Teaching AI by Doing, Not Studying

Institutions nationwide have responded to the rapid growth of artificial intelligence by introducing everything from drop-in workshops to research centers dedicated to the ever-evolving technology. At the University of Virginia College and Graduate School of Arts & Sciences, a new initiative launched last month aims to establish a more comprehensive framework for how colleges and universities engage with AI.

Developed in partnership with the UVA Library, the AI Literacy and Action Lab is designed to equip students, faculty and staff with structured, evidence-based AI competency embedded directly into courses across disciplines. It will initially be delivered through course pilots led by faculty, a flagship one-credit seminar, a series of three one-credit AI courses and an incubator pathway for AI projects that extend beyond a single semester.

Leo Lo, UVA’s librarian and dean of libraries, said the lab is built on a framework he developed around five core competencies: technical knowledge, ethical awareness, critical thinking, practical skills and an understanding of AI’s societal impact.

“The structure reflects our belief that people are most motivated to learn when they’re working on something they care about—perhaps a problem they want to solve or a question they want answered,” Lo said. “Rather than attending a workshop or sitting through a webinar or lecture, we believe in learning by doing.”

The effort is timely; a recent report from Handshake found that students graduating this year are adopting AI tools at a rapid pace: 85 percent reported using them—up 31 percentage points from two years ago—and more than a third said they use them daily.

Employer demand for those skills is also accelerating. The same report showed that more than 10 percent of active internships on the platform now mention AI-related skills, while the share of full-time job postings referencing AI has nearly doubled year over year to 4.2 percent.

A similar report from EAB found that 42 percent of college-bound students said AI will influence their career choice, and 10 percent said they have already changed their planned major because of it.

Christa Acampora, dean of the College and Graduate School of Arts & Sciences at UVA, said the decision to base the initiative in the library was intentional.

“Librarians have been at the leading edges of information and access to knowledge,” Acampora said. “They were some of the first people in universities to understand the uses of the internet, for example, and its impact on research—not just studying it, but actually using it.”

“It felt like a natural place to anchor this work,” she added. “The library exists to serve all of our students and faculty and all of the big questions we want to pursue. So it makes great sense for librarians to be our primary partners in this effort.”

Other institutions are also turning to campus libraries to advance AI literacy. At Bryn Mawr College, the libraries are emerging as AI sandboxes—shared spaces for experimentation and ethical use. There, librarians facilitate workshops and one-on-one consultations with faculty and students, focusing on AI literacy and practical classroom applications.

The AI initiative: UVA’s lab currently has four pilot projects underway, spanning disciplines from economics to biochemistry.

One pilot, launched this spring, brings together an economics professor and three librarians to offer a course that combines hands-on AI coding with training in critical thinking and ethics. The goal is to explore what responsible use of AI tools looks like in practice and how they may reshape employment, economic growth and inequality.

A second spring pilot places first-year writing seminar students in conversation with students and teachers at a local high school, examining AI’s impact on teaching and learning. Working with an English professor and lab facilitators, students develop lesson plans that model thoughtful AI integration in high school classrooms.

Two additional pilots will launch this fall. One, led by a philosophy professor, will guide student projects exploring potential uses of AI across society, with a focus on building the skills needed to critically evaluate and validate AI outputs. The other, developed by a professor of chemistry and molecular physiology and biological physics, will integrate AI-supported learning into biochemistry courses.

“As you look at the pilots, these are all real-world problems,” Lo said. “Faculty are asking, ‘How can I incorporate AI into teaching and learning?’ And students want to use AI to create something tangible—an artifact they can show future employers that demonstrates how they’ve applied these tools responsibly and ethically.”

AI and the workforce: Looking ahead, Acampora said the pace and scope of AI-driven change may challenge long-held assumptions about how technological innovation shapes employment.

“It’s higher ed’s inclination to say, ‘Oh, there’s a new thing. Let’s study it, and then we’ll understand it,’” Acampora said. “There’s a presumption that having more knowledge or access will make you better prepared for the workforce. But these changes may not follow the pattern of past technological shifts, where new jobs ultimately offset those that were lost.”

“That remains an open question,” she added. “So teaching students to better understand their own human capabilities through the use of these tools—that has real pedagogical power, and that’s where our focus should be.”

Lo echoed that point, emphasizing that developing critical engagement with AI—not blind adoption—is key.

“We’re not pretending AI is perfect,” Lo said. “The technology is improving and changing, but it’s far from it. Even if you’re critical of AI, your arguments become stronger when you understand it better. We want people to build that literacy so they can help shape the technology in the direction they want it to go.”

Get more content like this directly to your inbox. Subscribe here.