Toward linking dyslexia types and symptoms to the available assistive technologies

Conference paper


Alsobhi, A., Khan, N. and Rahanu, H. 2014. Toward linking dyslexia types and symptoms to the available assistive technologies. The 14th IEEE International Conference on Advanced Learning Technologies - ICALT2014. Athens, Greece 07 - 10 Jul 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 597-598 https://doi.org/10.1109/ICALT.2014.174
TypeConference paper
TitleToward linking dyslexia types and symptoms to the available assistive technologies
AuthorsAlsobhi, A., Khan, N. and Rahanu, H.
Abstract

As a result of the widespread, and accelerating, dissemination of digital technologies, there has been a profound effect on how people learn. These effects have been greatly debated over the years. While many educational developers have agree on the effects technologies have brought on educational performance, little attention has been made to the relationship between such technologies effects and individual differences such as individuals who suffer dyslexia. There are readily available Assistive Technologies1 that offer potential to help students with learning difficulties such as dyslexia. This paper will attempt to tease out these technologies and dyslexia types, hence attempt at providing a solution. The focus should not be on correlating one technology to one disability. Instead of identifying different pedagogical needs such as help with reading and writing. Then, trying to meet those needs by looking at the whole range of ways that available.

KeywordsDyslexia; E-learning; Assistive Technologies.
Research GroupAspects of Law and Ethics Related to Technology group
ConferenceThe 14th IEEE International Conference on Advanced Learning Technologies - ICALT2014
Page range597-598
ISSN2161-3761
ISBN
Hardcover9781479940387
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Publication dates
Print06 Jul 2014
Online27 Sep 2014
Publication process dates
Deposited16 Jul 2014
Output statusPublished
Accepted author manuscript
Copyright Statement

© 2014 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.

Digital Object Identifier (DOI)https://doi.org/10.1109/ICALT.2014.174
LanguageEnglish
Book title2014 IEEE 14th International Conference on Advanced Learning Technologies
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