in how to search for and select relevant marine aquaculture policies using government websites and legal code.
Data Entry: Data collected from online sources will be recorded and maintained in a database. Skills in data extraction and database management will be developed.
Data Analysis: Summary of policy differences and metrics will be analyzed and summarized.

Skills that research assistant(s) may need: Available at least one day per week to meet with mentor for check-ins and training assistance, in-person or over Zoom. As independence is achieved schedule will be more flexible for working from home *Required*
Proficiency in the basics of MS Excel and MS Word, Google Drive * Required*
General interest in marine systems, marine aquaculture, policy, and management *Recommended*

Machine Learning for UAVs

drones, machine learning, artificial intelligence

Research Mentor: Salma Aboelmagd,
Department, College, Affiliation: Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: saboelmagd@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Electrical engineering
Computer science
Computer engineering
Project Location: Center for Advanced Power Systems
Research Assistant Transportation Required: FSU Seminole Express
Remote or In-person: In-person
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

This project focuses on applying machine learning techniques to improve cyberattack detection in unmanned aerial vehicles (UAV). Students will work with real UAVs and datasets containing physical, cyber, and cyber-physical data to develop an understanding of data-driven intrusion detection methods. Throughout the project, students will gain experience with the research process, including reading scientific literature, exploring and analyzing datasets, implementing machine learning algorithms, evaluating model performance, and interpreting experimental results. As students progress, they will also be introduced to numerous machine learning concepts and cybersecurity challenges affecting autonomous systems.

Research Tasks: 1. Reading and summarizing research papers related to UAV security and machine learning.
2. Learning Python for data analysis and machine learning applications.
3. Implementing and evaluating supervised machine learning models.
4. Documenting experimental procedures, observations, and results.
5. Set UAV environments and experiments.

Skills that research assistant(s) may need: Required:
- Interest in cybersecurity, machine learning, or autonomous systems
- Willingness to learn programming and data analysis
- Strong problem-solving skills
- Good organizational and communication skills

Recommended:
- Introductory programming experience (Python preferred, but not required)
- Exposure to machine learning concepts
- Interest in research and scientific writing

FSU Postcard Archive

digital archive, visual rhetoric, public memory, cultural studies, museum studies

Research Mentor: Dr. Michael Neal, he/him
Department, College, Affiliation: Florida State University, Arts and Sciences
Contact Email: mrneal@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 5
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 3-5 hours weekly (one hour of meeting in person, the rest self directed), Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Tuesday, September 1
  Start Time: 2:00
  End Time: 3:00
  Zoom Link: https://fsu.zoom.us/j/8818962394
• Day: Wednesday, September 2
  Start Time: 1:00
  End Time: 2:00
  Zoom Link: https://fsu.zoom.us/j/8818962394

Project Description

The FSU Card Archive serves as both a physical repository and digital humanities platform dedicated to preserving and providing scholarly access to historic postcards, stereo cards, first day issue stamp cards, and other related artifacts. The archive is organized by items (individual cards with metadata), exhibits (curated displays supporting interdisciplinary research in visual rhetoric, material culture studies, art history, communications, and related fields), and collections (honoring doners that have contributed to the site).

We believe each postcard functions as a primary source document that captures specific historical moments while reflecting the cultural values, technological capabilities, and social communications of its era. Researchers can locate materials by thematic content (e.g., World War II propaganda, Florida State College for Women imagery), chronological periods (1930s Depression-era cards), geographical locations (Vero Beach tourism, Cuban landscapes), or publisher information. Past student-curated exhibits have explored topics such as ethnic stereotyping in early 20th-century visual culture, sexist humor in popular media, public venues for entertainment, and environmental messaging. Each project demonstrates the archive’s capacity to support diverse voices and critical perspectives.

The archive’s mission includes preservation but extends to facilitate scholarship. The vast majority of items and exhibits have been curated by undergraduate students, though graduate students and faculty participate as well. We see this site as a tool for learning archival practices and processes. The platform’s exhibit functionality allows users to create publicly accessible displays that contribute to ongoing scholarly conversations.

Interns will engage in three interconnected areas of digital archiving work:
1. Learn OMEKA content management system for cultural heritage collections
2. Conduct visual readings and analysis of postcard entries to enhance descriptive metadata
3. Curate original thematic exhibits on specific postcard series, publishers, regional collections, or topical themes


Learn OMEKA archival system, conduct visual readings and analysis of postcard entries, and curate original thematic exhibits on specific postcard series on a topic relating to the student's interests.

