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Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/22608

Title: Evaluation of APeLS - an adaptive eLearning service based on the multi-model, metadata-driven approach
Author: CONLAN, OWEN
WADE, VINCENT PATRICK
Author's Homepage: http://people.tcd.ie/owconlan
Keywords: Computer Science
Issue Date: 2004
Publisher: Springer
Citation: Conlan, O., Wade, V. ‘Evaluation of APeLS - an adaptive eLearning service based on the multi-model, metadata-driven approach, Lecture Notes in Computer Science’ in proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH2004), Eindhoven, The Netherlands, August 2004, edited by De Bra, P., Nejdl, W. , 3137, (2004), Springer, pp 291 - 295
Series/Report no.: 3137
2004
Abstract: The evaluation of learner and tutor feedback is essential in the production of high quality personalized eLearning services. There are few evaluations available in the Adaptive Hypermedia domain relative to the amount of research interest this domain is attracting. Many of the papers in this domain focus on the technological design of systems without justifying the designs through the lessons learned from evaluations. This paper evaluates the usability and effectiveness of using the multi-model, metadata-driven approach for producing rich adaptive eLearning solutions that remain content and domain independent. Through this independence, the eLearning services developed can utilize many pedagogical approaches and a variety of models to produce a wide range of highly flexible solutions. This paper identifies benefits to learners brought through adopting the multi-model approach gathered over four years of student evaluation. It briefly describes the evaluation of the Adaptive Personalized eLearning Service (APeLS), a personalized eLearning service based on a generic adaptive engine.
Description: PUBLISHED
URI: http://www.springerlink.com/content/ge95r9210fj6gmpv/fulltext.pdf
https://www.cs.tcd.ie/Owen.Conlan/publications/ah2004_conlan_v1.0_final.pdf
http://hdl.handle.net/2262/22608
ISSN: 37212
Appears in Collections:Computer Science (Scholarly Publications)

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