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A practical, applied perspective guides the research, and it aligns with the principles of universal design, which aims to create products and environments that are usable by people of all abilities. In the context of digital accessibility, this means designing accessible websites for people with disabilities. This study, by examining the accessibility of higher education homepages, directly contributes to the goals of universal design by assessing how well these websites are meeting the needs of diverse users.
In this research, a sample of higher education institutions was identified to address this study’s primary research question of whether institution website homepages are accessible. In May 2024, a list of all institutions currently holding the Carnegie Classification of Institutions of Higher Education’s designation as Research 1 (R1) (N = 146 R1 institutions) or Research 2 (R2) (N = 133 R2 institutions) was generated to collect data (N = 279 total institutions) (Carnegie Classifications). Automated testing tools were selected due to their ease of access (novice users can interpret the data), availability (free of charge for anyone to use), and ease of use (novice users can effectively apply the tool). Consistent with current studies, two web accessibility tools were selected to review the institutions’ homepages –AChecker and WAVE Web Accessibility Evaluation Tool (WAVE). Additionally, because the tools have different success criteria and consider other components that impact website accessibility, this helps reduce quantitative bias. During the data collection, local versions of the websites were collected to ensure the study's repeatability and reproducibility. The main research question regarding the accessibility of the institution homepages is answered via descriptive statistics, including mean, median, and mode, which are used to ascertain the data set’s average and basic percentages. Additionally, measures of variability, including range and standard deviation, are used to determine how much the data varies from the central values. The results are presented in order of the research questions.
Across the population, the average institutional website has 14.40 errors when using AChecker (Table 2) and 10.83 errors when using WAVE (Table 3). However, many institutions have no errors, with 17 institutions showing no errors when analyzed with AChecker, 29 showing no error when analyzed with WAVE, and 11 showing no error by either checker (Table C3). There is a notable range in the data. When using AChecker, the maximum number of errors is 173, and the minimum is 0 (Table 2). Comparatively, when using WAVE, the maximum number of errors is 207, and the minimum is 0 (Table 3). When using AChecker, there are several variables that must be noted. When using the tool, it malfunctioned consistently on three institutions’ homepages: James Madison University, Prairie View A&M University, and University at Buffalo; therefore, there are three fewer data points in the AChecker analysis (N = 276 vs. N = 279). Application of the tool was attempted three times before moving on to the next institution’s webpage. Additionally, when reviewing the data, there is a considerable range when considering the recurrence of errors when analyzing the home pages. The institutions with the highest number of errors are Middle Tennessee State University (173 errors), Morgan State University (129 errors), and Long Island University (108 errors) (Table B1). Many institutions have few to no errors, with 14.5% of websites having no errors and 79.71% having 20 errors or less (Table 4).
When errors are broken down by WCAG standard within AChecker, WCAG 2.1.1 is the least common, occurring only on the University of California—Riverside’s homepage. WCAG 2.2.1 appears three times (Columbia University, SUNY at Albany, and Eastern Michigan University). WCAG 2.4.2 appears four times, and WCAG 3.1.1 appears five times. After that, the next most common error is WCAG 1.4.3 at 50 times. The most common error is WCAG 1.4.4, which appears 121 times (Table 5; Table C1). WAVE data must be considered in two parts: errors and potential errors. Within this tool, there are two types of definitive errors: errors and contrast errors. These errors do not require a manual check; however, they must be combined to generate an error number more similar to AChecker (Table D3). When reviewing the data, 239 of the 279 institutions have 20 errors or less (Tables 4, B1, B2, D2, and D3). Most institutions have few to no errors, with 10.39% of websites having no errors and 85.66% having 20 errors or less (Table 4; Figure 2). Long Island University’s homepage is an outlier with 207 errors; the next closest institutions are Texas Tech University (91 errors), University of Pittsburgh-Pittsburgh Campus (65 errors), and Clark Atlanta University (64 errors) (Table B1). All institutions in the study have at least one instructional designer on staff. While their jobs at the institutions probably vary, their presence has the potential for a positive impact. Of the institutions reviewed, 17 have no errors when using AChecker, 29 have no errors when using WAVE, and 11 have no errors with either tool. While it is impossible to directly correlate the existence of an instructional designer to the positive creation of the homepages, the rate of institutions with no errors is far higher than other prior studies. As a result, a majority of institutional home pages are not accessible even though there are instructional designers on staff. However, the most egregious errors are extremely limited. It is promising that most institutions have less than 20 errors per homepage when using automated tools to assess the content. This means that many web pages may be brought to compliance quickly.
Online learning in higher education has grown exponentially since the COVID-19 pandemic. Paired with the DOJ’s updated ruling, all digital materials must meet WCAG 2.1 Level AA standards. Instructional designers are uniquely positioned at institutions of higher education to positively impact decisions and help steer conversations toward digital accessibility needs.
Due to the changes in technology, web pages and digital course content are continually evolving. The home page may be the digital front door of an institution, but the learning materials and other web pages are what is inside the door, and their accessibility is critical to student success. This study may be replicated easily, and the tools may also be used to evaluate other digital learning materials as long as they are web based. The moment a document is placed in a web space (e.g., email, learning management system), it is required to meet WCAG standards as it has become web based digital material.
While COVID-19 was devastating, a positive that came from it was a renewed focus on digital accessibility. Instructional designers, with their unique skill set that requires them to be student focused, are positioned in such a way that they can continue accessibility conversations to ensure positive changes continue. While the DOJ has ensured that the conversation about digital accessibility will continue for the next several years, changes must start now instead of waiting for the deadline.
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