Approximately one hour team meeting per week. The rest independent, though I'm available for one-on-one meetings by appointment. AI acceptable for research, design, and editing as long as it is used reflectively and critically as a support, not substitute for student work.

Research Tasks: Fall semester will include learning the metadata system, editing existing items, adding new items, transferring one or more exhibits from the old to new system to learn how to create exhibits, and begin framing their own exhibits. Students will develop their own focus, which will require secondary research for literature and potentially a framework for the visual analysis.

Skills that research assistant(s) may need: All research skills and programs (e.g., OMEKA) are taught. They are simple to learn.

Prompt Engineering in Higher Education: University Students’ Strategies, Trajectories, and AI Literacy Development

Generative AI; AI Literacy; Prompt Engineering; Higher Education; Interaction Trajectories

Research Mentor: Yixin Qian,
Department, College, Affiliation: Edu Psychology & Learning Sys, Education, Health, and Human Sciences
Contact Email: yq23@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Open to all majors; students in Education, Applied Linguistics, Psychology, Communication, Information/Computer Science, Statistics or related fields are especially encouraged to apply.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Yes
Remote or In-person: Partially Remote
Approximate Weekly Hours: 6-8 hours a week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Thursday, September 3
  Start Time: 2:30
  End Time: 3:30
  Zoom Link: https://fsu.zoom.us/j/92196116707

Project Description

The study would examine whether and how university students adopt, combine, and refine prompting strategies, such as zero-shot prompting, few-shot prompting, chain-of-thought prompting, zero-shot chain-of-thought, least-to-most prompting, and self-consistency, and how these observable practices relate to the development of their GenAI literacy.

The central research question would be:

How do university students use and combine prompt-engineering strategies across disciplinary learning tasks, and how do these strategies and multi-turn interaction trajectories develop over time?

Subquestions could be: To what extent do these observable prompting behaviors reflect students’ GenAI literacy, particularly their strategic use of GenAI, critical evaluation of outputs, verification practices, and responsible delegation of academic work?

The project would bridge two areas that are often studied separately. Prompt-engineering research focuses primarily on how particular prompting techniques improve GenAI reasoning and output quality, whereas higher education research often relies on students’ self-reported GenAI literacy. This study would translate established prompt-engineering techniques into observable student behaviors. For example, providing examples or rubrics could be coded as few-shot-inspired prompting, requesting explanations as chain-of-thought-inspired prompting, decomposing a task as least-to-most-inspired prompting, and generating or comparing multiple answers as self-consistency-inspired prompting. These prompt-level strategies could then be examined as parts of broader conversation-level trajectories.

Methodologically, the study could use a longitudinal mixed-methods design. With appropriate consent and anonymization, student–GenAI chat logs would be collected at different time points from students in different disciplines, such as during the first several months of using GenAI tools, after one year of use, and after several years of use. The logs would be supplemented by brief GenAI literacy surveys, task-based assessments of students’ ability to design and evaluate prompts, GenAI-free learning or transfer measures, and stimulated-recall interviews. A deductive–inductive coding framework would identify both prompting strategies and broader trajectories, such as direct delegation, iterative refinement, reasoning-oriented interaction, and verification-oriented interaction.

The main contribution would be to conceptualize prompt engineering as an observable behavioral enactment of GenAI literacy, rather than treating GenAI literacy only as a self-reported attitude or general competency. The project could also clarify whether students become more strategic, evaluative, and responsible GenAI users with experience, or simply become more efficient at directing GenAI to complete academic work.


Research Tasks: The research assistant will help conduct literature reviews on prompt-engineering strategies and GenAI literacy, develop and refine the coding framework, assist with participant recruitment and survey administration, and collect and anonymize student–GenAI chat logs. With training, the student will code individual prompts and broader interaction trajectories, conduct basic descriptive analyses, support inter-rater reliability checks, and assist with stimulated-recall interviews and qualitative coding. The student may also contribute to the preparation of a UROP poster, conference proposal, research report, or manuscript.


Skills that research assistant(s) may need: Required: Strong attention to detail; good organizational and communication skills; willingness to learn qualitative coding procedures; ability to work responsibly with research data; and an interest in GenAI, higher education, or educational research.

Recommended: Basic knowledge of statistics and data analysis; prior experience with qualitative coding, surveys, interviews, or research projects; and familiarity with GenAI tools such as ChatGPT; be able to speak Spanish fluently.