Knowledge Management: Problems, Promises, Realities, and Challenges
IEEE Intelligent Systems
Sweetening Ontologies with DOLCE
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Personalization in distributed e-learning environments
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Bridging the gap between knowledge management and e-learning with context-aware corporate learning
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
IRS-III: a broker for semantic web services based applications
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Expert Systems with Applications: An International Journal
Learning object retrieval in heterogeneous environments
International Journal of Web Engineering and Technology
Personal learning environments on the Social Semantic Web
Semantic Web - Linked Data for science and education
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The current state of the art in supporting e-learning objectives is primarily based on providing a learner with learning content by using metadata standards. Due to this approach, several issues have to be taken into account --- e. g. limited re-usability across different standards and learning contexts and high development costs. To overcome these issues, this paper describes an innovative semantic web service-oriented framework aimed at changing this data- and metadata-based paradigm to a highly dynamic service-oriented approach. Instead of providing a learner with static data, our approach is based on fulfilling learning objectives based on a dynamic supply of services. Therefore, we introduce a semantic layer architecture to abstract from existing learning data as well as process metadata standards by using Semantic Web Service (SWS) technology. Furthermore, our approach is based on abstract and reusable learning process models describing a learning process semantically as a composition of learning goals. Based on the formal semantic descriptions of learning goals as well as web services, services appropriate to achieve a specific learning goal can be selected, composed and invoked dynamically. This supports a high level of re-usability since a dynamic adaptation to different learning contexts and requirements of individual learners is achieved while utilizing standard-compliant learning applications. To illustrate the application of our approach, we describe a prototypical implementation utilizing the introduced approach based on the SWS framework WSMO.