Reference : An Architecture for E-Learning System with Computational Intelligence

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/17178

Title :	An Architecture for E-Learning System with Computational Intelligence
Language :	English
Author, co-author :	El Alami, Marc [University of Luxembourg > Central Administration > IT Department]
	Casel, Nicolas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Zampunieris, Denis [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	2007
Main document title :	Proceedings of KES - International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, September 2007, Vietri sul Mare (Italy)
Editor :	Apolloni, B.
Publisher :	Springer-Verlag Berlin Heidelberg
Collection and collection volume :	LNAI-4693
Pages :	58-65
Peer reviewed :	Yes
On invitation :	No
Audience :	International
ISBN :	978-3-540-74826-7
Event name :	Proceedings of “KES - International Conference on Knowledge-Based and Intelligent Information & Engineering Systems”, September 2007, Vietri sul Mare (Italy)
Event date :	September 2007
Event place (city) :	Vietri sul Mare
Event country :	Italy
Keywords :	[en] e-learning ; learning management system ; rules-based expert system ; computational intelligence
Abstract :	[en] In this paper, we introduce a new kind of software tools intended to offer a virtual educational and/or training environment online: proactive e-Learning Management Systems. These computational intelligence based systems are designed to improve the users’ online (inter)actions by providing programmable, automatic and continuous intelligent analyses of the users’ behaviors, augmented with appropriate actions initiated by the LMS itself. We show how we implemented the proactive part of our LMS on the basis of a dynamic rules-based expert system. We also sketch how it looks like from a user’s point of view. Finally, We give some examples of intelligent analysis of users’ behaviors coded into proactive rules.
Permalink :	http://hdl.handle.net/10993/17178
Mentions required by the publisher for OA :	(C) Springer-Verlag Berlin Heidelberg 2007
Commentary :	Proceedings of “KES - International Conference on Knowledge-Based and Intelligent Information & Engineering Systems”, September 2007, Vietri sul Mare (Italy)

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