Continuous Ranking of Estonian Public Sector Web Sites With Respect to WCAG 2.0 Guidelines
Name
Jaan Susi
Abstract
Accessibility of public sector Web sites has been recently recognized as one of the objectives of governments of EU member states and countries
elsewhere. In order to measure in which extent the accessibility has been achieved, WCAG 2.0 guidelines have been adopted as a benchmark measure.
Although conformance to the guidelines has been partially automated, there is still a lot of human effort and subjectivity involved in the evaluation process. Furthermore, due to human involvement, evaluation is mostly narrowed down to a limited set of Web pages of a domain under evaluation. This study aims to make another step toward evaluation automation by 1) reverse-engineering strategies of humans evaluators and 2) analyzing whether higher number of evaluated Web pages will have positive effect to the final ranking. The experimental results show that human ranking is closer to semi-permissive and restrictive evaluation strategies. Furthermore, we show that higher number of evaluated pages will not have positive impact on the evalution precision wrt human rankings.
elsewhere. In order to measure in which extent the accessibility has been achieved, WCAG 2.0 guidelines have been adopted as a benchmark measure.
Although conformance to the guidelines has been partially automated, there is still a lot of human effort and subjectivity involved in the evaluation process. Furthermore, due to human involvement, evaluation is mostly narrowed down to a limited set of Web pages of a domain under evaluation. This study aims to make another step toward evaluation automation by 1) reverse-engineering strategies of humans evaluators and 2) analyzing whether higher number of evaluated Web pages will have positive effect to the final ranking. The experimental results show that human ranking is closer to semi-permissive and restrictive evaluation strategies. Furthermore, we show that higher number of evaluated pages will not have positive impact on the evalution precision wrt human rankings.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Peep Küngas
Defence year
2016