Innovation in AI Grants
February 13, 2024
The Campus Technology Committee, the Office of Research and Sponsored Programs, Office of Faculty Excellence & Academic Engagement, and Information Technology Services, of the 海角社区 (UNF) are pleased to announce a Request for Proposals (RFP) from faculty for innovative projects focusing on Artificial Intelligence (AI) in various academic and research domains.
Proposal Submission Deadline: March 29, 2024
Purpose
The purpose of the Innovation in AI Grants is to foster integration of Artificial Intelligence and Large Language Models to enhance pedagogy, student success, course/curricular development, and research/scholarship/creative activities (RSCA). Specifically, the following four distinct grants are offered, each addressing a unique aspect of AI in academia:
- AI and Pedagogy Enhancement in 海角社区Classrooms: Seeking proposals that integrate AI to transform teaching methods and learning environments. This includes utilizing AI tools for personalized learning, enhancing interactive learning experiences, or developing AI-driven enhancements to assessment of student learning.
- AI and Student Success at UNF: Projects that leverage AI to improve student engagement, retention, and academic performance. This may involve AI-driven analytics to identify and support at-risk students, AI in career counseling, or enhancing student services through AI technologies.
- AI Course/Curricular Development: Proposals for creating new AI-focused courses, programs, or digital/certification badges. This can include interdisciplinary courses merging AI with other fields, online course offerings, or new concentrations or majors.
- AI in Research Enhancement: Focuses on how AI can augment research capabilities at UNF. This includes using AI for data (both quantitative and qualitative) analysis, enhancing research methodologies, AI developments in the arts and humanities, or developing AI-based tools to assist in various research fields.
Funding: Grant recipients will receive $15,000 for one semester, Summer 2024. Four grants, one in each category listed for $60,000 total, will be awarded.
Eligibility
Open to all full-time faculty members at UNF. Collaborations across departments are encouraged. The following restrictions apply:
- Grants may be held while on sabbatical; they may not be held while on leave of absence without pay.
- Faculty who intend to terminate employment or leave UNF, or faculty who are on administrative leave or terminal notice and will not receive a contract during the next academic year, are ineligible. Except in extenuating circumstances, failure to remain at 海角社区for at least one academic year following the award will require grant repayment.
- Members of the Campus Technology Committee may not apply for Innovation in AI Grants.
Timeline
Application deadlines will be the fourth Friday after the beginning of the Fall and Spring terms. Applications must be received no later than 5:00 p.m. on the deadline date. Late or incomplete submissions will not be considered.
Applications for the Summer 2024 funding round are due by 5 p.m. on Friday, March 29, 2024
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Proposal Guidelines & Submission
Each application must be submitted online via the .
The submission will include the online form at the portal and uploading through the portal of an application packet in Adobe PDF format. Please use the last name of the first author of the proposal as the PDF file name. The application packet includes the sections listed below, formatted using 1-inch margins and 12-point Times New Roman font. All sections, unless otherwise noted, must be double-spaced. All sections of the application must have a footer that includes the proposal title, the name of the applicant and the page number. It is imperative that all sections are submitted as instructed, and that all formatting instructions and page and word limits be followed. Failure to do so will result in the rejection of the application.
- Section 1 of PDF file: Proposal Narrative (maximum of 3 pages, double-spaced). Proposal narratives should include a project description, expected outcomes, plan of completion, and relevance to one of the four grant categories.
- Section 2 of PDF file: Timeline and budget with estimated project completion date (1 page). Applicants should obtain pricing estimates or quotes from ITS where appropriate.
- Section 3 of PDF file: Up-to-date curriculum vitae of all involved faculty.
Award Notification and Implementation
Grant awardees will be notified by April 19, 2024, and will receive funding for implementation Summer 2024.
Review Process
A committee of representatives from the Campus Technology Committee, the Office of Research and Sponsored Programs, Information Technology Services, and the Provost’s Office will review submissions, assessing innovation, feasibility, potential impact, alignment with UNF’s strategic goals, and clarity and organization.
Proposals must be submitted by March 29, 2024. Grant awardees will be notified by April 19, 2024, and will receive funding for implementation in Summer 2024.
Deliverables
Every recipient is expected to submit their results to the if their work is related to teaching. Additionally, all recipients will be requested to provide an elevator pitch overview during the upcoming 海角社区AI Workshop scheduled for April 26, 2024. Lastly, each recipient will deliver a public presentation of their project results at the 海角社区Fall AI Symposium, in coordination with the Office of Faculty Excellence & Academic Engagement
Contact Information
For inquiries, contact Chris Petrello at chris.petrello@unf.edu
The 海角社区 is eager to support cutting-edge AI initiatives that advance our educational and scholarship missions. We look forward to your creative and impactful proposals!
Proposal Review Rubric
This rubric evaluates proposals for the Innovation in AI Grants based on five key criteria: Innovation, Feasibility, Potential Impact, Alignment with University Strategic Goals, and Clarity & Organization. Each criterion is assessed on a 5-point scale (5 = Excellent, 1 = Needs Significant Improvement).
Rubric
| Criterion | 5 Points | 3 Points | 1 Point |
|---|---|---|---|
| Innovation | Proposes a highly original and transformative use of AI/LLMs. The proposed approach significantly advances current practices or opens new avenues for exploration | Proposes a somewhat innovative use of AI/LLMs, building on existing methods but demonstrating unique adaptation or application. | Offers a relatively conventional use of AI/LLMs with limited originality or novel contribution to the field. |
| Feasibility | Provides a clear and well-structured plan for project implementation, with realistic timelines, resource allocation, and risk mitigation strategies. Demonstrates access to necessary technical expertise and infrastructure. | Presents a generally feasible plan, but some aspects require further clarification or justification. Resource allocation or risk management may need refinement. | Lacks a convincing implementation plan, with unclear timelines, insufficient resources, or unrealistic expectations. Raises significant concerns about project feasibility. |
| Potential Impact | Clearly articulates the potential impact of the project on pedagogy, student success, course/curricular development, or RSCA. Defines specific metrics for measuring success and demonstrates potential for broader dissemination or scalability. | Identifies potential impacts but lacks clear definition of success metrics or limited explanation of dissemination and scalability potential. | Impact remains undefined or limited, with negligible contribution to pedagogy, student success, or academic advancement. |
| Alignment with University Strategic Goals | Explicitly and effectively links the project to the university's identified strategic goals for AI integration, pedagogy, student success, or RSCA. Shows a deep understanding of these goals and demonstrates how the project will contribute to their achievement. | Aligns with some university strategic goals, but the connection is superficial or lacks sufficient detail. | Weak or nonexistent connection to university strategic goals. Fails to demonstrate how the project contributes to the university's vision. |
| Clarity & Organization | The proposal is well-written, logical, and easy to understand. Information is presented concisely and effectively, with clear headings, subheadings, and visuals. | The proposal is generally clear and organized but may have some sections that are unclear or repetitive. | The proposal is poorly organized, difficult to follow, and may contain factual errors or inconsistencies. |
Additional Considerations:
- Interdisciplinary collaboration will be positively weighed.
- Budget clarity and justification will be assessed.
Resources:
- UNF’s hosted by CIRT and OFE
- UNF’s OFE Decoding the Impact of Generative AI on Teaching and Learning at UNF webpage
- Free, 1-hour, from the University of Florida
- A on the environmental impact of generative AI
- Complete College America’s
- Harvard’s metaLAB
- University of Michigan’s Institute for Data Science
Chris Petrello
Assistant Vice President
Campus Technology Services
Information Technology Services
(904) 620-5469
chris.petrello@unf.edu