The AI RiTL FLC is a collaboration between the AI2 Center and the Center for Teaching Excellence, representing an innovative, interdisciplinary community dedicated to the advancement and integration of artificial intelligence in teaching and learning. Building on the foundations established in the “Harnessing AI for Teaching & Learning FLC,” this FLC allows faculty to conduct scholarly research about teaching implementations of AI at UF.

Deadline

August 29, 2025

Apply here!

 

Key Details:

Participation: Limited to 15 faculty members

Stipends:

• Participants will receive a $1000 stipend for completion of the FLC requirements.
• Participants will receive an additional $1000 stipend if their work is published in a peer-reviewed journal. (Additional funds of up to $1000 are available to reimburse publication fees after publication).

Support: Comprehensive support from the inception to completion of Research in Teaching and Learning (RiTL) projects.

 

Location and Meeting Schedule

Location: Tigert 302

Fall 2025 and Spring 2026

Every other Thursday from 2:00 – 3:30pm

The FLC will run September 11, 2025 – April 9, 2026

• Fall 2025 Dates: 9/11, 9/25, 10/9, 10/23, 11/6, 11/20, 12/4
• Spring 2026 Dates: 1/15,1/29, 2/12, 2/26, 3/12, 3/26, 4/9

FLC Requirements:

Active Participation: Attend 75% of meetings (11 of the 14 sessions).

Big Idea Project: Propose and develop a teaching-as-research project, either as a group endeavor or as an individual. Projects could range from studying course-specific AI integrations, evaluating AI professional development or teaching resources for the broader community, or conducting scholarship of AI teaching and learning.

CTE Event Participation: Present your AI scholarship of teaching and learning research at the Center for Teaching Excellence’s RiTL Symposium or Interface Conference.

 

Participant Eligibility

• Participants must show that they have a sustained commitment to incorporating AI in teaching and learning. This may include successful completion of Harnessing AI for Teaching & Learning, Teaching with AI in the SEC Learning Community, or the AI Learning Academy Micro-credential. Other possibilities include teaching an AI-designated course, other forms of professional development around AI, micro-credentials in AI, or being an AI 100 hire.
• No previous research experience in teaching and learning is required.

Goals and Objectives:

1. Develop an in-depth understanding of RiTL and its significance in the context of AI-enhanced education.

2. Foster an environment for reading, learning, and discussing scholarly works on teaching and learning with AI and about AI.

3. Generate unique research questions and devise comprehensive research plans that incorporate AI into different teaching and learning domains.

4. Submit a presentation proposal to the 2026 Interface Conference or 2026 RiTL Symposium to share your AI RiTL project with a campus-wide audience.

5. Begin and make progress on a publication of a Research as Teaching project.