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Open corpus architecture for personalised ubiquitous e-learning

Muntean, Cristina Hava and Muntean, Gabriel-Miro (2009) Open corpus architecture for personalised ubiquitous e-learning. Personal and Ubiquitous Computing, 13 (3). pp. 197-205. ISSN 1617-4917

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Abstract

As the e-learning area matures, there are a growing number of e-learning content providers that produce and distribute material that covers a large range of topics, differs in quality and is represented in various formats. Lately, different devices and various network technologies allow extensive user access to educational content almost anywhere, anytime and from any device. Ubiquitous e-learning has the potential to provide continuous and context-based, educational material to human learners anytime, anywhere and on any device. Since each person has different expectations related to the content, the performance of the delivery and display of that content, it is desirable for an ubiquitous e-learning environment to provide user-oriented personalisation of e-learning material. However very often there are multiple sources of e-learning material at various web locations (open corpus resources) that cover the same topic, but differ in terms of quality, formatting and even cost. It is very difficult for learners to select the content that best suits their interests and goals, characteristics of the device used and delivery network as well as their cost budget. This paper proposes an innovative ubiquitous e-learning environment called Performance-based E-learning Adaptive Cost-efficient Open Corpus frameworK (PEACOCK) that provides support for the selection and distribution of personalised e-learning rich media content (e.g. multimedia, pictures, graphics and text) to e-learners such as it will best suit users’ interests and goals, meet their formatting preferences and cost constraints, while considering the limitations introduced by the end-user devices and the delivery networks to the user. PEACOCK’s main goal is to maximise the users’ e-learning experience and increase their learning satisfaction and learning outcome.

Item Type: Article
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Staff Research and Publications
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 17 May 2014 11:15
Last Modified: 17 May 2014 11:15
URI: http://trap.ncirl.ie/id/eprint/1253

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