A novel expert evaluation methodology based on fuzzy logic

Abstract

In order to maintain the training quality and ensure efficient learning, the introduction of a scalable and well-adapted evaluation system is essential. An adequate evaluation system will positively involve students in the evaluation of their own learning, as well as providing teachers with indicators on the student's strengths, the specific encountered difficulties and the false or misunderstood studied parts. In this context, we present, in this article, a novel intelligent evaluation methodology based on fuzzy logic and knowledge based expert systems. The principle of this methodology is to reify abstract concepts of a human expertise in a numerical inference engine applied to evaluation. It reproduces, therefore, the cognitive mechanisms of evaluation experts. An implementation example is presented to compare this method with the classical one and draw conclusions about its efficiency. Furthermore, thanks to its flexibility, different kinds of extensions are possible by updating the basic rules and adjusting to possible new architectures and new types of evaluation.