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Klebl, Michael; Kramer, Bernd J.; Zobel, Annett – British Journal of Educational Technology, 2010
For technology-enhanced learning, the idea of "learning objects" transfers the technologies of content management, methods of software engineering and principles of open access to educational resources. This paper reports on CampusContent, a research project and competence centre for e-learning at FernUniversitat in Hagen that designed…
Descriptors: Foreign Countries, Electronic Learning, Educational Practices, Educational Technology
Holzinger, Andreas; Kleinberger, Thomas; Muller, Paul – 2001
One of the "hottest" topics in recent information systems and computer science is metadata. Learning Object Metadata (LOM) appears to be a very powerful mechanism for representing metadata, because of the great variety of LOM Objects. This is on of the reasons why the LOM standard is repeatedly cited in projects in the field of eLearning…
Descriptors: Computer System Design, Distance Education, Educational Resources, Educational Technology
Steinacker, Achim; Faatz, Andreas; Seeberg, Cornelia; Rimac, Ivica; Hormann, Stefan; El Saddik, Abdulmotaleb; Steinmetz, Ralf – 2001
This paper gives an overview of MediBook, a joint project of the Medical Department of the University GieBen (Germany) and the Department of Electrical Engineering and Information Technology at Darmstadt University of Technology (Germany) funded by the Hessian Ministry for Science and Arts (HMWK). The basis of MediBook is a formal representation…
Descriptors: Computer System Design, Educational Media, Educational Resources, Educational Technology
Brase, Jan; Painter, Mark – Educational Technology & Society, 2004
Learning Objects Metadata (LOM) aims at describing educational resources in order to allow better reusability and retrieval. In this article we show how additional inference rules allows us to derive additional metadata from existing ones. Additionally, using these rules as integrity constraints helps us to define the constraints on LOM elements,…
Descriptors: Inferences, Metadata, Information Retrieval, Standards