WABS : Web Accessibility Barrier Severity Metric
Web accessibility aims at providing disabled users with a barrier-free user experience so they can use and contribute to the Web more effectively. However, not all websites comply with the Web Content Accessibility Guidelines (WCAG 2.0) due to challenges facing Web developers during the website'...
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my-usim-ddms-13003 |
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uketd_dc |
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Universiti Sains Islam Malaysia |
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USIM Institutional Repository |
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en_US |
| topic |
Accessible Web sites, people with disabilities Computers Human-computer interaction |
| spellingShingle |
Accessible Web sites, people with disabilities Computers Human-computer interaction Hayfa Yousef Musallam Abu-Addous WABS : Web Accessibility Barrier Severity Metric |
| description |
Web accessibility aims at providing disabled users with a barrier-free user experience so they can use and contribute to the Web more effectively. However, not all websites comply with the Web Content Accessibility Guidelines (WCAG 2.0) due to challenges facing Web developers during the website's design and development. These challenges which lead to incorrect ways of coding produce barriers for assistive technologies. Thus, assistive technologies such as screen readers would not be able to interpret the presented contents on the monitor which will contribute to making websites inaccessible to disabled users. Therefore, these websites can suffer from barriers that make accessing their contents difficult for disabled people. The purpose of this work is to develop a Web Accessibility Barrier Severity (WABS) metric that adheres to WCAG 2.0 standards, and assign measurable weight to each identified barrier. The proposed metric will help Web evaluators to disclose the most prevalent and frequent accessibility barriers that violate WCAG 2.0, and then rank them based on their severities and impacts on the accessibility level. Once the barriers are ranked, 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. Four experiments were conducted to check the metric quality in terms of validity, reliability and sensitivity. The first experiment was carried out to test the metric validity by checking if the metric values have discriminating power and whether the barrier frequency has a positive correlation with its weight. The theoretical validation confirms that WABS metric adheres to the requirements and assumptions of building a good metric suggested by eminent researchers, whereas the empirical validation of the metric shows that WABS values have large discriminating power and all the results are positive, finite and normalized with continuous range of values fell within the range (0-1) as intended by the specifications. Moreover, Spearman rank-order correlation shows a significant positive relationship between barriers' frequency and weights with rs(15) = .96 and p < .001. The remaining experiments were conducted under different contexts (time span, tools and samples) to examine metric reliability and sensitivity. WABS metric shows reliability, because all the measurements are reproducible and consistent when calculated by different evaluators under similar circumstances. The conducted experiments have demonstrated that the metric is robust enough since it is not too sensitive or over reacting to small changes in websites contents when the experiments are conducted in different contexts. Following, the accessibility level for a dataset of websites that contain different types of barriers was measured. Then, WABS metric measured the severity of each barrier type found in the evaluated dataset and ranked them accordingly. After that, the top five severe types of barriers as identified by the metric were removed from the dataset, and then the accessibility level for the evaluated dataset was measured again. Paired samples t-test elicited statistically significant improvement of accessibility level after removing the five barriers (t = 8.467, p = 0.001 < 0.05 =a). This doctoral research contributes to web accessibility area by developing a good quality web accessibility metric that identifies severe barriers in which fixing them will increase the accessibility level of websites significantly. Moreover, this work provides some practical recommendations and solutions to overcome accessibility challenges, such as: the need to issue enforcement legislations regarding web accessibility rather than depending on voluntary guidelines. |
| format |
Thesis |
| author |
Hayfa Yousef Musallam Abu-Addous |
| author_facet |
Hayfa Yousef Musallam Abu-Addous |
| author_sort |
Hayfa Yousef Musallam Abu-Addous |
| title |
WABS : Web Accessibility Barrier Severity Metric |
| title_short |
WABS : Web Accessibility Barrier Severity Metric |
| title_full |
WABS : Web Accessibility Barrier Severity Metric |
| title_fullStr |
WABS : Web Accessibility Barrier Severity Metric |
| title_full_unstemmed |
WABS : Web Accessibility Barrier Severity Metric |
| title_sort |
wabs : web accessibility barrier severity metric |
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Universiti Sains Islam Malaysia |
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my-usim-ddms-130032024-05-29T18:21:41Z WABS : Web Accessibility Barrier Severity Metric Hayfa Yousef Musallam Abu-Addous Web accessibility aims at providing disabled users with a barrier-free user experience so they can use and contribute to the Web more effectively. However, not all websites comply with the Web Content Accessibility Guidelines (WCAG 2.0) due to challenges facing Web developers during the website's design and development. These challenges which lead to incorrect ways of coding produce barriers for assistive technologies. Thus, assistive technologies such as screen readers would not be able to interpret the presented contents on the monitor which will contribute to making websites inaccessible to disabled users. Therefore, these websites can suffer from barriers that make accessing their contents difficult for disabled people. The purpose of this work is to develop a Web Accessibility Barrier Severity (WABS) metric that adheres to WCAG 2.0 standards, and assign measurable weight to each identified barrier. The proposed metric will help Web evaluators to disclose the most prevalent and frequent accessibility barriers that violate WCAG 2.0, and then rank them based on their severities and impacts on the accessibility level. Once the barriers are ranked, 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. Four experiments were conducted to check the metric quality in terms of validity, reliability and sensitivity. The first experiment was carried out to test the metric validity by checking if the metric values have discriminating power and whether the barrier frequency has a positive correlation with its weight. The theoretical validation confirms that WABS metric adheres to the requirements and assumptions of building a good metric suggested by eminent researchers, whereas the empirical validation of the metric shows that WABS values have large discriminating power and all the results are positive, finite and normalized with continuous range of values fell within the range (0-1) as intended by the specifications. Moreover, Spearman rank-order correlation shows a significant positive relationship between barriers' frequency and weights with rs(15) = .96 and p < .001. The remaining experiments were conducted under different contexts (time span, tools and samples) to examine metric reliability and sensitivity. WABS metric shows reliability, because all the measurements are reproducible and consistent when calculated by different evaluators under similar circumstances. The conducted experiments have demonstrated that the metric is robust enough since it is not too sensitive or over reacting to small changes in websites contents when the experiments are conducted in different contexts. Following, the accessibility level for a dataset of websites that contain different types of barriers was measured. Then, WABS metric measured the severity of each barrier type found in the evaluated dataset and ranked them accordingly. After that, the top five severe types of barriers as identified by the metric were removed from the dataset, and then the accessibility level for the evaluated dataset was measured again. Paired samples t-test elicited statistically significant improvement of accessibility level after removing the five barriers (t = 8.467, p = 0.001 < 0.05 =a). This doctoral research contributes to web accessibility area by developing a good quality web accessibility metric that identifies severe barriers in which fixing them will increase the accessibility level of websites significantly. Moreover, this work provides some practical recommendations and solutions to overcome accessibility challenges, such as: the need to issue enforcement legislations regarding web accessibility rather than depending on voluntary guidelines. 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