Quantitative Metric for Ranking Web Accessibility Barriers Based on Their Severity

Authors

  • Hayfa Yousef Abuaddous Faculty of Science & Technology Universiti Sains Islam Malaysia, Malaysia
  • Mohd Zalisham Jali Faculty of Science & Technology Universiti Sains Islam Malaysia, Malaysia
  • Nurlida Basir Faculty of Science & Technology Universiti Sains Islam Malaysia, Malaysia

DOI:

https://doi.org/10.32890/jict2017.16.1.5

Keywords:

Web accessibility barrier, WCAG 2.0, WABS metric, automated tools, A-Checker, disabled users

Abstract

Web accessibility aims at providing disabled users with a barrierfree user experience so they can use and contribute. However, not all websites comply with WCAG 2.0 which results in Web accessibility barriers in websites. Thus, assistive technologies such as screen readers would not be able to interpret the presented contents on the monitor due to these barriers and this will contribute to making websites inaccessible to disabled users. This paper proposed an innovative metric that assigns measurable weight to each identified barrier based on its severity and impacts on the accessibility level, and then ranks the barriers accordingly. Following, Web developers can fix the highly ranked severe barriers instead of wasting time in studying and fixing less severe types of barriers that may rarely occur. An experiment was conducted to check the metric validity. We found the metric was valid and thereby we suggested the usage of the metric as a valid scientific measurement.

 

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Published

31-05-2017

Issue

Vol. 16 No. 1 (2017): Journal of Information and Communication Technology (JICT) Vol.16, No.1, June 2017

Section

Articles

How to Cite

Abuaddous, H. Y., Jali, M. Z., & Basir, N. (2017). Quantitative Metric for Ranking Web Accessibility Barriers Based on Their Severity. Journal of Information and Communication Technology, 16(1), 81-102. https://doi.org/10.32890/jict2017.16.1.5

Research impact

Harvested 2026-09-06
6 citations, from OpenAlex — the highest of the sources checked

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Identifiers DOI 10.32890/jict2017.16.1.5 OpenAlex W4241118071