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Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites
Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
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Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites Abid Ismail, K.S. Kuppusamy ⇑ Department of Computer Science, School of Engineering and Technology, Pondicherry University, Pondicherry 605014, India
a r t i c l e
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Article history: Received 22 November 2018 Revised 29 March 2019 Accepted 29 March 2019 Available online xxxx Keywords: Web accessibility WCAG College websites Accessibility evaluation tools Test of normality Success criteria
a b s t r a c t The World Wide Web Consortium (W3C) has provided the most important set of guidelines for web accessibility which is popularly known as Web Content Accessibility Guidelines (WCAG). The accessibility analysis of higher education websites becomes paramount important to make them inclusive considering the growing number of enrollments of persons with disabilities (PwDs) in higher education, in countries such as India. This paper presents the accessibility analysis of higher education websites with the case study of college websites (N ¼ 44) affiliated with the University of Kashmir and Cluster University Srinagar. The study has been carried out with two major accessibility evaluation tools called web accessibility test, denoted as TAW and the accessibility engine powering browser extensions called the accessibility engine, denoted as aXe. This paper lists the major accessibility barriers exposed by these sites in terms of metrics such as a number of problems, warnings and a status of success criteria violations. With respect to TAW tool, a number of problems observed were 2646, a large number of warnings to the scale of 15995 and the not reviewed items were 1356. With aXe tool, the total violations observed were 1951 and items needing review were 1733. Findings of the statistical analysis are also presented in this paper. This paper presents a roadmap of steps for making these websites inclusive and barrier-free for PwDs. Ó 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction The modern age is the age of information technology especially the age of the Internet. So there is a need for accessing resources rendered via Internet platform, in many dimensions of day-today life such as e-commerce, educational resources, banking, travel and tourism. PwDs are no exception to this phenomenon. Indeed, the rendering of resources via Internet makes the life of PwDs simpler provided that the platform satisfies the accessibility criteria. The vice versa is also true that if the web-sites through which these services are rendered are not accessible then the PwDs face great number of barriers in interacting and utilizing these resources.
⇑ Corresponding author. E-mail address: [email protected] (K.S. Kuppusamy). Peer review under responsibility of King Saud University.
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Higher education is an important component in making the PwDs skillful and making them self-reliant in terms of financial and other requirements. Hence, it becomes important for making the higher education sites completely accessible or at-least minimize the barriers to the maximum possible extent. In countries such as India, with large number of youth population and proportionate number of persons with disabilities in that age spectrum, it gains increased significance to make the higher education website pose as minimal friction as possible, if not nothing. As per census 2011 in India 1, the disabled population by type of major activities is presented in Table 1. The Government of India’s pioneering initiatives such as Accessible India and Digital India have accelerated the work happening in this sector. In the digital ecosystem of India, it becomes foremost important to provide the web accessibility report of websites for the support and enhancement of these Digital India and Accessible India Campaign or Sugamya Bharat Abhiyan2 initiatives. For this, we considered 1 Available at:https://unstats.un.org/unsd/demographic-social/meetings/2016/ bangkok-disability-measurement-and-statistics/Session-6/India.pdf. 2 Available at:http://accessibleindia.gov.in/content/.
https://doi.org/10.1016/j.jksuci.2019.03.011 1319-1578/Ó 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Table 1 Disabled Non-Workers Population (in Millions) by type of Major Activities, India as per Census 2011. Type of Disability
Total (Millions)
Total disabled non-worker In seeing In hearing In speech In movement Mental abnormality Mental Illness Any other Multiple disability
Major Non-Economic Activity (Percentage) Student
Household duties
Dependent
Pensioner
Others
27.2 28 32.5 37.2 19.7 24.5 9.3 37.4 15
15.3 17.3 18.9 20 13.4 9.6 11.9 17.7 7.3
45.7 42.7 38.7 33.5 49.8 57.7 66.6 35.4 65.9
5.5 6.7 4.9 3.4 8.8 2.1 2.8 3.2 6.8
5.6 4.7 4.6 5.4 7.4 5.4 8.2 5.8 4.3
17.1 3.1 3 1.2 3.4 1.2 0.6 2.9 1.7
Source: C-Series, Table C-24, Census of India 2011.
the specific part of websites called higher educational websites of India for the evaluation process. In 2016, an exploratory study was performed based on web accessibility of 302 Indian universities homepages (Ismail and Kuppusamy, 2018b). Now, we planned to do a zone-wise evaluation of college websites affiliated with universities of the entire nation. So, this paper aims towards measuring the accessibility barriers posed by higher education websites with the case study of 44 colleges affiliated to University of Kashmir 3 and Cluster University Srinagar 4 of the state Jammu and Kashmir (Division Kashmir Province) in northern India. For making these web resources accessible, standard guidelines were framed and constantly getting updated by World Wide Web Consortium (W3C). These guidelines should be followed strictly by the developers of websites and resources for making them universally accessible. According to Tim Berners-Lee 5, the Web accessibility is the degree to which the Internet and its tasks are put at the distribution of all types of users whatever their requirements, locations, languages, physical and mental aptitudes, etc. This concept was also referenced by researchers (Bravo, 2005) in their work on web accessibility field. With the increasing emphasis on universal design principles, it becomes mandatory to maintain a level-playing field for all categories of users, irrespective of their age or physical/mental disabilities. So, accessibility is a concept arises to make the web resources accessible for all kinds of people. Making the navigation, browsing and interaction etc. of web resources easy for everyone is the main aim of web accessibility. When the website follows the guidelines which are framed by W3C or some country-based specific guidelines relevant to WCAG, then the site is universally accessible. If there is some mismatch then accessibility issue arises which increases the barrier in accessing these resources. If the web accessibility guidelines are not followed strictly, there would be large number of people who will be excluded from the benefits of web based electronic services. Therefore, this study focuses on Universal accessibility issues on the web pages in their current state. To measure the level of conformance, many accessibility analysis tools have been developed for assessment of websites. For this study, we have used two accessibility evaluation tools TAW and aXe for checking accessibility status of colleges affiliated with the universities under different parameters. Therefore, following research objectives are to be proposed for this web accessibility assessment with a case study of colleges, affiliated with University of Kashmir and Cluster University Srinagar:
3 4 5
Available at:http://www.kashmiruniversity.net/. Available at:http://www.cusrinagar.edu.in/. Available at:https://www.w3.org/standards/webdesign/accessibility.
