XML-based adaptation framework for psychological-driven E-learning

E-learning systems grew to popular knowledge delivery systems until now. Several applications have already been implemented and many project initiatives have been started. Although such systems come with interesting advantages, there are still many unsolved problems. Enriching common learning content by applying multimedia did not meet the general expectation to decrease drop out rates of e-learners using such systems. Additionally, most e-learners complain about a "one-size-fits-all" philosophy, a resulting cognitive overload and consequently the lack of personalization of existing applications. In this paper a user-centric approach is presented in order to improve the usability and acceptance, thus, making e-learning systems more successful. For this purpose psychological factors are integrated in an adaptable learning system which is based on meta data enriched learning objects specified and described in XML documents. General learning objects are transformed into personalized learning objects depending on the user profile and adaptation rules. Beside learning objects also layout and navigation through the content are adapted and personalized. An adaptation framework is introduced to show the interaction of the discussed concepts to fulfill the request for individualized learning systems.