Abstract
In this paper we describe an Integrated Development System for Instructional Model for E-learning (INDESIME) to create and to maintain instructional models using adaptive technologies and collaborative tools. An authoring tool has also been developed for helping to non-programming users to create Learning Management Systems (LMSs) courses that implement a specific instructional model. Data mining techniques are proposed to evaluate the e-learning courses generated from the model. We have tested the degree of effectiveness of our system using Moodle courses. The courses topics tested are based on the European Computer Driving Licence Foundation catalogue.
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References
WebCT Inc. Learning management system WebCT (2005), http://www.webct.com/
BlackBoard Inc. Learning management system BlackBoard (2005), http://www.blackboard.com/
WBT Systems. Learning management system TopClass (2005), http://www.wbtsystems.com/
Dougiamas, M., et al.: Course management system MOODLE (2005), http://www.moodle.org/
Leidhold, W., et al.: Learning management system ILIAS (2005), http://www.ilias.de/ios/index-e.html
Gay, G., et al.: Learning management system ATutor (2005), http://www.atutor.ca/
Brusilovsky, P.: Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education 13, 159–169 (2003)
Brusilovsky, P., Schwarz, E., Weber, G.: ELM-ART: An intelligent tutoring system on World Wide Web. In: Lesgold, A.M., Frasson, C., Gauthier, G. (eds.) ITS 1996. LNCS, vol. 1086, pp. 261–269. Springer, Heidelberg (1996)
Brusilovsky, P., Schwarz, E., Weber, G.: ELM-ART: An intelligent tutoring system on World Wide Web. In: Third International Conference on Intelligent Tutoring Systems, pp. 261–269 (1995)
Brusilovsky, P., Eklund, J., Schwarz, E.: Web-based education for all: A tool for developing adaptive courseware. Computer Networks and ISDN Systems 30(1-7), 291–300 (1998)
Carro, R.M., Pulido, E., Rodrígues, P.: TANGOW. Computer Science Report, Eindhoven University of Technology. pp. 49–57 (1999)
De Bra, P., Calvi, L.: AHA! An Open Adaptive Hypermedia Architecture. The New Review of Hypermedia and Multimedia, vol. 4, pp. 115–139. Taylor Graham Publishers (1998)
Weber, G.: ART-WEB. University of Trier, Trier (1999)
Romero, C., Ventura, S.: Educational data mining: A survey from 1995 to 2005. International Journal Experts Systems with Applications 33(1), 135–146 (2007)
Reigeluth, C.: A new paradigm of instructional theory, vol. II. Lawrence Erlbaum Associates Inc., Mahwah (1999)
Gros, B., et al.: Instructional Design and the Authoring of Multimedia and Hypermedia Systems: Does a Marriage make Sense? Educational Technology 1(37), 48–56 (1997)
D’Angelo, G.: From didactics to e-didactics. E-learning paradigms, models and techniques. Liguori Editori (2007)
Guardià, L., Sangrà, A.: Instructional design and learning objects; towards a model for the design of online learning evaluation activities. In: Proceedings of the First Pluri-Disciplinary Symposium on Design, Evaluation and Description of Reusable Learning Contents, Guadalajara, Spain (2004)
Chiappe, A.: Modelo de diseño instruccional basado en objetos de aprendizaje. Universidad de la Sabana, Colombia (2006), http://oas.unisabana.edu.co/files/MDIBOA.pdf
Advanced Distributed Learning. Shareable content object reference model (SCORM): The SCORM overview (2005), http://www.adlnet.org
Wu, H., Houben, G.J., De Bra, P.: AHAM: A Dexter-based Reference Model for Adaptive Hypermedia. In: Proceedings of the ACM Conference on Hypertext and Hypermedia, Darmstadt, Germany, pp. 147–156 (1999)
Zheng, Z., et al.: Real world performance of association rules. In: Proceedings of the Sixth ACM-SIGKDD (2001)
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. Proceedings of 20th VLDB CVonf. Santiago de Chile (1996)
Scheffer, T.: Finding Association Rules That Trade Support Optimally against Confidence. Intelligent Data Analysis 9(4), 381–395 (2005)
García, E., Romero, C., Ventura, S., de Castro, C.: An architecture for making recommendations to courseware authors through association rule mining and collaborative filtering. UMUAI: User Modelling and User Adapted Interaction 19(1-2), 99–132 (2009)
Advanced Distributed Learning. Shareable content object reference model (SCORM): The SCORM overview (2009), http://www.adlnet.org
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García, E., Romero, C., Ventura, S., de Castro, C. (2009). Evaluating Web Based Instructional Models Using Association Rule Mining. In: Houben, GJ., McCalla, G., Pianesi, F., Zancanaro, M. (eds) User Modeling, Adaptation, and Personalization. UMAP 2009. Lecture Notes in Computer Science, vol 5535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02247-0_5
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DOI: https://doi.org/10.1007/978-3-642-02247-0_5
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