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A context-aware adaptive learning system using agents

Evolution of Web technologies has made e-learning a popular common way of education and training. As an outcome, learning content adaptation has been the subject of many research projects lately. This paper suggests a framework for building an adaptive Learning Management System (LMS). The proposed...

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Main Authors:	Yaghmaie, Mahkameh, Bahreininejad, Ardeshir
Format:	Article
Published:	Elsevier 2011
Subjects:	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.um.edu.my/2069/ https://doi.org/10.1016/j.eswa.2010.08.113
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id	my.um.eprints.2069
record_format	eprints
spelling	my.um.eprints.20692019-02-13T03:39:19Z http://eprints.um.edu.my/2069/ A context-aware adaptive learning system using agents Yaghmaie, Mahkameh Bahreininejad, Ardeshir QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) Evolution of Web technologies has made e-learning a popular common way of education and training. As an outcome, learning content adaptation has been the subject of many research projects lately. This paper suggests a framework for building an adaptive Learning Management System (LMS). The proposed architecture is based upon multi-agent systems and uses both Sharable Content Object Reference Model (SCORM) 2004 and semantic Web ontology for learning content storage, sequencing and adaptation. This system has been implemented upon a well known open-source LMS and its functionalities are demonstrated through the simulation of a scenario mimicing the real life conditions. The result reveals the system effectiveness for which it appears that the proposed approach may be very promising. Elsevier 2011-04 Article PeerReviewed Yaghmaie, Mahkameh and Bahreininejad, Ardeshir (2011) A context-aware adaptive learning system using agents. Expert Systems with Applications, 38 (4). pp. 3280-3286. ISSN 0957-4174 https://doi.org/10.1016/j.eswa.2010.08.113 doi:10.1016/j.eswa.2010.08.113
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General)
spellingShingle	QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) Yaghmaie, Mahkameh Bahreininejad, Ardeshir A context-aware adaptive learning system using agents
description	Evolution of Web technologies has made e-learning a popular common way of education and training. As an outcome, learning content adaptation has been the subject of many research projects lately. This paper suggests a framework for building an adaptive Learning Management System (LMS). The proposed architecture is based upon multi-agent systems and uses both Sharable Content Object Reference Model (SCORM) 2004 and semantic Web ontology for learning content storage, sequencing and adaptation. This system has been implemented upon a well known open-source LMS and its functionalities are demonstrated through the simulation of a scenario mimicing the real life conditions. The result reveals the system effectiveness for which it appears that the proposed approach may be very promising.
format	Article
author	Yaghmaie, Mahkameh Bahreininejad, Ardeshir
author_facet	Yaghmaie, Mahkameh Bahreininejad, Ardeshir
author_sort	Yaghmaie, Mahkameh
title	A context-aware adaptive learning system using agents
title_short	A context-aware adaptive learning system using agents
title_full	A context-aware adaptive learning system using agents
title_fullStr	A context-aware adaptive learning system using agents
title_full_unstemmed	A context-aware adaptive learning system using agents
title_sort	context-aware adaptive learning system using agents
publisher	Elsevier
publishDate	2011
url	http://eprints.um.edu.my/2069/ https://doi.org/10.1016/j.eswa.2010.08.113
_version_	1643686835585548288
score	13.211869

A context-aware adaptive learning system using agents

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