PROGRAM DESCRIPTION
The Faculty Learning Community (FLC) is a small group of faculty who meet regularly throughout the semester to explore a common interest. We invite deans, department chairs, and/or faculty groups to propose and lead their own school-based FLCs to tackle an AI-related teaching and learning need, challenge, or opportunity within their schools. This decentralized model empowers faculty to lead peer-based explorations of AI topics most relevant to their disciplines.
EXAMPLE OF FLC THEMES
School of Humanities
AI and the Archive: New Methods for Humanistic Inquiry and the Challenges of AI-Generated Historical Texts.
School of Engineering
Using AI for Simulation and Modeling in Senior Design Projects while Maintaining Academic Integrity.
Shepherd School of Music
Exploring Generative AI for Musical Composition, Analysis, and Student Practice.
School of Social Sciences
Ethical Considerations for Using AI-Powered Data Analysis in Social Research.
WHO CAN PARTICIPATE AND APPLY?
Proposals for a new FLC should be submitted by a designated Faculty Facilitator. Participants can be recruited before or after the proposal is accepted.
Facilitators: Any Rice faculty member, including tenured, tenure-track, and non-tenure-track teaching faculty, is eligible to apply to be a facilitator.
Participants: All Rice faculty are eligible to participate. We also encourage the inclusion of key staff members (e.g., instructional designers, librarians, and academic advisors) as participants where their expertise is relevant to the FLC’s theme.
WHAT IS THE TIMEFRAME?
All FLCs funded through this initiative are expected to be held during the 2025-2026 academic year.
The FLC should plan to begin in the Fall 2025 semester and continue through Spring 2026.
FLCs should meet at least five times, 60-90 minutes each meeting.
WHAT ARE THE EXPECTED OUTCOMES?
The goal of an FLS is not just discussion, but the creation of a tangible outcome that can be shared with the broader Rice community. Each FLC will be expected to produce a “shareable resource” by the end of the academic year. Deliverables make the FLCs work tangible and provide a clear goal for participants. The deliverable should be something the faculty member can directly use or that contributes to the broader university community. Facilitators might choose to ask for individual and/or community-facing deliverables.
Individual Deliverables
Redesigned Syllabus: A revised syllabus for Fall 2025 course that explicitly incorporates an AI policy, AI-related learning objectives, and at least one new AI-integrated assignment.
A New Assignment or Module: A fully developed learning module or major assignment that uses AI to enhance student learning.
An “AI-Exploration” Report: A short, reflective paper detailing their experimentation with 2-3 new AI tools, analyzing their potential for their specific discipline and courses.
Community-Facing Deliverables
Annotated Resource List: A collaboratively build list of the most useful AI tools, readings, and resources for teaching in their specific discipline or school.
Departmental Workshop: A plan and materials for a 60-minute workshop that the FLC member will deliver to their home department the following semester.
Short Presentation or Blog Post: A 5-minute “lightning talk” video or a blog post for the Rice Digital Learning website, showcasing their project and key takeaways for their peers.
WHAT ARE THE INCENTIVES?
Below is a list of the funding to support the time and effort of FLC members.
Eligibility: All officially registered participants and the designated facilitator of an accepted FLC are eligible for a stipend.
Incentives: The facilitator will receive a $1,000 stipend, and each participant will receive a $500 stipend.
Payment Process: Stipends will be processed as a one-time payment at the end of the Fall 2025 semester, upon the successful completion of the FLC and submission of its final outcome/resource.
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