Intelligent computer-assisted instruction: a theoretical framework

Abstract

A theoretical and psychologically meaningful framework for the design of intelligent computer-assisted instruction (ICAI) systems is presented. It is argued that to design more effective and robust ICAI systems a thorough knowledge level analysis of the problem should be performed before implementation issues can be addressed. To this end, with the aid of artificial intelligence (AI) techniques and a knowledge level analysis of the problem an appropriate knowledge representation scheme and system architecture are proposed. It is further suggested that a suitable knowledge representation scheme should be psychologically valid and ideally modelled after a human tutor. One such representation, namely, Schank and Abelson's memory structures, is chosen and shown to be well matched to the requirements of an intelligent tutoring system. It models the basic memory structures of both the student and tutor upon which the goals, plans, and themes of these agents may be built. A blackboard control architecture which provides an extremely flexible environment for intelligent systems is also chosen, and is claimed to be in agreement with ICAI knowledge level requirements. A limited example is finally detailed demonstrating the applicability of this framework to ICAI systems.