Identification of felder-silverman learning styles with a supervised neural network

Abstract

In this paper, we present an intelligent tool implemented as a learning social network. An author can create, display, and share lessons, intelligent tutoring systems and other components among communities of learners in web-based and mobile environments. The tutoring systems are tailored to the student's learning style according to the model of Felder-Silverman. The identification of the student's learning style is performed using self-organizing maps. The main contribution of this paper is the implementation of a learning social network to create, view and manage adaptive and intelligent tutoring systems using a new method for automatic identification of the student's learning style. We present the architecture of the social network, the method for identifying learning styles, and some experiments made to the social network. © 2010 Springer-Verlag Berlin Heidelberg.