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Adaptive web accessibility metrics

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Adaptive web accessibility metrics

  1. 1. Adaptive Web Accessibility Metrics Markel Vigo1 and Giorgio Brajnik2 1 Laboratory of Human Mobility 2 University of Udine and TechnologyBCS HCI Workshop: The socio‐technological issues of adaptive interfaces and user profiling for accessibility September 6, Dundee (Scotland)
  2. 2. 1. Motivation for Adaptive Accessibility Metrics • We’d like to know the answer to this question: “To what extent is accessible a web page… - for a determined user with their own abilities - using a determined Assistive Technology and user agent - operating a specific device - and carrying out a determined task” • …equals to measuring accessibility in use or contextual accessibility • There are some scenarios that could benefit - As a way to measure interface adaptations - Adaptive hypermedia techniques - Accessibility observatories and QA • Traditional web accessibility metrics aim at measuring accessibility wrt to conformanceAdaptive Web Accessibility Metrics Vigo &Brajnik, 2010
  3. 3. 1. Motivation for Adaptive Accessibility Metrics • Why adaptive accessibility scores? - Do conformance scores capture the accessibility perceived by users? - Traditional metrics are based on general purpose guidelines - Assuming metrics are adequate and valid many error-rates are introduced - Trusting in guidelines is risky - Guidelines do not capture all users’ needs and interaction context• We need accessibility scores that capture the interaction context • Metrics are tied to evaluation process • Adaptive evaluation would produce user-tailored scores • Better if scores are automatically obtainedAdaptive Web Accessibility Metrics Vigo &Brajnik, 2010
  4. 4. 2. Challenges and Engineering solutionsChallenge 1: how to capture interaction context data (non intrusively) • Select only those guidelines that impact on a determined user group • Not enough • Context is key for adaptive evaluations •Detecting installed Assistive Technology and user agents is a step forward • Evaluation tools need a user profile as an inputAdaptive Web Accessibility Metrics Vigo &Brajnik, 2010
  5. 5. 2. Challenges and Engineering solutionsChallenge 2: quantify severity of violated accessibility barriers • Weight barriers for a specific user context • Application scenarios require real-time scores • How to quantify barriers automatically? • Make use of infrastructures such as Accessibility Commons • Accessibility metadata stored beforehand • Triples: <accessibility problem, context, severity>Adaptive Web Accessibility Metrics Vigo &Brajnik, 2010
  6. 6. 2. Challenges and Engineering solutionsChallenge 3: reasoning over guidelines • Not to tie the metric to a determined guideline set • No matter which guideline set is used the metric should adapt to it • Guidelines have to be specified in a common language so that evaluation tools can understand them interoperability • Metrics require parameters such as number of applied guidelines, severities, etc inference • Interoperability + inference = ontologies?Adaptive Web Accessibility Metrics Vigo &Brajnik, 2010
  7. 7. Adaptive Web Accessibility Metrics Markel Vigo1 and Giorgio Brajnik2 1 Laboratory of Human Mobility 2 University of Udine and TechnologyBCS HCI Workshop: The socio‐technological issues of adaptive interfaces and user profiling for accessibility September 6, Dundee (Scotland)

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