EdMedia + Innovate Learning, in Montreal, Canada ISBN 978-1-880094-56-3 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Learning Management Systems generally offer big repositories of learning material, but the lack of publicly available metadata to describe the learning objects makes it very difficult to share and reuse these objects. If metadata could be generated for these objects in order to index them in Learning Object Repositories (LOR), the gained amount of resources could solve the sub-critical mass problem of most existing Learning Object Repositories. This work proposes two frameworks that could facilitate the implementation of Automatic Indexers for LMS content. Prototype implementations of Automatic Indexing Systems following these frameworks for real LMSs (SIDWeb and Toledo-Blackboard) show that the amount of effort needed to construct them was small compared with the benefits that this kind of systems could have. While the metadata seems to be good enough at first sight, further research of the quality of automatically generated metadata is needed.
Ochoa, X., Cardinaels, K., Meire, M. & Duval, E. (2005). Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories. In P. Kommers & G. Richards (Eds.), Proceedings of ED-MEDIA 2005--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 1407-1414). Montreal, Canada: Association for the Advancement of Computing in Education (AACE).
© 2005 Association for the Advancement of Computing in Education (AACE)
Adaptation criteria for the personalised delivery of learning materials: A multi-stage empirical investigation
Stefan Thalmann, University of Innsbruck School of Management Information Systems
Australasian Journal of Educational Technology Vol. 30, No. 1 (Apr 03, 2014)
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