Intelligent Tutoring System using Rule-based And Case-based: A Comparison

Intelligent Tutoring System (ITS) is one of the solutions due to the need for on-demand tutoring among students nowadays. ITS may provide the students unlimited access to effective and affordable personal tutoring anytime, anywhere. It is developed specially to give a one-to-one tutoring to students while simulating the student-teacher learning environment. The tutoring process includes giving notes, examples, exercises, hints and corrections, similar to in-class tutoring process. The main objective of this study is provide a systematic view of implementing two different artificial intelligence techniques which are rule based and case based reasoning in an ITS for primary school children in the subject of Mathematics. It was built on cognitive models, which represent the knowledge a student might posses about specific subject. The scope of this research covers only for standard six students in the subject of Mathematics, especially in fraction. The objective of this research is to compare the implementation of rule-based and case-based in ITS, based on five features; knowledge representation, learning, search strategy effectiveness, user feedback, incomplete input and knowledge base expansion.