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Abstract
Antipatterns are mechanisms that describe how to arrive at a good (refactored) solution from a fallacious solution that has negative consequences. These mechanisms are used in a variety of computer science topics and although their integration in teaching and computer science curriculum has been proposed, the development of an e-learning system using antipatterns, still remains an open issue. Previous work has proposed the use of WebProtege, a Web-based environment that allows collaborative editing as well as annotation and voting of both components and changes of the antipattern ontology. This ontology has been implemented as the knowledge base of SPARSE, an intelligent system that uses semantic web tools and techniques in order to detect the antipatterns that exist in a software project. In this paper, we leverage this semantic web technology and the formalism of ontology in order to propose a peer-production based e-learning system for the electronically supported learning of antipatterns. We illustrate how this Web-based system can transfer antipattern knowledge using an e-learning scenario as an example.
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Authors and Affiliations
International Institute for Software Technology, United Nations University, Macau SAR, China
Dimitrios Settas & Antonio Cerone
- Dimitrios Settas
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- Antonio Cerone
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Editors and Affiliations
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China
Howard Leung & Rynson W. H. Lau &
Software Engineering Department, University of Craiova, A. I. Cuza 13, 200585, Craiova, Romania
Elvira Popescu
RWTH Aachen University, Informatik, 5, Ahornstr. 55, 52056, Aachen, Germany
Yiwei Cao
Institut für Verteilte Systeme, Wissensbasierte Systeme (KBS), Appelstrasse 4, 30167, Hannover, Germany
Wolfgang Nejdl
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Settas, D., Cerone, A. (2011). An Ontology Based E-Learning System Using Antipatterns. In: Leung, H., Popescu, E., Cao, Y., Lau, R.W.H., Nejdl, W. (eds) Advances in Web-Based Learning - ICWL 2011. ICWL 2011. Lecture Notes in Computer Science, vol 7048. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25813-8_26
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