Metadata Driven Approaches to Facilitate Adaptivity in Personalized eLearning Systems

Abstract

Personalized eLearning Systems tailor the learning experience to characteristics of individual learners. These tailored course offerings are often comprised of discrete electronic learning resources, such as text snippets, interactive animations, diagrams, and videos. An extension of standard metadata schemas developed for facilitating the discovery and reuse of such adaptive learning resources can also be utilized by the eLearning systems for realizing the adaptivity. An important feature of such reuse supporting adaptive systems is the clear distinction of separate models and components within the teaching process.