1. To find the web accessibility issues of web pages in terms of WCAG principles; 2. To extract the problems, warnings and not reviewed guidelines of web pages in terms of WCAG guidelines; 3. To find the success criteria estimation of web pages; 4. To identify the major violation of guidelines among the sites; 5. To provide proper suggestions for increasing the accessibility of these web pages. The other sections of this paper are organized as follows. Section 2 presents the relevant literature review based on assessment of web accessibility regarding with different types of websites used for evaluation process. In Section 3, we have explored web accessibility concepts and standards, and the characteristics of the tools which are used for evaluation process to check accessibility status of higher education websites. The work based on the analysis tools used in our study and their corresponding statistical inferences are presented in Section 4. The estimation of guideline violations among college websites with respect to their number, mean and standard deviation are presented in Section 4.4. The Section 5 involves two major subsections namely discussions about results and the suggestions regarding improvements. Therefore, the Section 5.1 presents the discussion about the result obtained and the Section 5.2 presents suggestions for minimizing the accessibility issues of these websites and provide alternative feedback for their accessibility enhancement. It also provides some important steps to enhance the web accessibility and usability of websites. Finally, the Section 6 presents the conclusion of our study that benefits the college website developers and designers for achieving the universality of the web for all without any hindrances when implemented. 2. Review of literature Making the Web more accessible for (PwDs), governments around the world have been setting up legislations and laws. For achieving the web accessibility successfully, more than 19 countries have established their own policies, laws, and legislations as per World Wide Web Consortium website laws and policies 6. This section presents some of the related research studies published by researchers throughout the world with respect to web accessibility and usability issues of the web regarding with PwDs. One of the clear reasons for using the Internet by the PwDs was found to access government websites and official services were studied in 2007 by the UK Office for Disability Studies (Kuzma et al., 2009). Also, an exploratory study was carried out (Al-Khalifa, 2012) on the accessibility of Saudi Arabia government websites and presented some recommendations for improving web accessibility along with future implications. 6
Available at:https://www.w3.org/WAI/Policy/. Accessed July 18, 2017.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
There is a lot of research carried out on higher education institutions in terms of web accessibility assessments. Like, an exploratory study was carried out by researchers (Ismail and Kuppusamy, 2018b) on accessibility analysis of Indian Universities homepages by using different web accessibility evaluation tools and classify them into three categories based on accessibility score. Also, an automated assessment tool called SortSite testing tool was used for analyzing 20 public Turkish universities to find the accessibility issues (Yerlikaya and Durdu, 2017). It was found that no single university fully satisfy the WCAG 2.0 accessibility criteria. Similarly, researchers (Akgül, 2017) carried out the accessibility evaluation of 23 Turkish universities homepage and identified the most violated WCAG 1.0 guidelines by the developers of university websites in Turkey. A study on web accessibility in Turkey has been carried out by researchers like (Inal et al., 2017). It was inferred that the user experience professionals in Turkey need to be improved in terms of web accessibility awarenesses, education, and training of web accessibility so that the accessibility for all will be enhanced. Another, accessibility study of Turkish universities homepage by using automatic evaluation tools was performed by researchers (Kurt, 2011). It was found that all university homepages showed some accessibility violations and warnings. Also, several suggestions are provided to enhance the web accessibility of websites (Kurt, 2017). Researchers like (Ismail et al., 2017a,b; Ahmi and Mohamad, 2015; Anderson, 2004; Harper and DeWaters, 2008; Ojha et al., 2018; Ismail and Kuppusamy, 2019; Ismail and Kuppusamy, 2018a) used online automatic tools like AChecker, WAVE, Bobby, SortSite, Cynthia Says, Hera, etc. for evaluation of websites in terms of WCAG 1.0 and WCAG 2.0 guidelines to find violations and warnings. Accordingly, they provide the feedback to developers and designers to enhance the web accessibility and readability of websites so that the PwDs can access the web resources easily, means to make the sites universally accessible. Also, a study was carried out by researchers (Ismail and Kuppusamy, 2016) to find accessibility analysis of North East India region websites by using online automatic evaluation tools like AChecker and WAVE. By analyzing the existing literature like (Fernandes et al., 2012; Gonçalves et al., 2013; Lee et al., 2013; Martins et al., 2015), we inferred that the statistical representation mainly gathered in tables and charts, whatever the statistical indicator used to analyze and interpret the evaluations results is not only to understand the overall results; but also to easily and quickly to perceive the target group tendency towards being or not web accessible grievances or criticism. Researchers like (Menzi-Çetin et al., 2017) carried out the research on usability of websites for visually impaired students. They involved six visually impaired students for evaluation processes of university websites in terms of usability. It was found that there is lack of basic accessibility components and need for their implementation like search engines, text versions, sequences of links with tabs and much more accessible features. Moreover, the researchers (Velleman et al., 2017) have identified the five categories of factors, which are adoption, external, personal and the factors related to web design process and organization structure. Later, they explained the adoption and implementation processes within e-government systems and organizations for web accessibility guidelines and standards. Similarly, researchers such as (Juárez-Ramírez, 2017; Ismailova and Kimsanova, 2017, Barroso et al., 2017; Ismailova and Inal, 2017; Al-Khalifa et al., 2017; Barricelli et al., 2017; Gonçalves et al., 2018; Kuppusamy and Aghila, 2017; Karaim and Inal, 2017; Kuppusamy, 2018; Liu et al., 2017; Goette et al., 2006) have analyzed web pages or websites, and also gave a lot of contributions in the field based on accessibility and usability of websites, in order to make the web accessible and usable for all. For produc-
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ing a quality website, a central criterion called validity evaluation is important to the success of accessibility efforts 7 and as such, it is a valuable step in accomplishing accessibility goals 8. Therefore, based on inferences from a review of the literature, it is important to investigate and identify the issues regarding with web accessibility of higher education institutions. In this paper, we are considering the case study of college websites affiliated with two Indian universities. 3. Web accessibility Making web pages easier to navigate and read, for every single user visiting the site, irrespective of the disabilities that they are experiencing, is the main goal of web accessibility. That is, inclusive practices to remove the web access barriers. The needs that web accessibility aims to address include visual, motor, auditory, seizures and cognitive or intellectual disabilities. When the websites are correctly designed, developed and edited, then all types of users can get equal and barrier-free access to information and functionality. In 1999, the Web Accessibility Initiative (WAI), a project by World Wide Web Consortium (W3C) was framed for achieving this accessibility concept. WAI had published two versions of Web Content Accessibility Guidelines namely WCAG 1.0 in 1999 and its updated version WCAG 2.0 in 2012 based on guidelines, checkpoints, success criteria, 4 principles, 3 levels of priority, conformance, etc. In addition to this, another WCAG version of W3C called WCAG 2.1 is recommendation since June 20189. It covers a wide range of recommendations for making web content more accessible to maximize the future applicability of accessibility efforts. Moreover, WCAG 2.0 is still W3C recommendation and does not deprecated by WCAG 2.1. From a broader perspective, for a website to be considered accessible, a website must obey with existing regulations and guidelines like Section 508, Stanca Act, GIGW, WCAG, etc. The W3C’s official website10 has mentioned the detailed summary of what these guidelines (WCAG) mean, their comparison and why they are important for web accessibility. Based on WCAG, different accessibility evaluation tools have been developed for checking whether the web page or website is accessible or not. Therefore, TAW and aXe tools are used in this paper to investigate and identify the major issues of higher education websites, because of their some characteristics as presented in Section 3.1. Also, these two tools categorize the identified issues into different groups that provides easy way to help accessibility specialist and experts to solve them successfully. 3.1. Tools used In this accessibility study, we used the following accessibility evaluation tools to check the violations of guidelines in terms of the WCAG principles along with their detailed list of issues: 1. TAW- Test de Accessibilidad Web: It is based on both versions of WCAG 1.0 & WCAG 2.0, and its own set of heuristics or guidelines for mobile accessibility (mobileok beta version). The TAW 11 clearly marks the accessibility violations that it finds and provides the proposal on how to solve them. This tool is
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Available at:https://validator.w3.org/docs/help.html. Accessed June 25, 2017. Available at:https://www.w3.org/WAI/GL/2005/06/validity-accessibility.html. Accessed June 21, 2017. 9 Available at:https://www.w3.org/TR/WCAG21/. Accessed Jan 12, 2019. 10 Available at:https://www.w3.org/WAI/WCAG20/from10/comparison/. Accessed July 18, 2017. 11 Available at:http://www.tawdis.net/ingles.html?lang=en, Accessed March 14, 2017. 8
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
developed by the CTIC Centro Technologico de la Informacion y la Comuicacion and is freely available online, as a desktop application and as a Firefox add-on. 2. aXe-Easy accessibility testing tool: It is a free and open source testing tool, developed by Deque. The tool runs in your browser as an extension for Chrome as well as Firefox. The working analysis instructions of the tool as explained in the Deque Systems site 12. The aXe tool’s dashboard provides the list of issues and how many times the issues occur on the page. In addition to this, it also provides the detailed description of the issue, information about the severity of issues and which type of guidelines are being violated. Moreover, TAW and aXe written in this format indicates the representation of functionality of these two major accessibility evaluation tools called web(W) accessibility(A) test (T) or Test (T) Accessilibilidad (A) Web (W), denoted as TAW and the accessibility (a) engine (e) powering browser extensions (X) called the accessibility engine, denoted as aXe. 4. The case study This paper is based on a case study conducted with 44 college websites affiliated to University of Kashmir and Cluster University Srinagar. This study was conducted during the period from October 2016 to June 201713 The said list of forty-four ð44Þ colleges affiliated with University of Kashmir and Cluster University Srinagar are shown in Table 2 used for the web accessibility evaluation process. The websites of these 44 colleges are taken up to depth-one level only to evaluate them. So, 44 homepages of these websites are taken for evaluation process because of their popularity and most important and visiting page from the website. The descriptive report of these 44 college websites by using two different web accessibility evaluation tools namely TAW and aXe tool are in Table 3. The table also presents various parameters report with respect to their statistics and standard errors. For characterization of data which is obtained from TAW and aXe tool includes skewness and kurtosis 14. To measure symmetry or lack of symmetry of data, we use skewness. The distribution is symmetric if it looks the same to the left and right of the center point. The z-values of skewness and kurtosis which lies 1:96 to 1:96 is obtained using equation 1.
