Learning what is important to learn, some experiments with inductive logic programming.
François Jacquenet, Bernard Marc, Claire Nicolini · 1999
Most Intelligent Tutoring Systems (ITS) nowadays integrate some Artificial Intelligence techniques to improve the quality of the Computer Aided Tutor. Knowledge bases, reasoning techniques, can be widely used. Nevertheless, the problem is "What is important to learn for a student". This question is an important bottleneck for the design of a good and efficient ITS. From the way we answer to it will depend the success of the ITS being designed. In this paper, we propose to integrate some Machine Learning techniques in ITS to allow them to automatically improve their knowledge bases and reasoning facilities. 1 Introduction Most Intelligent Tutoring Systems (ITS) designed nowadays integrate some Artificial Intelligence techniques to improve their performances. Knowledge bases, reasoning techniques, can be widely used in that context. In fact, when one design an ITS, the main question we must ask ourselves is : What is important to learn for a student? The answer to this question will in...