Exploiting knowledge representation in an intelligent tutoring system for English lexical errors

Intelligent tutoring systems (ITSs) construction requires lots of domain knowledge created by hand. In this paper we attempt to illustrate a central role that knowledge representation can play in automating ITS design and implementation. We propose a diagnosis, interaction and treatment (DIT) model for ITS. The entire system relies upon a knowledge representation system (InfoMap) whose structured encoding of English lexical information makes it possible to (1) initiate the relevant dialogue with learners when the system is not sure about learners' intentions, (2) trigger the appropriate lexical knowledge based on their responses, and (3) automatically generate practice and test exercises based on this knowledge.