z-value ¼
statistic standard error
ð1Þ
Therefore, the z-value of skewness and kurtosis obtained from Table 3 statistic and standard error of college websites with respect to TAW and aXe tool report are as under: In case of TAW tool,
3:505 ¼ 9:818 0:357
ð2Þ
13:159 ¼ 18:745 0:702
ð3Þ
1:324 ¼ 3:709 0:357
ð4Þ
z valueofskewness ¼ z valueofkurtosis ¼ In case of aXe tool,
z valueofskewness ¼
12
Available at:https://www.deque.com/products/axe/. Accessed March 03, 2017. Available at:http://www.kashmiruniversity.net/Colleges.aspx. Accessed December 13, 2016. 14 Available at:http://www.itl.nist.gov/div898/handbook/eda/Section3/eda35b.htm, Accessed July 10, 2017. 13
Table 2 List of Colleges affiliated with University of Kashmir and Cluster University Srinagar. S.No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
Name of College Govt. Degree College, Bijbehara Govt. Womens College Anantnag Govt. Boys College, Anantnag Govt. Degree College Women, Baramulla Govt. Degree College, Sopore Govt. Degree College Boys, Baramulla Govt. Degree College, Ganderbal Govt. Degree College, Kulgam Govt. Degree College of Handwara Govt. Degree College, Kupwara Govt. Degree College, Pulwama Govt. Degree College, Tral Govt. Degree College, Shopain Amar Singh College, Srinagar Govt. Degree College, Bemina Govt College for Women, M A Road, Srinagar Sri Pratap College, Srinagar Islamia College of Science & Commerce,Hawal,Srinagar Gandhi Memorial College, Srinagar Govt. Women College, Nawakadal, Srinagar Govt. Women’s College, Srinagar (A.S. College Campus, Srinagar) S.S.M. College of Engineering, Baramulla Kashmir Law College, Nowshera, Srinagar Institute of Asian Medical Science Unani, Zakura Bibi Haleema Nursing College, Srinagar Kashmir Tibbiya College, Saida Kada, Srinagar Kausar College of Computer Science,Nowshera,Srinagar Iqbal Institute of Technology and Management,Budgam Vitasta School of Law & Humanities Govt. Dental College, Srinagar Govt. College of Education, Srinagar Institute of Music & Fine Arts, Srinagar Govt. Medical College, Srinagar DOEACC, Rangreth Srinagar Composite Regional Centre Rehmate Aalam College of Education (RAC)-Anantnag Shah-i-Hamdan College of Education (SHCE)-Siligam Muslim Educational Trust (MET) -Sopore KSERT College of Education–Humhama Budgam Gandhi Memorial College of Education (GMC)-Jammu Vishwa Bharti College of Education (VBC)-Jammu Shiekh-ul-Aalam College of Education (SAC)-Kupwara Shanti Niketan College of Education (SNCE)-HMT Shadab College of Education (ShCE)-HMT Srinagar
z valueofkurtosis ¼
1:587 ¼ 2:261 0:702
ð5Þ
If all the z-values lies between 1:96 and þ1:96, then the data are little skewed and kurtotic for both TAW and aXe but it does not differ significantly from normality. We can assume that our data are approximately normally distributed in terms of skewness and kurtosis. To represent effective graphical technique, a Histogram is used which showed the both skewness and kurtosis of the data. The following Figs. 1 and 2 represents the skewness and kurtosis of our data obtained from TAW and aXe tool, respectively. The statistical interpretation of data which is obtained from these two web accessibility evaluation tools namely TAW and aXe tool is presented in Table 4. It is found that the number of guidelines scores not reviewed in TAW tool is 1356 and in aXe tool is 1733, so there is a need for web accessibility experts for manual evaluation processes to minimize it. The mean and standard deviation of TAW tool is higher than aXe tool. The number of warnings is higher than the problems or violations found, this should be minimized so that accessibility can be achieved successfully and indirectly, the accessibility score of websites also enhanced. The diagrammatic representation of the comparison of results obtained by TAW and aXe tool during evaluation processes is shown in Fig. 3.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx Table 3 Statistical Inference of TAW and aXe tool. Descriptives
TAW
Mean 95% Confidence Interval for Mean
Lower Bound Upper Bound
5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis aXe
Mean 95% Confidence Interval for Mean
Lower Bound Upper Bound
5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis
Fig. 1. Accurate graphical representation- a Histogram with trend of accessibility score obtained via TAW tool.
Moreover, the analyzed outliers based on aXe tool results of 44 websites in terms of violations and needs review are 4 to 226 and 0 to 184, respectively. Similarly, TAW tool outliers based on problems, warnings and not reviewed issues of 44 websites are 4 to 219; 2 to 2877 and 26 to 36, respectively are identified and analyzed. 4.1. Tests of normality The null hypothesis for this test of normality is that the data are normally distributed. The result obtained by these tests are presented in Table 5 and the result indicates that the p-value (significant value) below 0:05 means the null hypothesis is rejected. Hence, the data are not distributed normally.
Statistic
Std. Error
419.6136 248.0048 591.2225 320.2879 266.5000 318605.126 564.45117 23.00 2937.00 2914.00 299.75 3.505 13.159
85.09422
83.7273 68.2836 99.1710 79.3636 75.0000 2580.342 50.79707 19.00 235.00 216.00 57.25 1.324 1.587
7.65795
0.357 0.702
0.357 0.702
Fig. 2. Accurate graphical representation- a Histogram with trend of accessibility score obtained via aXe tool.
4.2. Q-Q plot Using SPSS procedure for the data obtained from TAW and aXe tool from the accessibility evaluation testing of college websites affiliated with the University of Kashmir and Cluster University Srinagar. The following graphs in Fig. 4–7 represents the normal as well as the detrended quartile-quartile plot with respect to violation score estimated during analysis of college websites by using two web accessibility evaluation tools namely TAW and aXe tool. These graphs indicate that how much the deviations from normal and the comparison between the analysis results obtained from these two evaluation tools.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Table 4 Statistical Inference: TAW and aXe tool results. Tools/ Statistical Inference
TAW
Total Mean STDEV
aXe
Problems
Warnings
Not Reviewed
Violations
Needs Review
2646 60.14 51.85
15995 363.52 556.35
1356 30.82 3.06
1951 44.34 39.86
1733 39.39 33.40
Fig. 3. Result Comparison: TAW versus aXe tool.
Table 5 Test for Normality. Fig. 5. TAW tool: Detrended quartile-Quartile (Q-Q) representation.
Tests of Normality Kolmogorov–Smirnov TAW aXe ⁄
Statistic .256 .133
df 44 44
⁄
Shapiro–Wilk Sig. .000 .049
Statistic .559 .882
df 44 44
Sig. .000 .000
Lilliefors Significance Correction.
Fig. 6. aXe tool: Normal quartile-Quartile (Q-Q) representation.
Fig. 4. TAW tool: Normal quartile-Quartile (Q-Q) representation.
4.3. Box plot The comparison between TAW and aXe tools analysis of college websites in terms of accessibility violation of guidelines are presented in Fig. 8. 4.4. Estimation of type of guidelines and their accessibility issues During accessibility analysis, the report of WCAG guidelines which are commonly violated by using aXe tool for college websites
evaluation process is presented in Table 6. The Table 6 presents type of guideline with respect to their violation score, mean and standard deviation. It is also found that the guidelines namely elements must have sufficient color contrast, images must have alternate texts, and links must have visible text are highly violated and their violation scores are 2567; 380 and 329, respectively. Also, guidelines like id attribute value must be unique and hlii elements must be contained in huli or holi have a score of violation 76 and 64, respectively and the other guidelines have score of violations below 50 means very little. The overall score of 44 college websites with respect to guidelines in terms of violations and needs review by using aXe tool is mentioned in Table 7 and their aggregate graphical representation in terms of violations and needs review is shown in Fig. 9.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx Table 6 Guidelines and their score of violations among college websites. Type of Guideline
Fig. 7. aXe tool: Detrended quartile-Quartile (Q-Q) representation.
