A Knowledge-Based Approach to Describe and Adapt Learning Objects
Amel Bouzeghoub, Bruno Defude, Freddy Duitama, Claire Lecocq, GET/INT, France
International Journal on E-Learning Volume 5, Number 1, ISSN 1537-2456 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Our claim is that semantic metadata are required to allow a real reusing and assembling of learning objects. Our system is based on three models used to describe the domain, learners, and learning objects. The learning object model is inspired from knowledge representation proposals. A learning object can be reused directly or can be combined with other learning objects using composition operators with well-defined semantic. Using these models we are able to define powerful search tools and an adaptive environment taking as input the learner model to construct the learning object to deliver. We are currently implementing this system using Sesame, an RDF repository.
Bouzeghoub, A., Defude, B., Duitama, F. & Lecocq, C. (2006). A Knowledge-Based Approach to Describe and Adapt Learning Objects. International Journal on E-Learning, 5(1), 95-102. Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).
© 2006 Association for the Advancement of Computing in Education (AACE)
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Juergen Heller, Christina Steiner, Cord Hockemeyer & Dietrich Albert, University of Graz, Austria
International Journal on E-Learning Vol. 5, No. 1 (2006) pp. 75–88
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