For the 2026-27 academic year, Guides are exploring the theme “Advancing Student Learning in the Age of AI,” focusing on how curricula and AI-aware assignments can optimize learning
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The Faculty AI Guides <a href="https://cte.virginia.edu/programs/faculty-ai-guides” rel=”nofollow noopener” target=”_blank”>program is a joint program between the Office of the Executive Vice President and Provost and Center for Teaching Excellence, designed to advance the use and understanding of generative artificial intelligence in education at the University by promoting collaboration between faculty across various disciplines.
The 2026-27 academic year marks the third annual cohort of Faculty AI Guides, who are selected through an application for their interest in AI in education and their knowledge of the field. According to the CTE website, since the program’s start in 2024, 15 members have served two-year terms, and four members have served three-year terms.
According to Ethan King, Faculty AI Guide and assistant English professor, guides are involved in identifying gaps in knowledge around generative AI in education, hosting learning opportunities for faculty and having discussions around how AI can be incorporated into teaching while minimizing cognitive offloading.
Jess Taggart, co-leader of the Faculty AI Guides program, assistant director in the CTE and assistant professor of education development, said that one goal of the Faculty AI Guides program is to enable instructors to make informed decisions about the use of generative AI in their classrooms. Twenty-three faculty were selected for this year, a decrease from the 27 Faculty AI Guides selected for the 2025-26 academic year. However, Taggart said that the quantity of Faculty AI Guides in the program is determined by the amount of funding they receive. Each guide receives $5,500 for their work.
Taggart co-leads the Faculty AI Guides program alongside Andrew Kennedy, assistant director of STEM education initiatives at the CTE, and Derek Bruff, associate director at CTE.
“Our faculty AI Guides have been tasked with better understanding the landscape around AI in teaching and learning, figuring out what they and their colleagues, particularly in their discipline areas, need to know about teaching in this new environment,” Taggart said.
According to Taggart, faculty have a lot of freedom to consider how and whether AI might manifest in their fields of study.
Currently, for this academic year, the theme of the Faculty AI Guides program is“Advancing Student Learning in the Age of AI.” Guides will explore how academic programs can respond to AI at the curricular level and dissect emerging challenges and opportunities surrounding AI in higher education. Further, they will delve into how instructors should incorporate low-tech and AI-free learning experiences that minimize cognitive offloading to AI tools. This is the first cohort since the program’s founding to have a stated theme, and Taggart said the theme was chosen based on the interest expressed from faculty last year.
“The key things that our guides are focusing on this year are … how academic programs can respond to AI, not just at this course level, but at the curricular level,” Taggart said.
According to Taggart, this year’s cohort includes guides who are interested in the impacts of frontier AI models and tools. Frontier AI models are the most advanced AI models available at a given moment.
Ashish Venkat, Faculty AI Guide and William Wulf Career Enhancement Associate Professor of Computer Science, said that he joined the program because he wanted to help build frameworks for meaningful engagement with AI and make them adoptable across different disciplines. Venkat said he was initially drawn to the program because of what he observed and implemented in CS 6354, “Computer Architecture” taught in Fall 2025.
Venkat explained that coding projects often take up a large portion of a computer science course but that these projects can be easily completed by AI. So, instead of the original coding projects, Venkat implemented a new type of project that required students to verify the outputs from an AI model.
“This kind of University-wide program allows you to broaden your perspective, and [generative AI] is a problem … and an opportunity that affects all disciplines, not just engineering disciplines,” Venkat said.
Venkat also noted that his opinions are his own and do not represent the entire Department of Computer Science.
King said that he joined the Faculty AI Guides because he wanted a community and discussion space to unpack how to best use generative AI with other faculty members.
“I felt that there was a disconnect between the student experience of learning in an era of AI and the faculty experience of teaching in an era of AI,” King said. “The particular theme of this year’s AI guide … centers on student learning, and so I’m hoping with the work of other faculty members … there’s opportunities to close that gap between the faculty and student experience.”
Through this program, King said that he also works in a smaller group with other people teaching in the humanities disciplines, which allows them to discuss or workshop ideas around AI-aware teaching. He said approaches to AI vary, but that his goal is to ensure student needs are met regarding AI-use in their education.
“Every class has a different policy, and sometimes some of these policies are more transparent or less transparent than others,” King said. “I’m hoping that this work … is in the service of student needs right now around AI in their education. There’s obviously such a hunger for it amongst our students, and we’ve got to make sure that we’re meeting them where they are.”
Frederick Cheng, Faculty AI Guide and assistant professor of Environmental Science, said that he uses generative AI in some aspects of his research, such as tackling complex issues and analyses, as well as an educational aid in large classrooms.
Through the Faculty AI Guides program, Cheng said that he has worked on events showcasing the different capabilities and educational AI tools available for faculty instructors, as well as experimented with AI “teaching assistants” — not as a replacement for student teaching assistants, but instead as a way to provide students with low-stakes interactions and feedback to enhance learning.
“I think one of the biggest challenges with AI in the current teaching landscape is that a lot of us recognize that it’s a very powerful and useful tool,” Cheng said. “The question of where it comes in … within our courses without AI short-circuiting learning is the main concern.”
Charlotte Gabriel is a second-year Commerce and College student, and she serves as a staff writer on the news desk.