Elements must have sufficient color contrast Headings must not be empty < html> must have a lang attribute Images must have alternate texts Image buttons must have alternate text Form elements must have labels Links must have visible text Zooming and scaling must not be disabled < marquee> elements are deprecated and must not be used Id attribute value must be unique Text of buttons and links should not be repeated in the image alternative < ul> and
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Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites Abid Ismail, K.S. Kuppusamy ⇑ Department of Computer Science, School of Engineering and Technology, Pondicherry University, Pondicherry 605014, India
a r t i c l e
i n f o
Article history: Received 22 November 2018 Revised 29 March 2019 Accepted 29 March 2019 Available online xxxx Keywords: Web accessibility WCAG College websites Accessibility evaluation tools Test of normality Success criteria
a b s t r a c t The World Wide Web Consortium (W3C) has provided the most important set of guidelines for web accessibility which is popularly known as Web Content Accessibility Guidelines (WCAG). The accessibility analysis of higher education websites becomes paramount important to make them inclusive considering the growing number of enrollments of persons with disabilities (PwDs) in higher education, in countries such as India. This paper presents the accessibility analysis of higher education websites with the case study of college websites (N ¼ 44) affiliated with the University of Kashmir and Cluster University Srinagar. The study has been carried out with two major accessibility evaluation tools called web accessibility test, denoted as TAW and the accessibility engine powering browser extensions called the accessibility engine, denoted as aXe. This paper lists the major accessibility barriers exposed by these sites in terms of metrics such as a number of problems, warnings and a status of success criteria violations. With respect to TAW tool, a number of problems observed were 2646, a large number of warnings to the scale of 15995 and the not reviewed items were 1356. With aXe tool, the total violations observed were 1951 and items needing review were 1733. Findings of the statistical analysis are also presented in this paper. This paper presents a roadmap of steps for making these websites inclusive and barrier-free for PwDs. Ó 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction The modern age is the age of information technology especially the age of the Internet. So there is a need for accessing resources rendered via Internet platform, in many dimensions of day-today life such as e-commerce, educational resources, banking, travel and tourism. PwDs are no exception to this phenomenon. Indeed, the rendering of resources via Internet makes the life of PwDs simpler provided that the platform satisfies the accessibility criteria. The vice versa is also true that if the web-sites through which these services are rendered are not accessible then the PwDs face great number of barriers in interacting and utilizing these resources.
⇑ Corresponding author. E-mail address: [email protected] (K.S. Kuppusamy). Peer review under responsibility of King Saud University.
Production and hosting by Elsevier
Higher education is an important component in making the PwDs skillful and making them self-reliant in terms of financial and other requirements. Hence, it becomes important for making the higher education sites completely accessible or at-least minimize the barriers to the maximum possible extent. In countries such as India, with large number of youth population and proportionate number of persons with disabilities in that age spectrum, it gains increased significance to make the higher education website pose as minimal friction as possible, if not nothing. As per census 2011 in India 1, the disabled population by type of major activities is presented in Table 1. The Government of India’s pioneering initiatives such as Accessible India and Digital India have accelerated the work happening in this sector. In the digital ecosystem of India, it becomes foremost important to provide the web accessibility report of websites for the support and enhancement of these Digital India and Accessible India Campaign or Sugamya Bharat Abhiyan2 initiatives. For this, we considered 1 Available at:https://unstats.un.org/unsd/demographic-social/meetings/2016/ bangkok-disability-measurement-and-statistics/Session-6/India.pdf. 2 Available at:http://accessibleindia.gov.in/content/.
https://doi.org/10.1016/j.jksuci.2019.03.011 1319-1578/Ó 2019 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Table 1 Disabled Non-Workers Population (in Millions) by type of Major Activities, India as per Census 2011. Type of Disability
Total (Millions)
Total disabled non-worker In seeing In hearing In speech In movement Mental abnormality Mental Illness Any other Multiple disability
Major Non-Economic Activity (Percentage) Student
Household duties
Dependent
Pensioner
Others
27.2 28 32.5 37.2 19.7 24.5 9.3 37.4 15
15.3 17.3 18.9 20 13.4 9.6 11.9 17.7 7.3
45.7 42.7 38.7 33.5 49.8 57.7 66.6 35.4 65.9
5.5 6.7 4.9 3.4 8.8 2.1 2.8 3.2 6.8
5.6 4.7 4.6 5.4 7.4 5.4 8.2 5.8 4.3
17.1 3.1 3 1.2 3.4 1.2 0.6 2.9 1.7
Source: C-Series, Table C-24, Census of India 2011.
the specific part of websites called higher educational websites of India for the evaluation process. In 2016, an exploratory study was performed based on web accessibility of 302 Indian universities homepages (Ismail and Kuppusamy, 2018b). Now, we planned to do a zone-wise evaluation of college websites affiliated with universities of the entire nation. So, this paper aims towards measuring the accessibility barriers posed by higher education websites with the case study of 44 colleges affiliated to University of Kashmir 3 and Cluster University Srinagar 4 of the state Jammu and Kashmir (Division Kashmir Province) in northern India. For making these web resources accessible, standard guidelines were framed and constantly getting updated by World Wide Web Consortium (W3C). These guidelines should be followed strictly by the developers of websites and resources for making them universally accessible. According to Tim Berners-Lee 5, the Web accessibility is the degree to which the Internet and its tasks are put at the distribution of all types of users whatever their requirements, locations, languages, physical and mental aptitudes, etc. This concept was also referenced by researchers (Bravo, 2005) in their work on web accessibility field. With the increasing emphasis on universal design principles, it becomes mandatory to maintain a level-playing field for all categories of users, irrespective of their age or physical/mental disabilities. So, accessibility is a concept arises to make the web resources accessible for all kinds of people. Making the navigation, browsing and interaction etc. of web resources easy for everyone is the main aim of web accessibility. When the website follows the guidelines which are framed by W3C or some country-based specific guidelines relevant to WCAG, then the site is universally accessible. If there is some mismatch then accessibility issue arises which increases the barrier in accessing these resources. If the web accessibility guidelines are not followed strictly, there would be large number of people who will be excluded from the benefits of web based electronic services. Therefore, this study focuses on Universal accessibility issues on the web pages in their current state. To measure the level of conformance, many accessibility analysis tools have been developed for assessment of websites. For this study, we have used two accessibility evaluation tools TAW and aXe for checking accessibility status of colleges affiliated with the universities under different parameters. Therefore, following research objectives are to be proposed for this web accessibility assessment with a case study of colleges, affiliated with University of Kashmir and Cluster University Srinagar:
3 4 5
Available at:http://www.kashmiruniversity.net/. Available at:http://www.cusrinagar.edu.in/. Available at:https://www.w3.org/standards/webdesign/accessibility.
