Adaptive course generation through learning styles representation

This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focused on the construction of an adaptive e-learning platform. The aim of the platform is the automatic generation and personalization of courses, taking into account pedagogical knowledge on the didactic domain as well as statistic information on both the student's knowledge degree and learning preferences. Pedagogical information is described by means of an innovative methodology suitable for effective and efficient course generation and personalization. Moreover, statistic information can be collected and exploited by the system in order to better describe the student's preferences and learning performances. Learning material is chosen by the system matching the student's learning preferences with the learning material type, following a pedagogical approach suggested by Felder and Silverman. The ...

• Type: Journal
• Year: 2008
• Where: UAIS
• Authors: Enver Sangineto, Nicola Capuano, Matteo Gaeta, Alessandro Micarelli
• Keywords: Automatic Course, Learning Material, Personalization, UAIS 2008