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"METADATA-BASED PERSONALISATION OF eLEARNING CONTENTS" eLearning and eResearch in the Arab World, SRO'05, Fez, Marokko, Oct. 26-30,2008

Dr.-Ing. Ali Diab
Dr.-Ing. Heinz- Dietrich Wuttke
Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel
Dr.-Ing. Prof. h. c. Karsten Henke
Date of publication
The increasing importance of eLearning and its role in modernizing the teaching and learning methods can be seen from the huge amount of new offered eLearning courses and research projects. Although, new technologies and in particular the Internet has opened many new opportunities that are of a big interest for eLearning environments, these opportunities have not yet been exhausted. For example, the management of large amounts of information, the provision of eLearning contents and the dealing with the users show that many demands remain to be met. One of these demands is the design and the implementation of adaptive eLearning environments that are able to personalize the eLearning contents so that each user obtains contents that are sufficient for him. The current eLearning environments offer little or no support for adaptivity. Therefore, developing new adaptive eLearning environments that are able to satisfy the user’s requirements is of a big interest nowadays. This paper addresses the adaptivity issue and describes the architecture of a new Metadata-driven Adaptive eLearning Environment (MAeLE), which is a new framework for personalized adaptive eLearning. The basic principle of MAeLE depends on delivering adequate metadata for the user as well as for eLearning contents. The eLearning contents themselves do not contain any sequence logic or metadata. User metadata are updated from time to time depending on the user’s behavior in the offered courses. His metadata correlates to the contents metadata that mainly depends on a Learning Object Metadata (LOM) standard. According to the user characteristics existing in the user model, the eLearning contents, eLearning strategy and a navigation method are selected and updated from time to time correspondingly. A main advantage of MAeLE is its flexibility, extensibility and compatibility to the Sharable Content Object Reference Model standard.
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