1. To find the web accessibility issues of web pages in terms of WCAG principles; 2. To extract the problems, warnings and not reviewed guidelines of web pages in terms of WCAG guidelines; 3. To find the success criteria estimation of web pages; 4. To identify the major violation of guidelines among the sites; 5. To provide proper suggestions for increasing the accessibility of these web pages. The other sections of this paper are organized as follows. Section 2 presents the relevant literature review based on assessment of web accessibility regarding with different types of websites used for evaluation process. In Section 3, we have explored web accessibility concepts and standards, and the characteristics of the tools which are used for evaluation process to check accessibility status of higher education websites. The work based on the analysis tools used in our study and their corresponding statistical inferences are presented in Section 4. The estimation of guideline violations among college websites with respect to their number, mean and standard deviation are presented in Section 4.4. The Section 5 involves two major subsections namely discussions about results and the suggestions regarding improvements. Therefore, the Section 5.1 presents the discussion about the result obtained and the Section 5.2 presents suggestions for minimizing the accessibility issues of these websites and provide alternative feedback for their accessibility enhancement. It also provides some important steps to enhance the web accessibility and usability of websites. Finally, the Section 6 presents the conclusion of our study that benefits the college website developers and designers for achieving the universality of the web for all without any hindrances when implemented. 2. Review of literature Making the Web more accessible for (PwDs), governments around the world have been setting up legislations and laws. For achieving the web accessibility successfully, more than 19 countries have established their own policies, laws, and legislations as per World Wide Web Consortium website laws and policies 6. This section presents some of the related research studies published by researchers throughout the world with respect to web accessibility and usability issues of the web regarding with PwDs. One of the clear reasons for using the Internet by the PwDs was found to access government websites and official services were studied in 2007 by the UK Office for Disability Studies (Kuzma et al., 2009). Also, an exploratory study was carried out (Al-Khalifa, 2012) on the accessibility of Saudi Arabia government websites and presented some recommendations for improving web accessibility along with future implications. 6
Available at:https://www.w3.org/WAI/Policy/. Accessed July 18, 2017.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
There is a lot of research carried out on higher education institutions in terms of web accessibility assessments. Like, an exploratory study was carried out by researchers (Ismail and Kuppusamy, 2018b) on accessibility analysis of Indian Universities homepages by using different web accessibility evaluation tools and classify them into three categories based on accessibility score. Also, an automated assessment tool called SortSite testing tool was used for analyzing 20 public Turkish universities to find the accessibility issues (Yerlikaya and Durdu, 2017). It was found that no single university fully satisfy the WCAG 2.0 accessibility criteria. Similarly, researchers (Akgül, 2017) carried out the accessibility evaluation of 23 Turkish universities homepage and identified the most violated WCAG 1.0 guidelines by the developers of university websites in Turkey. A study on web accessibility in Turkey has been carried out by researchers like (Inal et al., 2017). It was inferred that the user experience professionals in Turkey need to be improved in terms of web accessibility awarenesses, education, and training of web accessibility so that the accessibility for all will be enhanced. Another, accessibility study of Turkish universities homepage by using automatic evaluation tools was performed by researchers (Kurt, 2011). It was found that all university homepages showed some accessibility violations and warnings. Also, several suggestions are provided to enhance the web accessibility of websites (Kurt, 2017). Researchers like (Ismail et al., 2017a,b; Ahmi and Mohamad, 2015; Anderson, 2004; Harper and DeWaters, 2008; Ojha et al., 2018; Ismail and Kuppusamy, 2019; Ismail and Kuppusamy, 2018a) used online automatic tools like AChecker, WAVE, Bobby, SortSite, Cynthia Says, Hera, etc. for evaluation of websites in terms of WCAG 1.0 and WCAG 2.0 guidelines to find violations and warnings. Accordingly, they provide the feedback to developers and designers to enhance the web accessibility and readability of websites so that the PwDs can access the web resources easily, means to make the sites universally accessible. Also, a study was carried out by researchers (Ismail and Kuppusamy, 2016) to find accessibility analysis of North East India region websites by using online automatic evaluation tools like AChecker and WAVE. By analyzing the existing literature like (Fernandes et al., 2012; Gonçalves et al., 2013; Lee et al., 2013; Martins et al., 2015), we inferred that the statistical representation mainly gathered in tables and charts, whatever the statistical indicator used to analyze and interpret the evaluations results is not only to understand the overall results; but also to easily and quickly to perceive the target group tendency towards being or not web accessible grievances or criticism. Researchers like (Menzi-Çetin et al., 2017) carried out the research on usability of websites for visually impaired students. They involved six visually impaired students for evaluation processes of university websites in terms of usability. It was found that there is lack of basic accessibility components and need for their implementation like search engines, text versions, sequences of links with tabs and much more accessible features. Moreover, the researchers (Velleman et al., 2017) have identified the five categories of factors, which are adoption, external, personal and the factors related to web design process and organization structure. Later, they explained the adoption and implementation processes within e-government systems and organizations for web accessibility guidelines and standards. Similarly, researchers such as (Juárez-Ramírez, 2017; Ismailova and Kimsanova, 2017, Barroso et al., 2017; Ismailova and Inal, 2017; Al-Khalifa et al., 2017; Barricelli et al., 2017; Gonçalves et al., 2018; Kuppusamy and Aghila, 2017; Karaim and Inal, 2017; Kuppusamy, 2018; Liu et al., 2017; Goette et al., 2006) have analyzed web pages or websites, and also gave a lot of contributions in the field based on accessibility and usability of websites, in order to make the web accessible and usable for all. For produc-
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ing a quality website, a central criterion called validity evaluation is important to the success of accessibility efforts 7 and as such, it is a valuable step in accomplishing accessibility goals 8. Therefore, based on inferences from a review of the literature, it is important to investigate and identify the issues regarding with web accessibility of higher education institutions. In this paper, we are considering the case study of college websites affiliated with two Indian universities. 3. Web accessibility Making web pages easier to navigate and read, for every single user visiting the site, irrespective of the disabilities that they are experiencing, is the main goal of web accessibility. That is, inclusive practices to remove the web access barriers. The needs that web accessibility aims to address include visual, motor, auditory, seizures and cognitive or intellectual disabilities. When the websites are correctly designed, developed and edited, then all types of users can get equal and barrier-free access to information and functionality. In 1999, the Web Accessibility Initiative (WAI), a project by World Wide Web Consortium (W3C) was framed for achieving this accessibility concept. WAI had published two versions of Web Content Accessibility Guidelines namely WCAG 1.0 in 1999 and its updated version WCAG 2.0 in 2012 based on guidelines, checkpoints, success criteria, 4 principles, 3 levels of priority, conformance, etc. In addition to this, another WCAG version of W3C called WCAG 2.1 is recommendation since June 20189. It covers a wide range of recommendations for making web content more accessible to maximize the future applicability of accessibility efforts. Moreover, WCAG 2.0 is still W3C recommendation and does not deprecated by WCAG 2.1. From a broader perspective, for a website to be considered accessible, a website must obey with existing regulations and guidelines like Section 508, Stanca Act, GIGW, WCAG, etc. The W3C’s official website10 has mentioned the detailed summary of what these guidelines (WCAG) mean, their comparison and why they are important for web accessibility. Based on WCAG, different accessibility evaluation tools have been developed for checking whether the web page or website is accessible or not. Therefore, TAW and aXe tools are used in this paper to investigate and identify the major issues of higher education websites, because of their some characteristics as presented in Section 3.1. Also, these two tools categorize the identified issues into different groups that provides easy way to help accessibility specialist and experts to solve them successfully. 3.1. Tools used In this accessibility study, we used the following accessibility evaluation tools to check the violations of guidelines in terms of the WCAG principles along with their detailed list of issues: 1. TAW- Test de Accessibilidad Web: It is based on both versions of WCAG 1.0 & WCAG 2.0, and its own set of heuristics or guidelines for mobile accessibility (mobileok beta version). The TAW 11 clearly marks the accessibility violations that it finds and provides the proposal on how to solve them. This tool is
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Available at:https://validator.w3.org/docs/help.html. Accessed June 25, 2017. Available at:https://www.w3.org/WAI/GL/2005/06/validity-accessibility.html. Accessed June 21, 2017. 9 Available at:https://www.w3.org/TR/WCAG21/. Accessed Jan 12, 2019. 10 Available at:https://www.w3.org/WAI/WCAG20/from10/comparison/. Accessed July 18, 2017. 11 Available at:http://www.tawdis.net/ingles.html?lang=en, Accessed March 14, 2017. 8
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
developed by the CTIC Centro Technologico de la Informacion y la Comuicacion and is freely available online, as a desktop application and as a Firefox add-on. 2. aXe-Easy accessibility testing tool: It is a free and open source testing tool, developed by Deque. The tool runs in your browser as an extension for Chrome as well as Firefox. The working analysis instructions of the tool as explained in the Deque Systems site 12. The aXe tool’s dashboard provides the list of issues and how many times the issues occur on the page. In addition to this, it also provides the detailed description of the issue, information about the severity of issues and which type of guidelines are being violated. Moreover, TAW and aXe written in this format indicates the representation of functionality of these two major accessibility evaluation tools called web(W) accessibility(A) test (T) or Test (T) Accessilibilidad (A) Web (W), denoted as TAW and the accessibility (a) engine (e) powering browser extensions (X) called the accessibility engine, denoted as aXe. 4. The case study This paper is based on a case study conducted with 44 college websites affiliated to University of Kashmir and Cluster University Srinagar. This study was conducted during the period from October 2016 to June 201713 The said list of forty-four ð44Þ colleges affiliated with University of Kashmir and Cluster University Srinagar are shown in Table 2 used for the web accessibility evaluation process. The websites of these 44 colleges are taken up to depth-one level only to evaluate them. So, 44 homepages of these websites are taken for evaluation process because of their popularity and most important and visiting page from the website. The descriptive report of these 44 college websites by using two different web accessibility evaluation tools namely TAW and aXe tool are in Table 3. The table also presents various parameters report with respect to their statistics and standard errors. For characterization of data which is obtained from TAW and aXe tool includes skewness and kurtosis 14. To measure symmetry or lack of symmetry of data, we use skewness. The distribution is symmetric if it looks the same to the left and right of the center point. The z-values of skewness and kurtosis which lies 1:96 to 1:96 is obtained using equation 1.
