EAAI-13 Invited Talk: Learning in the Lab at Midnight: Experiences from Teaching AI at Berkeley and Online
ABSTRACT. Where does learning really happen? Only a little happens in lecture; most students learn much more working with friends in the lab at midnight. The modern student experience increasingly revolves around coursework, peer assistance, and asynchronous interactions — not lectures, textbooks, and office hours. With these trends only increasing as enrollments rise and online channels emerge, how should we design our AI courses?
I'll talk about the best answers we've found so far for the Berkeley AI course. One key component of our approach is a set of thematically coherent, autograded projects that engage students and integrate with lectures in an ongoing way. More generally, I'll focus on several questions that have shaped our course, including: What should the role of a modern lecture be? What's the balance between cooperative learning and competition? When is an autograder more useful than a human TA? Why are students even taking AI in the first place? Finally, I'll talk about how technology that we originally developed for pedagogical purposes, such as rich autograding, has helped the course scale from tens to hundreds of students on campus and now to tens of thousands online.
Our experiences have resulted in a large number of re-usable materials, which we're always excited to share. I'll conclude with a discussion of how other instructors can take advantage of our lectures, interactive assignments, and autograded projects, which have already been used by over a hundred AI courses.