Generative AI is already reshaping how students learn, write, and prepare for their careers, and how faculty teach and conduct research. Good resources for building generative AI fluency exist across Penn, but coverage is uneven and often depends on individual faculty seeking things out on their own. DDDI supports Penn faculty in developing a working understanding of generative AI and in deciding, on their own terms, whether and how to bring it into their teaching and scholarship.

To meet faculty where they are, DDDI offers multiple entry points rather than a single required course. Faculty Minicourse, an intensive, hands on introduction to how modern generative AI systems actually work, taught by DDDI Co Director Bhuvnesh Jain along with colleagues from Computer and Information Science, Wharton, CETLI, and Penn Libraries, held in June 2026. For departments that want ongoing, discipline specific support, AI Training builds a network of peer faculty partners who bring tailored generative AI sessions and materials directly to their own colleagues, backed by optional graduate student office hours. And for faculty who want to go deeper and actively shape how generative AI is used in their own classroom, AI Innovation, led by Penn GSE, offers a structured research partnership that co designs, tests, and refines generative AI enhanced teaching activities over a full semester.

The Faculty Minicourse

How AI Works is a two day, eight hour minicourse for Penn faculty across disciplines, held June 2 to 3, 2026, covering how modern generative AI systems work and how to evaluate their use in teaching and research, with no technical background required. It is taught by Bhuvnesh Jain (Physics & Astronomy), with guest lecturers Chris Callison Burch (Computer and Information Science) and Laura Zarrow (Wharton Generative AI Labs), and lab sessions led by Rachel Hoke (CETLI) and Jajwalya Karajgikar (Penn Libraries). The course moves through six modules on the fundamentals of AI, data driven models, neural networks, large language models, and the limitations and future of generative AI, ending with a hands on lab where participants build a custom AI tool for their own teaching or research.

AI Training

AI Fluency for Teaching is a peer led initiative that trains one or two AI faculty partners in each department to run a discipline specific, two hour AI for teaching session for their own colleagues, using shared materials they can adapt to their field. Partners get an informal orientation session and, where useful, funded graduate student office hours, so departments can offer ongoing, tailored support without waiting on a central course.

AI Innovation (lead by Penn GSE)

Led by Penn GSE, the Penn AI Pedagogy Initiative pairs interested faculty with a learning sciences researcher and a student technical partner to co design AI enhanced activities for an actual course they are teaching. Over a sixteen week cycle, the team observes the classroom, prototypes tools such as custom tutors or digital personas, tests them with students, and contributes the results to a shared teaching repository open to educators worldwide.