z-value ¼
statistic standard error
ð1Þ
Therefore, the z-value of skewness and kurtosis obtained from Table 3 statistic and standard error of college websites with respect to TAW and aXe tool report are as under: In case of TAW tool,
3:505 ¼ 9:818 0:357
ð2Þ
13:159 ¼ 18:745 0:702
ð3Þ
1:324 ¼ 3:709 0:357
ð4Þ
z valueofskewness ¼ z valueofkurtosis ¼ In case of aXe tool,
z valueofskewness ¼
12
Available at:https://www.deque.com/products/axe/. Accessed March 03, 2017. Available at:http://www.kashmiruniversity.net/Colleges.aspx. Accessed December 13, 2016. 14 Available at:http://www.itl.nist.gov/div898/handbook/eda/Section3/eda35b.htm, Accessed July 10, 2017. 13
Table 2 List of Colleges affiliated with University of Kashmir and Cluster University Srinagar. S.No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
Name of College Govt. Degree College, Bijbehara Govt. Womens College Anantnag Govt. Boys College, Anantnag Govt. Degree College Women, Baramulla Govt. Degree College, Sopore Govt. Degree College Boys, Baramulla Govt. Degree College, Ganderbal Govt. Degree College, Kulgam Govt. Degree College of Handwara Govt. Degree College, Kupwara Govt. Degree College, Pulwama Govt. Degree College, Tral Govt. Degree College, Shopain Amar Singh College, Srinagar Govt. Degree College, Bemina Govt College for Women, M A Road, Srinagar Sri Pratap College, Srinagar Islamia College of Science & Commerce,Hawal,Srinagar Gandhi Memorial College, Srinagar Govt. Women College, Nawakadal, Srinagar Govt. Women’s College, Srinagar (A.S. College Campus, Srinagar) S.S.M. College of Engineering, Baramulla Kashmir Law College, Nowshera, Srinagar Institute of Asian Medical Science Unani, Zakura Bibi Haleema Nursing College, Srinagar Kashmir Tibbiya College, Saida Kada, Srinagar Kausar College of Computer Science,Nowshera,Srinagar Iqbal Institute of Technology and Management,Budgam Vitasta School of Law & Humanities Govt. Dental College, Srinagar Govt. College of Education, Srinagar Institute of Music & Fine Arts, Srinagar Govt. Medical College, Srinagar DOEACC, Rangreth Srinagar Composite Regional Centre Rehmate Aalam College of Education (RAC)-Anantnag Shah-i-Hamdan College of Education (SHCE)-Siligam Muslim Educational Trust (MET) -Sopore KSERT College of Education–Humhama Budgam Gandhi Memorial College of Education (GMC)-Jammu Vishwa Bharti College of Education (VBC)-Jammu Shiekh-ul-Aalam College of Education (SAC)-Kupwara Shanti Niketan College of Education (SNCE)-HMT Shadab College of Education (ShCE)-HMT Srinagar
z valueofkurtosis ¼
1:587 ¼ 2:261 0:702
ð5Þ
If all the z-values lies between 1:96 and þ1:96, then the data are little skewed and kurtotic for both TAW and aXe but it does not differ significantly from normality. We can assume that our data are approximately normally distributed in terms of skewness and kurtosis. To represent effective graphical technique, a Histogram is used which showed the both skewness and kurtosis of the data. The following Figs. 1 and 2 represents the skewness and kurtosis of our data obtained from TAW and aXe tool, respectively. The statistical interpretation of data which is obtained from these two web accessibility evaluation tools namely TAW and aXe tool is presented in Table 4. It is found that the number of guidelines scores not reviewed in TAW tool is 1356 and in aXe tool is 1733, so there is a need for web accessibility experts for manual evaluation processes to minimize it. The mean and standard deviation of TAW tool is higher than aXe tool. The number of warnings is higher than the problems or violations found, this should be minimized so that accessibility can be achieved successfully and indirectly, the accessibility score of websites also enhanced. The diagrammatic representation of the comparison of results obtained by TAW and aXe tool during evaluation processes is shown in Fig. 3.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx Table 3 Statistical Inference of TAW and aXe tool. Descriptives
TAW
Mean 95% Confidence Interval for Mean
Lower Bound Upper Bound
5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis aXe
Mean 95% Confidence Interval for Mean
Lower Bound Upper Bound
5% Trimmed Mean Median Variance Std. Deviation Minimum Maximum Range Interquartile Range Skewness Kurtosis
Fig. 1. Accurate graphical representation- a Histogram with trend of accessibility score obtained via TAW tool.
Moreover, the analyzed outliers based on aXe tool results of 44 websites in terms of violations and needs review are 4 to 226 and 0 to 184, respectively. Similarly, TAW tool outliers based on problems, warnings and not reviewed issues of 44 websites are 4 to 219; 2 to 2877 and 26 to 36, respectively are identified and analyzed. 4.1. Tests of normality The null hypothesis for this test of normality is that the data are normally distributed. The result obtained by these tests are presented in Table 5 and the result indicates that the p-value (significant value) below 0:05 means the null hypothesis is rejected. Hence, the data are not distributed normally.
Statistic
Std. Error
419.6136 248.0048 591.2225 320.2879 266.5000 318605.126 564.45117 23.00 2937.00 2914.00 299.75 3.505 13.159
85.09422
83.7273 68.2836 99.1710 79.3636 75.0000 2580.342 50.79707 19.00 235.00 216.00 57.25 1.324 1.587
7.65795
0.357 0.702
0.357 0.702
Fig. 2. Accurate graphical representation- a Histogram with trend of accessibility score obtained via aXe tool.
4.2. Q-Q plot Using SPSS procedure for the data obtained from TAW and aXe tool from the accessibility evaluation testing of college websites affiliated with the University of Kashmir and Cluster University Srinagar. The following graphs in Fig. 4–7 represents the normal as well as the detrended quartile-quartile plot with respect to violation score estimated during analysis of college websites by using two web accessibility evaluation tools namely TAW and aXe tool. These graphs indicate that how much the deviations from normal and the comparison between the analysis results obtained from these two evaluation tools.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Table 4 Statistical Inference: TAW and aXe tool results. Tools/ Statistical Inference
TAW
Total Mean STDEV
aXe
Problems
Warnings
Not Reviewed
Violations
Needs Review
2646 60.14 51.85
15995 363.52 556.35
1356 30.82 3.06
1951 44.34 39.86
1733 39.39 33.40
Fig. 3. Result Comparison: TAW versus aXe tool.
Table 5 Test for Normality. Fig. 5. TAW tool: Detrended quartile-Quartile (Q-Q) representation.
Tests of Normality Kolmogorov–Smirnov TAW aXe ⁄
Statistic .256 .133
df 44 44
⁄
Shapiro–Wilk Sig. .000 .049
Statistic .559 .882
df 44 44
Sig. .000 .000
Lilliefors Significance Correction.
Fig. 6. aXe tool: Normal quartile-Quartile (Q-Q) representation.
Fig. 4. TAW tool: Normal quartile-Quartile (Q-Q) representation.
4.3. Box plot The comparison between TAW and aXe tools analysis of college websites in terms of accessibility violation of guidelines are presented in Fig. 8. 4.4. Estimation of type of guidelines and their accessibility issues During accessibility analysis, the report of WCAG guidelines which are commonly violated by using aXe tool for college websites
evaluation process is presented in Table 6. The Table 6 presents type of guideline with respect to their violation score, mean and standard deviation. It is also found that the guidelines namely elements must have sufficient color contrast, images must have alternate texts, and links must have visible text are highly violated and their violation scores are 2567; 380 and 329, respectively. Also, guidelines like id attribute value must be unique and hlii elements must be contained in huli or holi have a score of violation 76 and 64, respectively and the other guidelines have score of violations below 50 means very little. The overall score of 44 college websites with respect to guidelines in terms of violations and needs review by using aXe tool is mentioned in Table 7 and their aggregate graphical representation in terms of violations and needs review is shown in Fig. 9.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx Table 6 Guidelines and their score of violations among college websites. Type of Guideline
Fig. 7. aXe tool: Detrended quartile-Quartile (Q-Q) representation.
