An algorithm for peer review matching using student profiles based on fuzzy classification and genetic algorithms

Abstract

In the context of Intelligent Tutoring Systems, there is a potential for adapting either content or its sequence to student as to enhance the learning experience. Recent theories propose the use of team-working environments to improve even further this experience. In this paper an effective matching algorithm is presented in the context of peer reviewing applied to an educational setting. The problem is formulated as an optimization problem to search a solution that satisfies a set of given criteria modeled as "profiles". These profiles represent regions of the solution space to be either favored or avoided when searching for a solution. The proposed technique was deployed in a first semester computer engineering course and proved to be both effective and well received by the students. © Springer-Verlag Berlin Heidelberg 2005.