Assistant Professor Chelsea Finn and her team designed a neural network system solely for Stanford's programming class. They used techniques that could automate student feedback in other situations, including for classes beyond programming.
Chelsea's system spent hours analyzing examples from old midterms, learning from a decade of possibilities. Then it was ready to learn more. When given just a handful of extra examples from the new exam offered this spring, it could quickly grasp the task at hand.
"It sees many kinds of problems," said PhD candidate Mike Wu. "Then it can adapt to problems it has never seen before."
This spring, the system provided 16,000 pieces of feedback, and students agreed with the feedback 97.9 percent of the time, according to a study by the researchers. By comparison, students agreed with the feedback from human instructors 96.7 percent of the time.
Chelsea Finn is an assistant professor of electrical engineering and computer science.
Excerpted from The New York Times, "Can A.I. Grade Your Next Test?"