Web accessibility aims at providing people with disabilities with a barrier-free user experience. This PhD report explores how automatic accessibility assessment benefits both accessibility experts and end-users. In the context of this document assessment is understood as a twofold goal consisting of evaluation and measurement. The former group, accessibility experts, can make use of a set of tools and flexible frameworks to create and maintain accessible content for a wide range of users and interaction environments. In addition, the techniques and methods used throughout this document can be replicated and incorporated by third parties. Expert assessment of fourteen websites and large- scale automatic assessment of almost 1,500 web pages demonstrates that the Web Accessibility Quantitative Metric (WAQM) is a valid and reliable metric to automatically measure accessibility of web pages. Moreover, by deploying WAQM jointly with commercial search engines (Google and Yahoo!) it is corroborated that search engine crawlers consider web accessibility while indexing the Web although pages are not ranked according to their accessibility score. The latter group, end-users, can take advantage from contextual accessibility assessment by deploying assessment scores in web pages to increase user orientation. To do so from a guidelines conformance point of view, not only content accessibility has to be considered but also the dependencies between content guidelines, user group, assistive technology and the access device. Twenty users took part in a user test conducted for determining the validity of this approach with the mobile web, concluding that device-tailored assessment is more faithful to usability assessment in terms of satisfaction and task completion time. Another experiment with sixteen blind users also demonstrates that deploying user-tailored scores increases user orientation and confidence. It is also observed that when links are annotated with the accessibility score of the page they point to, blind users change the browsing paradigm from sequential navigation to random criteria within those links that score higher. Finally it is noteworthy that lessons drawn from automatic assessment can be extrapolated to manual assessment carried out by experts or user-testing.

Full Thesis:
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Thesis Advisor:
Julio Abascal

Award Date:
November 1, 2009

University of the Basque Country
San Sebastián, Spain

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