Expert Tutoring and Natural Language Feedback in Intelligent Tutoring Systems
|Xin Lu will be defending her thesis this thursday. Details about her defense are outlined below:
Location: SEO 1000
Intelligent tutoring systems can provide benefits of one-on-one instruction automatically and cost effectively. To make the intelligent tutoring systems as effective as expert human tutors, this research aims at investigating what type of natural language feedback an intelligent tutoring system should provide and how to implement the feedback generation to engender significantly more learning than unsupervised practice. This research demonstrates the utility of a computational model of expert tutoring in generating effective natural language feedback in intelligent tutoring systems.
This presentation will start from a comprehensive study of the difference between one expert tutor and two non-expert tutors in effectiveness, behavior and language. Then it will present a rule-based model of expert tutoring which takes advantage of a machine learning technique, Classification based on Associations. The tutorial rules are automatically learned from a set of annotated tutorial dialogues, to model how the expert tutor makes decisions on tutors attitude, domain concepts and problem