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SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology

In this era of knowledge economy in which knowledge have become the most precious resource, surveys have shown that e-Learning has been on the increasing trend in various organizations including, among others, education and corporate. The use of e-Learning is not only aim to acquire knowledge but...

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Main Author: Mukhlason, Ahmad Mukhlason
Format: Thesis
Language:English
Published: 2009
Online Access:http://utpedia.utp.edu.my/2889/1/AhmadMukhlason_Thesis_Final_Thesis_MSc_IT_2009.pdf
http://utpedia.utp.edu.my/2889/
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spelling my-utp-utpedia.28892017-01-25T09:44:08Z http://utpedia.utp.edu.my/2889/ SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology Mukhlason, Ahmad Mukhlason In this era of knowledge economy in which knowledge have become the most precious resource, surveys have shown that e-Learning has been on the increasing trend in various organizations including, among others, education and corporate. The use of e-Learning is not only aim to acquire knowledge but also to maintain competitiveness and advantages for individuals or organizations. However, the early promise of e-Learning has yet to be fully realized, as it has been no more than a handout being published online, coupled with simple multiple-choice quizzes. The emerging of e-Learning 2.0 that is empowered by Web 2.0 technology still hardly overcome common problem such as information overload and poor content aggregation in a highly increasing number of learning objects in an e-Learning Management System (LMS) environment. The aim of this research study is to exploit the Semantic Web (SW) and Knowledge Management (KM) technology; the two emerging and promising technology to enhance the existing LMS. The proposed system is named as Semantic Web Aware-Knowledge Management Driven e-Learning System (SWA-KMDLS). An Ontology approach that is the backbone of SW and KM is introduced for managing knowledge especially from learning object and developing automated question answering system (Aquas) with expert locator in SWA-KMDLS. The METHONTOLOGY methodology is selected to develop the Ontology in this research work. The potential of SW and KM technology is identified in this research finding which will benefit e-Learning developer to develop e-Learning system especially with social constructivist pedagogical approach from the point of view of KM framework and SW environment. The (semi-) automatic ontological knowledge base construction system (SAOKBCS) has contributed to knowledge extraction from learning object semiautomatically whilst the Aquas with expert locator has facilitated knowledge retrieval that encourages knowledge sharing in e-Learning environment. The experiment conducted has shown that the SAOKBCS can extract concept that is the main component of Ontology from text learning object with precision of 86.67%, thus saving the expert time and effort to build Ontology manually. Additionally the experiment on Aquas has shown that more than 80% of users are satisfied with answers provided by the system. The expert locator framework can also improve the performance of Aquas in the future usage. Keywords: semantic web aware – knowledge e-Learning Management System (SWAKMDLS), semi-automatic ontological knowledge base construction system (SAOKBCS), automated question answering system (Aquas), Ontology, expert locator. 2009-03 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/2889/1/AhmadMukhlason_Thesis_Final_Thesis_MSc_IT_2009.pdf Mukhlason, Ahmad Mukhlason (2009) SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology. Masters thesis, UNIVERSITI TEKNOLOGI PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
description In this era of knowledge economy in which knowledge have become the most precious resource, surveys have shown that e-Learning has been on the increasing trend in various organizations including, among others, education and corporate. The use of e-Learning is not only aim to acquire knowledge but also to maintain competitiveness and advantages for individuals or organizations. However, the early promise of e-Learning has yet to be fully realized, as it has been no more than a handout being published online, coupled with simple multiple-choice quizzes. The emerging of e-Learning 2.0 that is empowered by Web 2.0 technology still hardly overcome common problem such as information overload and poor content aggregation in a highly increasing number of learning objects in an e-Learning Management System (LMS) environment. The aim of this research study is to exploit the Semantic Web (SW) and Knowledge Management (KM) technology; the two emerging and promising technology to enhance the existing LMS. The proposed system is named as Semantic Web Aware-Knowledge Management Driven e-Learning System (SWA-KMDLS). An Ontology approach that is the backbone of SW and KM is introduced for managing knowledge especially from learning object and developing automated question answering system (Aquas) with expert locator in SWA-KMDLS. The METHONTOLOGY methodology is selected to develop the Ontology in this research work. The potential of SW and KM technology is identified in this research finding which will benefit e-Learning developer to develop e-Learning system especially with social constructivist pedagogical approach from the point of view of KM framework and SW environment. The (semi-) automatic ontological knowledge base construction system (SAOKBCS) has contributed to knowledge extraction from learning object semiautomatically whilst the Aquas with expert locator has facilitated knowledge retrieval that encourages knowledge sharing in e-Learning environment. The experiment conducted has shown that the SAOKBCS can extract concept that is the main component of Ontology from text learning object with precision of 86.67%, thus saving the expert time and effort to build Ontology manually. Additionally the experiment on Aquas has shown that more than 80% of users are satisfied with answers provided by the system. The expert locator framework can also improve the performance of Aquas in the future usage. Keywords: semantic web aware – knowledge e-Learning Management System (SWAKMDLS), semi-automatic ontological knowledge base construction system (SAOKBCS), automated question answering system (Aquas), Ontology, expert locator.
format Thesis
author Mukhlason, Ahmad Mukhlason
spellingShingle Mukhlason, Ahmad Mukhlason
SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
author_facet Mukhlason, Ahmad Mukhlason
author_sort Mukhlason, Ahmad Mukhlason
title SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
title_short SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
title_full SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
title_fullStr SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
title_full_unstemmed SWA-KMDLS: An Enhanced e-Learning Management System Using Semantic Web and Knowledge Management Technology
title_sort swa-kmdls: an enhanced e-learning management system using semantic web and knowledge management technology
publishDate 2009
url http://utpedia.utp.edu.my/2889/1/AhmadMukhlason_Thesis_Final_Thesis_MSc_IT_2009.pdf
http://utpedia.utp.edu.my/2889/
_version_ 1739830972081242112
score 13.211869

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