Learning style based personalization of SCORM e-learning courses

Abstract

This paper presents a system for learning style based personalization of e-learning courses. The courses are created according to SCORM standard. Student learning style is defined using Felder-Silverman model. For each learning style specific adaptation actions are presented. The paper analyzes different meta-data sets for describing learning content. Presented system is added as an extension to an e-learning system Sakai.