Elements must have sufficient color contrast Headings must not be empty < html> must have a lang attribute Images must have alternate texts Image buttons must have alternate text Form elements must have labels Links must have visible text Zooming and scaling must not be disabled < marquee> elements are deprecated and must not be used Id attribute value must be unique Text of buttons and links should not be repeated in the image alternative < ul> and
- must only directly contain < li>, < script> and elements < li> elements must be contained in
- elements must be contained by a
- Frames must have title attribute Active elements must have alternate text Buttons must have visible text < video> elements must have captions < video> elements must have audo description track All the element and elements with role = columnheader/rowheader must datacells which it describes Certain ARIA roles must contain particular children Page must have means to bypass repeated blocks Radio inputs with the same name attribute value must be part of group Elements should not have tabindex greater than zero
Total Violations
Mean
STDEV
2567 11 31 380 22 46 329 11
58.34 0.25 0.71 8.64 0.5 1.05 7.47 0.25
44.25 0.49 0.76 10.79 2.57 1.68 10.6 0.49
20 76
0.45 1.73
0.9 4.4
9
0.2
0.95
12 64
0.27 1.45
0.59 5.32
32
0.73
4.67
19 16
0.43 0.36
0.73 1.63
11 9 9
0.25 0.2 0.2
0.69 0.59 0.59
1
0.02
0.15
3
0.07
0.33
2
0.05
0.21
1
0.02
0.15
3
0.07
0.45
information about the severity of issues and which type of guidelines (WCAG 2.0) are being violated. Fig. 8. Boxplot comparison of result between TAW and aXe tools.
5. Discussions and suggestions Another accessibility evaluation report of 44 college websites generated by using TAW tool are summarized in Table 8. This TAW tool presents the results of 44 college websites affiliated with the University of Kashmir and Cluster University Srinagar, in terms of Four WCAG principles and success criteria with respect to problems, warnings and not reviewed guidelines as shown in Table 8. The aggregate score of TAW tool with respect to Four WCAG principles namely Perceivable, Operable, Understandable and Robust along with success criteria is presented in Table 9. The diagrammatic representation of accessibility status of 44 college websites with respect to four WCAG principles namely Perceivable, Operable, Understandable and Robust, and the success criteria by using TAW tool under WCAG 2.0 level AA guidelines (Problems, Warnings, Not reviewed) is shown in Fig. 10. Therefore, in this case study of 44 college websites, TAW tool involves only level AA of conformity to identify issues based on perceivable, operable, understandable, robust and success criteria. It gives result in the form of problems, warnings and not reviewed issues based on POUR and SC violations of websites. In the aXe tool, there is no concept about levels of conformity but it includes all levels of conformity and provides results in the form of dashboard to list and count the issues (violations and needs review) on the web page. It also provides the detailed description of the issues,
5.1. Discussions Based on the evaluation result of 44 college websites by using automatic evaluation tools, it is found that the color contrast, alternative texts, link visibility, list elements, lang attributes, form labels, captions, and marquee elements, etc. are the major issues among the websites and their problem or issue rate is higher than other issues of the websites. It needs to be minimized so that accessibility will be enhanced. The accessibility status of number of problems, warnings and not reviewed in terms of perceivable, operable, understandable, robust and success criteria are (1100; 358; 95; 843; 250), (2989; 1492; 295; 10713; 506), and (176; 274; 211; 17; 678), respectively. In addition to this, it is found that the number of warnings of these websites are higher than the number of problems and needs review report of evaluation processes. As per TAW and aXe tool, total problems of these websites are 2646 and 1951, respectively. Furthermore, the total number of warnings of websites is 15995 with the mean and standard deviation are 363:52 and 556:35, respectively. It also needs to be optimized. Some of the issues of websites which are not detected by these tools, are categorized into not reviewed (TAW tool) and needs review (aXe tool). This type of evaluation result is not considered for web evaluation processes, it needs web accessibility specialist and
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Table 7 The overall score of 44 websites individually in terms of violations and needs review by using aXe tool. aXe Tool (Individual websites) Website S.No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
Total Violations Found
Total Needs Review
49 226 65 55 9 80 40 11 52 14 27 4 19 21 24 21 90 48 81 33 30 86 12 15 19 45 63 73 18 45 47 11 81 28 27 10 21 82 80 116 17 42 7 7
17 9 12 58 24 21 108 16 34 70 20 40 52 68 52 11 2 57 68 184 33 10 39 30 0 5 52 25 28 59 27 21 47 52 38 25 30 4 100 78 26 23 19 39
to solve it. Hence, there is a need for human inspection of these websites so that the web accessibility of these websites will be improved. In addition to, the overall result will be improved by the inclusion of manual evaluation process as complements of the performed automatic evaluation process (Rocha et al., 2015). Therefore, there is a need to perform a full assessment of websites by involving both organizations and web developers means to achieve full scope of evaluation processes, the web accessibility, and usability evaluation procedure is needed (Martins et al., 2017). 5.2. Suggestions Researchers increasingly suggest that the accessibility remains an important issue across the Web. Specifically, web accessibility issues are concerned with the users of web pages. These issues should be handled by giving proper awareness about accessibility guidelines to developers and designers. Following are the suggestions based on the major issues found in our study of websites to enhance the web accessibility of these 44 college websites. 1. First of all, it is important to note that the awareness about web accessibility is the first step for web developers and designers to design and develop accessible websites. 2. Color contrast issues: Provide sufficient color contrast means ensures the color contrast between foreground color and background color and also meets WCAG 2.0 color contrast ratios among the websites. 3. Text alternative issues: Ensure the images have alternative texts. 4. Links Visibility issues: Ensures the links with visible texts. 5. List elements issues: Ensures every list elements with unique value. 6. Lang attributes issues: Every HTML document is to add lang attribute. 7. Form labels issues: Protect every form element with labels. 8. Captions issues: Ensures audio tags with captions. 9. Marquee issues: Avoid using marquee elements, etc. These above suggestions are mentioned based on the result obtained from the tools used. At least, if the web developer and designer of these websites used the mentioned suggestions, the web accessibility of these websites are automatically enhanced and the websites will be more usable and more accessible. Furthermore, researchers (Anderson, 2004; Harper and DeWaters, 2008) provide some useful tips for enhancing web accessibility, is shown in Table 10. Also, to improve and enhance the usability and accessibility of web pages or websites, at-least a set of guidelines given in Section 5.3 should be followed by web administrators and web designers. The involvement of a skilled professional reviewer called experts for full compliance and risk mitigation is always needed even when we have a tool as well. 5.3. Improvement
Fig. 9. Graphical representation of college websites accessibility results by aXe tool.
proper experts to review these issues so that the web accessibility status of websites will be generated. In our result, we have 1356 not reviewed and 1733 needs review scores which needs experts
Based on accessibility evaluation report of 44 college websites, it is found that there is a need to focus on accessibility improvement of these websites. Following points based on issues found in these websites taken into consideration to improve their accessibility performances. Such as, provide them sufficient color contrast, ensure them alternative texts to images, links with visibility, audio tags with captions in videos, avoid marquees and protect elements with labels and unique values. Also, addition of accessibility components features of these websites like text size, language options, screen readers, accessibility statements, skip to
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx Table 8 Summary report of 44 college websites individually by using TAW accessibility evaluation tool. Problems Website S.No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
Warnings
Not Reviewed
P
O
U
R
SC
P
O
U
R
SC
P
O
U
R
SC
23 16 6 25 4 11 71 4 1 4 2 39 12 1 9 6 78 15 31 28 14 40 10 17 1 36 41 26 9 30 54 21 98 16 24 4 10 80 14 90 12 61 0 6
5 1 31 19 0 6 4 1 0 0 8 1 11 0 2 18 14 3 2 4 2 19 3 6 1 2 25 8 4 3 1 22 9 56 3 1 0 17 3 32 1 4 3 3
3 1 1 3 0 1 1 0 1 1 0 1 2 1 3 2 0 2 0 4 1 1 1 0 1 5 3 1 2 3 1 0 27 0 6 0 2 2 4 1 3 1 0 3
2 43 14 5 1 6 6 1 0 4 1 20 4 1 198 12 1 13 97 27 3 5 0 6 1 6 50 0 4 15 88 1 34 8 7 1 3 6 9 18 14 91 0 17
6 5 6 7 2 6 6 4 2 4 5 5 8 3 7 8 4 6 4 8 7 6 5 4 4 7 8 4 7 8 6 5 7 3 7 4 6 7 7 7 7 7 1 10
25 52 34 89 15 53 62 45 0 13 105 58 267 5 78 118 7 73 132 72 50 95 59 29 0 67 136 89 16 137 19 84 115 82 50 102 59 21 37 98 129 124 42 46
6 3 19 75 32 22 27 16 3 39 10 27 22 5 29 148 69 11 28 40 41 42 18 23 1 46 39 41 18 70 46 20 37 50 44 59 23 41 39 90 24 8 23 18
18 0 12 12 0 6 6 6 0 0 6 6 6 0 6 12 6 6 0 6 6 6 6 6 0 6 6 6 6 6 6 6 31 6 24 6 6 6 12 0 12 6 0 6
77 8 2803 468 210 168 23 9 0 50 3 8 9 2 13 129 369 2436 67 19 235 297 1 67 0 67 102 222 53 3 574 2 444 143 82 9 30 882 26 165 388 10 26 14
11 6 9 13 8 12 15 13 3 8 13 14 11 5 13 14 10 10 10 14 12 12 13 13 1 14 13 15 12 13 13 13 16 12 15 14 14 12 14 10 11 13 8 11
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
8 7 8 6 8 7 4 5 8 7 5 5 6 8 7 5 8 8 6 5 5 6 5 6 8 5 6 5 7 6 6 5 5 8 5 6 6 7 6 5 7 5 7 6
5 5 5 4 5 5 5 5 5 5 5 5 4 5 5 5 5 5 5 5 5 5 5 5 5 5 4 5 5 4 5 5 4 5 4 5 5 4 4 5 5 5 5 4
0 1 0 0 1 0 0 1 1 1 1 1 0 1 0 0 1 0 1 0 0 0 1 1 1 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0
17 17 17 14 18 16 13 15 18 17 15 15 14 18 16 14 18 17 16 14 14 15 15 16 18 14 14 15 16 14 15 15 13 18 13 15 15 15 14 14 16 14 17 14
Where P = Perceivable, O = Operable, U = Understandable, R = Robust, SC = Success Criteria.
