Info for Participating Teams

The AI for Teaching & Learning (AI4TL) Institute is a cohort-based professional learning community led by the College of the Canyons, Carnegie Mellon University, the State University of New York (SUNY) System, and the California Community Colleges Chancellor’s Office (CCCCO), in partnership with Axim Collaborative. We invite broad-access higher education institutions to form cross-functional teams and join a national initiative dedicated to advancing AI to support teaching and learning. The AI4TL Institute aims to fill a critical gap in professional development by moving institutions beyond isolated AI experimentation toward coordinated, mission-aligned instructional strategies. The Institute centers the unique teaching focus and community values of broad-access institutions while building local capacity to enhance student success, expand access, and improve learning outcomes through AI. While many people are engaging in this work individually and uncompensated, in the Institute you’ll do this work with support, structure, and community while supporting your institution’s priorities.

Desired Attributes of Participating Institutions

We are seeking institutional teams to join our first cohort that possess:

• A commitment to expanding educational opportunities, including those within the California Community Colleges (CCC) system, the State University of New York (SUNY) System, and UNCF member institutions.
• A commitment to evidence-based instruction and an organizational desire to move beyond isolated AI experimentation toward a coordinated, mission-aligned instructional strategy.
• A willingness to dedicate cross-functional personnel to a sustained, 5-month engagement designed to enact tangible change in teaching and learning, curricula, campus policies, or support structures.

Program Timeline for Cohort 1

The Institute will launch on January 19, 2027, and end by June 18, 2027. 

Team Composition 

We believe that meaningful and effective institutional change requires alignment between faculty innovation, staff expertise, and administrative leadership. Therefore, participating institutions should apply as cross-functional teams of ~5 members each. A successful team would likely include:

• Teaching Faculty (Minimum of 3): Faculty members representing diverse academic disciplines who are eager to pilot AI-supported instructional practices.
• Professional Staff: Instructional designers, academic technologists, librarians, and/or Teaching & Learning Center staff specializing in instructional support.
• Academic Administrators: Deans, department chairs, or campus leaders positioned to influence institutional policy, academic strategy, and resource allocation.

One member of the team should serve as the Team Lead, who will:

• Serve as the primary point of contact between the participating institution and the Institute.
• Inform your team’s assigned coach (see description below) of any issues hindering the successful completion of the participating institution.
• Schedule regular (monthly) team check-in meetings with the team’s coach.

Expectations for Participation

Participation in the Institute unfolds over 5 months of activities, with an estimated total 40-60 hours of effort per team member. (This includes 22 hours of synchronous activities and ~18-36 hours of asynchronous work, not inclusive of meeting or planning time outside of formal Institute activities.) 

Virtual Plenary Dates 

• Friday January 22, 2027
• Friday March 12, 2027
• Friday June 11, 2027

We understand that not every team member will be able to attend every session, but we strongly encourage full participation.

Each team will be paired with an experienced AI4TL Coach who will provide structured subject matter expertise, mentorship, and pedagogical guidance to teams as they navigate the complexities of ethical, practical, and effective AI integration. Institute activities include:

• Foundational Learning: Team members will complete the foundational AI 4 Learning (AI4LN) self-paced online course via Carnegie Mellon University’s Open Learning Initiative Torus platform to establish a shared baseline of AI literacy, equity-focused frameworks, and pedagogical possibilities. Regular webinars led by AI experts on relevant topics will enhance and augment the course content. 
• Active Coaching & Collaboration: Teams will participate in five structured, monthly synchronous check-ins with their assigned coach. Teams will also attend three virtual Institute Plenaries (Kick-off, Mid-term, Concluding) and participate in “birds of a feather” affinity group breakout sessions. 
• Project Execution & Artifact Creation: Teams will design and execute a locally relevant AI integration project related to one of the tracks below. By the concluding plenary, teams should deliver a final artifact (e.g., revised syllabus, AI classroom policies, professional development model) to be openly licensed and shared in a national public-good repository.

Institutional Project Tracks

Teams will select one of the following primary focus areas to guide their 5-month journey through the Institute:

Project Track	Description
Updating Course Design and Assessments	Redesigning syllabi, assignments, and rubrics to validate learning in an AI-augmented environment. These revisions should apply to more than individual classes and find utility across disciplines.
Developing Shared Guidelines for Teaching and Learning	Creating institutional or departmental policies for academic integrity, AI ethics, and acceptable use in teaching and learning.
Designing Faculty Professional Development	Building local train-the-trainer models or campus workshops to increase baseline AI literacy for teaching and learning.
Piloting AI-Supported Learning Practices	Deploying instructional or student-support interventions, such as agentic AI, tutoring, or personalized learning frameworks.
Student AI Literacy	Developing modules, workshops, or campaigns to equip students with the skills and knowledge to use AI safely and effectively for academic success.
Selecting AI Tools for Teaching and Learning	Developing recommendations or evaluation checklists tailored specifically to the needs of teaching and learning.

Project Evaluation 

The AI4TL Institute includes a robust, structured research component, led by the Research and Planning Group for California Community Colleges (RP Group), designed to assess individual, institutional, and student impact. As part of program evaluation and broader research dissemination, participants will be asked to complete pre- and post-surveys measuring AI confidence and institutional cohesion. Additionally, faculty participants who implement AI-informed instructional changes will be asked to distribute a survey to students in the relevant courses.

For questions contact Judith Sebesta, Ph.D., Project Director, AI4TL Institute, at judith.sebesta@canyons.edu.