A Case-Based Reasoning Approach to Intelligent Tutoring

The goal of this proposed research is to prove the feasibility of a software solution to provide intelligent tutoring for the REGIS Training Center. Because students often learn best by example, we intend to design a tutoring system around example problems. We will apply the Artificial Intelligence (AI) technique of Case-Based Reasoning (CBR) to elicit and represent the example problems (or cases) and provide explanations to students on problem solving techniques. The system would be sensitive to a student\'s knowledge o problem solving principles and tailor the teaching sessions accordingly. The body of knowledge contained in the system could be expanded over time simply through addition of more problems. An intelligent tutoring system is an exciting supplement to traditional classroom instruction. It offers the possibility of individualized teaching and allows the student to work at his own pace, somewhat mitigating the problems of staff cutbacks and increasing complexity of subject area. In Phase I, we will design a generic intelligent tutoring system using a case-based reasoning paradigm. The feasibility of the system will be proven through implementation of a proof-of-concept prototype in a specific domain.