This paper describes a prototype system that uses machine learning to acquire domain knowledge for an Intelligent Tutoring System in propositional logic. The system uses a form of inductive learning to learn a hierarchy of operators by taking instructions from a human expert. It successfully demonstrates that domain knowledge can be effectively acquired through instruction and integrated into a tutorial framework.
Intelligent Tutoring System, Knowledge Acquisition, Machine Learning