User Profile Modeling in the context of web-based learning management systems

Kritikou, Y; Demestichas, P; Adamopoulou, E; Demestichas, K; Theologou, M; Paradia, M

dc.contributor.author	Kritikou, Y	en
dc.contributor.author	Demestichas, P	en
dc.contributor.author	Adamopoulou, E	en
dc.contributor.author	Demestichas, K	en
dc.contributor.author	Theologou, M	en
dc.contributor.author	Paradia, M	en
dc.date.accessioned	2014-03-01T01:29:27Z
dc.date.available	2014-03-01T01:29:27Z
dc.date.issued	2008	en
dc.identifier.issn	1084-8045	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19268
dc.subject	Bayesian Networks	en
dc.subject	E-learning system	en
dc.subject	User modeling	en
dc.subject	User Profile	en
dc.subject.classification	Computer Science, Hardware & Architecture	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.subject.other	Bayesian networks	en
dc.subject.other	Distributed parameter networks	en
dc.subject.other	Education	en
dc.subject.other	Inference engines	en
dc.subject.other	Intelligent networks	en
dc.subject.other	Internet	en
dc.subject.other	Learning systems	en
dc.subject.other	Management	en
dc.subject.other	Multimedia systems	en
dc.subject.other	Network architecture	en
dc.subject.other	Speech analysis	en
dc.subject.other	Statistical tests	en
dc.subject.other	Bayesian	en
dc.subject.other	E learning	en
dc.subject.other	E learning platform	en
dc.subject.other	e-learning systems	en
dc.subject.other	Elsevier (CO)	en
dc.subject.other	Focal points	en
dc.subject.other	In order	en
dc.subject.other	Learning services	en
dc.subject.other	Personalization	en
dc.subject.other	Research efforts	en
dc.subject.other	Special needs	en
dc.subject.other	User modelling	en
dc.subject.other	User preferences	en
dc.subject.other	user profiling	en
dc.subject.other	User's preferences	en
dc.subject.other	Web based learning	en
dc.subject.other	E-learning	en
dc.title	User Profile Modeling in the context of web-based learning management systems	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.jnca.2007.11.006	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.jnca.2007.11.006	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Over the past two decades, great research efforts have been made towards the personalization of e-learning platforms. This feature increases remarkably the quality of the provided learning services, since the users' special needs and capabilities are respected. The idea of predicting the users' preferences and adapting the e-learning platform accordingly is the focal point of this paper. In particular, this paper starts with the main requirements of an advanced e-learning system, explains the way a user navigates in such a system, presents the architecture of a corresponding e-learning system and describes its main components. Research is focused on the User Model component, its role in the e-learning system and the parameters that comprise it. In this context, Bayesian Networks are used as a tool for the encoding, learning and reasoning of probabilistic relationships, with the aim to effectively predict user preferences. In support of this vision, four different scenarios are presented, in order to test the way Bayesian Networks apply in the c-learning field. (C) 2007 Elsevier Ltd. All rights reserved.	en
heal.publisher	ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD	en
heal.journalName	Journal of Network and Computer Applications	en
dc.identifier.doi	10.1016/j.jnca.2007.11.006	en
dc.identifier.isi	ISI:000262946600014	en
dc.identifier.volume	31	en
dc.identifier.issue	4	en
dc.identifier.spage	603	en
dc.identifier.epage	627	en