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Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments

Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments
Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments
The aim of this thesis is to investigate how to automatically evaluate the mobile web accessibility of Higher Education (HE) electronic texts for those with print impairments. The outcome is a master key component referred to as accessibility metadata. This unlocks hidden information that can be presented in human readable form and provides a means to automatically assess the accessibility support offered by mobile device settings, mobile browsers, ereader applications and downloadable formats. This process involves an academic or student searching for, finding, downloading, navigating and reading an electronic text while using a Higher Education Institute (HEI) library web portal on a mobile device. Two research questions are addressed using expert reviews. RQ1: determines four physical and sensory control categories, namely: visual, audio, touch and speech that support automatic evaluation. This also incorporates issues arising for those with dyslexia a form of cognitive impairment. The control categories analysed against user tasks, specific to searching for, finding, downloading, navigating and reading HE electronic texts provides the basis to answer RQ2. The latter investigates how automatic evaluation is achieved through the production of an instrument that provides Barrier Walkthrough (BW) success criteria. This criteria enables a specification to be written for a mobile web accessibility evaluation tool that is incorporated into a wireframe for four mobile web applications and a web service. In the future, the framework can be repurposed to other sectors, from pre‐school tablet content to the use of adaptive mobile technologies by older adults who may experience age‐related disabilities.
Rogers, Neil, Edward
3a256977-94b6-4f5d-8911-3210fc360ffe
Rogers, Neil, Edward
3a256977-94b6-4f5d-8911-3210fc360ffe
Wald, Michael
90577cfd-35ae-4e4a-9422-5acffecd89d5

Rogers, Neil, Edward (2019) Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments. University of Southampton, Doctoral Thesis, 670pp.

Record type: Thesis (Doctoral)

Abstract

The aim of this thesis is to investigate how to automatically evaluate the mobile web accessibility of Higher Education (HE) electronic texts for those with print impairments. The outcome is a master key component referred to as accessibility metadata. This unlocks hidden information that can be presented in human readable form and provides a means to automatically assess the accessibility support offered by mobile device settings, mobile browsers, ereader applications and downloadable formats. This process involves an academic or student searching for, finding, downloading, navigating and reading an electronic text while using a Higher Education Institute (HEI) library web portal on a mobile device. Two research questions are addressed using expert reviews. RQ1: determines four physical and sensory control categories, namely: visual, audio, touch and speech that support automatic evaluation. This also incorporates issues arising for those with dyslexia a form of cognitive impairment. The control categories analysed against user tasks, specific to searching for, finding, downloading, navigating and reading HE electronic texts provides the basis to answer RQ2. The latter investigates how automatic evaluation is achieved through the production of an instrument that provides Barrier Walkthrough (BW) success criteria. This criteria enables a specification to be written for a mobile web accessibility evaluation tool that is incorporated into a wireframe for four mobile web applications and a web service. In the future, the framework can be repurposed to other sectors, from pre‐school tablet content to the use of adaptive mobile technologies by older adults who may experience age‐related disabilities.

Text
NRogers_PhDThesis_Sept2019 - Version of Record
Restricted to Repository staff only until 31 January 2022.
Available under License University of Southampton Thesis Licence.

More information

Published date: September 2019

Identifiers

Local EPrints ID: 445205
URI: http://eprints.soton.ac.uk/id/eprint/445205
PURE UUID: ad571ea8-cc17-455c-a112-45a72db052b3
ORCID for Neil, Edward Rogers: ORCID iD orcid.org/0000-0001-6159-9342

Catalogue record

Date deposited: 25 Nov 2020 17:31
Last modified: 25 Nov 2020 17:33

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Contributors

Author: Neil, Edward Rogers ORCID iD
Thesis advisor: Michael Wald

University divisions

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