Table 9 Overall result of accessibility evaluation of college websites by using TAW tool. TAW Tool Problems
Warnings
Not Review
Perceivable Operable Understandable Robust Success Criteria
1100 358 95 843 250
2989 1492 295 10713 506
176 274 211 17 678
Total
2646
15995
1356
navigations and main menu, font size, etc. should be included to enhance their accessibility. . In addition to this, for general following are the 10 guidelines (Rems, 2018) that improve and enhance the usability and accessibility of web pages or websites: 1. Include a site map on websites. 2. Use of clear and consistent Navigation systems. 3. Validate pages and style sheets.
4. Using automated accessibility assessment tools for website reviews. 5. Use HTML markup to provide semantic information. 6. Include alt text for all graphics and images that convey information. 7. Test pages with a keyboard. 8. Provide captions for embedded videos. 9. Provide transcripts for time-based media. 10. Test pages or websites on a mobile device. Moreover, to improve accessibility which should be understandable, manageable, measurable and achievable. The website at-least should follow the tips as mentioned in Table 10 and aforementioned guidelines for performing more usable and accessible result. The success of website involves the attributes like credibility, usability, efficiency, functionality, content and information, etc. So, website developers and designers should take into consideration these attributes during the overall life cycle of the website process. Furthermore, for creating a great user experience, accessibility and usability are necessary steps and they sometimes go hand in spite of their differences.
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
Fig. 10. TAW tool accessibility result with respect WCAG 2.0 Level AA of 44 college websites affiliated with University of Kashmir and Cluster University Srinagar.
Table 10 Quick Tips for accessibility. Web page Feature
Accessibility tip
Images and animations Image maps Multimedia Hypertext links Page organization Graphs and Figures Scripts, applets & plug-ins Frames Tables
Use the alt attribute to describe the function of each visual. Use the client-side map and text for hotspots. Provide captioning and transcripts of audio and descriptions of video. Use text that makes sense when read out of context. Avoid ’click here’. Use headings lists and consistent structure. Use cascading sheets for layout and style whenever possible. Summarize or use the longdesc attribute. Provide alternative content in case active features are inaccessible or unsupported. Use the no frames element and meaningful titles. Make line-by-line reading easy. Summarize.
6. Conclusion Today, educational websites are essential for institutions of higher education and their accessibility also plays the paramount role to their information retrieval, that is accessing the website ser-
vices. In order to provide accessibility, developers and designers must consider the accessibility issues and make effort to resolve and improve them based on design principles offered by W3C. In this study, we used two automatic evaluation tools namely TAW and aXe tool to find the accessibility status of 44 college web-
Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
A. Ismail, K.S. Kuppusamy / Journal of King Saud University – Computer and Information Sciences xxx (xxxx) xxx
sites affiliated with the University of Kashmir and Cluster University Srinagar. During evaluation process we identified 24 major issues with their violation scores are elements must have sufficient color contrast ð2567Þ, images must have alternate texts ð380Þ, Links must have visible text ð329Þ, Id attribute value must be unique ð76Þ; hlii elements must be contained in huli or holi ð64Þ and rest are below 50 in violation score. The result of this study indicates that the college websites affiliated with the University of Kashmir and Cluster University Srinagar are still not delivering full accessibility to users because of their problems ð2646Þ, warnings ð15995Þ, not reviewed ð1356Þ guidelines identified by TAW tool; and violations ð1951Þ, needs review ð1733Þ guidelines by aXe tool. It is found that the Warnings are maximum than problems identified and should be minimized by involving experts for manual judgment. The analysis data obtained from these tools is represented by using different statistical indicators to differentiate them each other and the normality test indicates that the distribution is not uniform. In addition to, z-values of kurtosis and skewness are also falling out of normal range indicates that there are high kurtosis and skewness. However, our findings should be valuable and helpful to web developers and designers of college websites affiliated with the said universities and hopefully, provide some suggestions for improving the accessibility of college websites. Hence, this study warrants further research so that patterns of compliance can be followed closely. For achieving the design of accessible websites universally upward, we should increasingly initiate the awareness of accessibility guidelines. This would hopefully upward the trend of accountability in the design of universally accessible websites. Hence, the awareness about web accessibility among developers and designers is the main factor for development and maintenance of accessible web content. Finally, it is the responsibility of web administrators along with individual organizations for achieving a high level of web accessibility by involving both automatic and manual evaluation processes. Conflict of Interest None. References Ahmi, A., Mohamad, R., 2015. Web accessibility of the malaysian public university websites. In: In International Conference on E-Commerce (ICoEC), pp. 171–177. Akgül, Y., 2017. The most violated wcag 1.0 guidelines by the developers of university websites in turkey. 2017 12th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, pp. 1–7. Al-Khalifa, H.S., 2012. The accessibility of Saudi Arabia government web sites: an exploratory study. Universal Access Inform. Soc. 11, 201–210. Al-Khalifa, H.S., Baazeem, I., Alamer, R., 2017. Revisiting the accessibility of Saudi Arabia government websites. Universal Access Inform. Soc. 16, 1027–1039. Anderson, M.O., 2004. Web accessibility–does your web site make the grade? Association of Small Computer Users in Education (ASCUE). Barricelli, B.R., Sciarelli, P., Valtolina, S., Rizzi, A., 2017. Web accessibility legislation in italy: a survey 10 years after the stanca act. Universal Access Inform. Soc., 1– 12 Barroso, J., Cota, M.P., Paredes, H., Hadjileontiadis, L., 2017. Technologies for enhancing accessibility and fighting info-exclusion. Bravo, I.F., 2005. Cognitive accessibility to hypertext systems: the role of verbal and visuospatial abilities of deaf and hearing users. In: Information Retrieval. Editorial de la Universidad de Granada. Fernandes, N., Costa, D., Duarte, C., Carriço, L., 2012. Evaluating the accessibility of web applications. Procedia Comput. Sci. 14, 28–35. Goette, T., Collier, C., White, J.D., 2006. An exploratory study of the accessibility of state government web sites. Universal Access Inform. Soc. 5, 41–50. Gonçalves, R., Martins, J., Branco, F., Barroso, J., 2013. Web accessibility–from the evaluation and analysis to the implementation–the anogov/peppol case.
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Please cite this article as: A. Ismail and K. S. Kuppusamy, Web accessibility investigation and identification of major issues of higher education websites with statistical measures: A case study of college websites, Journal of King Saud University – Computer and Information Sciences, https://doi.org/10.1016/j.jksuci.2019.03.011
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