ABSTRACT
Since the beginning of research in artificial intelligence several attempts have been made to construct intelligent tutorial systems (ITS). Such an ITS consists in general of a representation of the knowledge in a special domain, a diagnostic procedure to determine the knowledge of a student working with the system, teaching material, and a procedure for adaptive teaching. This chapter demonstrates how an extension of the theory of knowledge spaces can be used for the design of a domain-independent ITS. The main components of this ITS are a representation of the skills necessary in the knowledge domain and their depen-dencies as a surmise system, a set of questions related through a skill assignment to the skill states used for knowledge diagnosis, and a rule that relates skill states to teaching operations. The ITS is adaptive with respect to the consideration of the prior knowledge a student possess and with respect to the learning speed of a student. The strict formalized description of the systems components and their interactions during the teaching process guarantees that an ITS with the described properties can be implemented easily.
