Friday, Feb. 3
M1-09 (Brickyard mezzanine)
Adapting to student states in a spoken tutorial dialogue system for physics
Diane Litman, professor of computer science, University of Pittsburgh
It has been hypothesized that human tutoring might be so effective because of its use of natural language dialogue. Potential advantages of natural language dialogue as a learning environment include providing opportunities for both the tutor to infer information about a student and the student to participate more actively in the learning process. In this talk Litman describes the design and evaluation of several versions of an adaptive spoken dialogue system for tutoring physics, that uses speech and natural language processing to detect and respond to student states such as uncertainty and disengagement.
She will discuss the empirical approach used to design and implement the system, then present experimental results suggesting that computer tutoring that monitors and adapts to user states over and above correctness can significantly improve both cognitive and metacognitive student abilities.
Bio: Diane Litman is professor of computer science, Senior Scientist with the Learning Research and Development Center and faculty with the Graduate Program in Intelligent Systems, all at the University of Pittsburgh. She received her Ph.D. degree in computer science from the University of Rochester, and was previously a member of the Artificial Intelligence Principles Research Department, AT&T Labs–Research (formerly Bell Laboratories).