GenAI Preparedness for Teaching and Learning

To remain at the cutting edge of teaching, learning and workforce development in this age of generative artificial intelligence (AI), San Francisco State University, a minority-serving institution located in the heart of the AI revolution, will use this AI Fast Challenge grant to facilitate faculty development and academic department readiness by supporting inter-faculty and inter and intra-department collaborations, leading to the discovery and development of necessary processes, policies, curriculum, pedagogical support, tools and technical training, with a critical, equitable and ethical lens.                             

This study is funded by the California Education Learning Lab through an AI FAST Challenge: Funding for Accelerated Study and Transformation 

Goals

Begin discussing AI and develop a practical range of responses across different perspectives

Student Guidance and Engagement

  • Responsible and ethical use guidance
  • Departmental/syllabi statements/SLOs
  • Determine generative AI training needs for workforce preparedness

Discipline Impacts

  • Determine the impact of generative AI on the future of discipline
  • Examine use of generative AI in research and scholarship
  • Faculty professional development needs

Curricular Planning

  • Review courses and curriculum to infuse generative AI use
  • Consider course content and pedagogy with or without generative AI
  • Consider new courses, minors, programs and certificates

AI Faculty Learning Community Spring 2026

This is a time limited and grant funded opportunity. Spots are limited. This submission form will promptly close at 5pm on February 6th. Emailed submissions will not be accepted.

The Center for Equity and Excellence in Teaching and Learning and Academic Technology invite faculty members to submit a letter of interest (in 250 words) in joining a faculty learning community (FLC) this spring semester to explore AI-related topics more deeply. 

FLCs constituting 4-5 members will meet weekly and spend 8-10 weeks researching and experimenting on one of the topics listed below. The FLC members will be paid a modest stipend. Amount will be determined based on response.

By the end of the 10th week, the group will be expected to submit:

  1. Written recommendations and best practice suggestions for the courses you teach
  2. Examples of experimentations (in and out of class) with self-reflections of what worked, what did not in written or video format.
  3. Research articles and readings that influenced the FLC’s work
  4. Assignments, lesson plans and instructor reflections to share with colleagues

Topics identified are:

  • Teaching research methods courses in the age of AI
  • Can AI help with instructional tasks?
  • AI and coding for curriculum, teaching and student preparation
  • Foundational knowledge about genAI and Critical AI Literacy that all faculty should know for teaching
  • Suggest your own

Please use the Qualtrics form for letter of interest to submit your letter of interest. Please indicate if you’d like to lead the group. Since funding is limited, we will consider suggestions beyond those listed only if there is substantial interest.

Please apply by 5 p.m. on February 6, 2026.

Team

Team: Graduate Research Assistants

  • Parth Desai
  • Tannaz Haghi
  • Chetas Parekh
  • Kunal Sheth
  • Zurva Aziz

SFSU Fast Challenge Grant Proposal

San Francisco State University has engaged the campus with generative artificial intelligence (AI) programming delivered under the theme of “Sensemaking through Community.” Our bottom-up approach has been successful at creating awareness and campus discussion about generative AI while highlighting pockets of effective generative AI uses in the classroom. Led by the Center for Equity and Excellence in Teaching and Learning (CEETL) and Academic Technology (AT), a series of workshops, individual and department consultations, support materials, campus guidance and policy and a central website were produced last year. 

We believe that department-level engagement is key for our campus to building AI literacy and preparedness for ongoing AI discoveries. We also believe that building guidance from the ground-up through our community sense-making approach can be a national model for campuses like ours, where budgets are tight and teaching loads are high.

In this study, we propose to do a needs assessment to determine levels of faculty preparedness for generative AI at SFSU. Interview data from department chairs will help us build an AI readiness audit tool. One can find many such tools for the technology sector but none exist for higher education yet. This tool would then enable departments and individual faculty to pilot, assess, and identify needs for the use of generative AI tools within their courses and curriculum under a critical and responsible-use lens. The audit tool will provide the scaffolding for a Canvas-based course shell, which will be used by faculty participating in Teaching Squares. 

In Teaching Squares, faculty will come together in groups of their choice: departmental, interdisciplinary or area-focused (such as writing, coding or critical thinking). Teaching Squares will also provide a space and structure for faculty to engage in pedagogical exercises, develop student guidance on generative AI, revise curriculum and investigate discipline impacts and workforce preparation needs for their majors. 

Findings from this study will help us create professional development tool kits, ongoing trainings and workshops as well as an AI-readiness methodology for faculty, departments and academic organizational structures. It will also help build a critical mass of academic departments on our campus that can harness and benefit from generative AI applications in teaching and learning.

The Logic Model provides the project plan, deliverables and short term and long-term outcomes.