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Towards adaptive e-learning applications based on Semantic Web Services

Dietze, Stefan; Gugliotta, Alessio and Domingue, John (2007). Towards adaptive e-learning applications based on Semantic Web Services. In: Griffiths, David; Koper, Rob and Liber, Oleg eds. Service Oriented Approaches and Lifelong Competence Development Infrastructures. Bolton: The Institute for Educational Cybernetics, University of Bolton, pp. 75–83.

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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 like ADL SCORM 2004 or IMS Learning Design. By following this approach, several issues can be observed including high development costs due to a limited reusability across different standards and learning contexts. To overcome these issues, our approach changes this data-centric paradigm to a highly dynamic service-oriented approach. By following this approach, learning objectives are supported based on a automatic allocation of services instead of a manual composition of learning data. Our approach is fundamentally based on current Semantic Web Service (SWS) technology and considers mappings between different learning metadata standards as well as ontological concepts for E-Learning. Since our approach is based on a dynamic selection and invocation of SWS appropriate to achieve a given learning objective within a specific learning context, it enables the dynamic adaptation to specific learning needs as well as a high level of reusability across different learning contexts.

Item Type: Book Section
Copyright Holders: 2007 Not known
ISBN: 0-907311-22-9, 978-0-907311-22-5
Extra Information: Proceedings of the 2nd TENCompetence Open Workshop, held Manchester, UK, 11th and 12th January 2007
Keywords: Semantic Web Services; learning applications; learning processes; WSMO; learning standards; ADL SCORM; IMS learning design
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 23042
Depositing User: Kay Dave
Date Deposited: 01 Oct 2010 10:32
Last Modified: 14 Jan 2019 19:44
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