Dyslexia adaptive e-learning system based on multi-layer architecture
Alsobhi, Aisha, Khan, Nawaz and Rahanu, Harjinder ORCID: https://orcid.org/0000-0002-3620-8036
(2015)
Dyslexia adaptive e-learning system based on multi-layer architecture.
Proceedings of the 2015 Science and Information Conference (SAI).
In: Science and Information Conference 2015, 28-30 Jul 2015, London, United Kingdom.
ISBN 9781479985470.
[Conference or Workshop Item]
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Abstract
The key shortcoming of traditional e-learning systems is that the learning they promote is not adaptive. This paper analyses the e-learning activity of individuals with dyslexia and proposes an innovative design for an e-learning system. This new system is user-centric and interactive based on information about the user’s learning preferences. The proposed system design employs a multi-layer architecture, including a presentation layer, an adaption layer, a learning management system layer, an application server layer and a database layer. The learning management system layer contains all the possible systems that provide resources to support the learning process, hence improving the system’s reusability. The adaption layer provides the system’s adaptive technique functionality, which makes it more intelligent and adaptive – the main objective of this research.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords (uncontrolled): | e-learning; Adaptive; Dyslexia; multi-layer |
Research Areas: | A. > School of Science and Technology > Computer Science |
Item ID: | 15468 |
Notes on copyright: | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
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Depositing User: | Aisha Alsobhi |
Date Deposited: | 28 Apr 2015 14:10 |
Last Modified: | 29 Nov 2022 22:35 |
URI: | https://eprints.mdx.ac.uk/id/eprint/15468 |
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