In the literature, there is insufficient research concerning the impact of web-accessible course content on academic performance. This research is critical to shaping our understanding of equitable and inclusive instructional practices in postsecondary academics. Web accessibility consists of built-in features on web pages and digital documents that give users with disabilities access to the web (WCAG, n.d.). The Web Content Accessibility Guidelines (WCAG), which are the leading guidelines for ensuring accessible web content describe ‘access’ as the ability to perceive, operate, and understand the web, and the ability for websites to communicate with assistive technologies such as screen readers (WCAG, n.d.).
The research supports the existence of a performance gap among college staff and faculty when it comes to implementing web accessibility (Alahmadi & Drew, 2017). For example, Alahmadi & Drew (2017) report 30,944 accessibility related home-page errors in 180 evaluated websites among the top universities in the world, Oceania, and Arab countries (Alahmadi & Drew, 2017). This study surveyed university homepages from around the globe for their conformance to web accessibility standards, finding that little improvement to web accessibility happened between 2005 and 2015. Most relevant to my research is the study’s focus on the accessibility of universities’ Learning Management Systems (LMSs). Its findings support that the foremost shortcomings in LMSs are a lack of audio files and videos, strict time limits on exams, inaccessible PowerPoint slides, extensive use of inaccessible course materials, and lack of adaptive technologies (Alahmadi & Drew, 2017). These limitations are what restrict students with disabilities in engaging in course continent to the same extent as their peers.
Web accessibility is becoming more important as the enrollment of students with disabilities continues to grow. In addition to their survey of top university home pages, Alahmadi and Drew (2017) report the growing percentage of students with disabilities and the growing popularity of distance higher education.
Instructional designers consider web accessibility a best practice for several reasons. Beyond conversations of diversity, equity, and inclusion, the principles of web accessibility align with those of instructional frameworks rooted in neuroscience, such as the Universal Design for Learning (UDL). UDL is a customizable instructional planning framework that applies Universal Design (UD) principles to the range of abilities in the affective, recognition, and strategic networks of the brain to promote learning (CAST, 2018). UD has its roots in the field of architecture (AlRawi et. al, 2022), specifically on designing buildings and roads that allows access for everyone, including those with disabilities. Similarly, UDL strives to design instruction that gives all students access to the general instructional method regardless of their disability status (AlRawi et. al, 2022). To promote UDL, the instructor should provide multiple means of engagement (to accommodate differences in the brain's affective networks); multiple means of representation (to address differences in recognition networks); and multiple means of action and expression (to address differences in strategic networks) (CAST, 2018). UDL interventions are instructional strategies related to these principles. For example, an instructor might promote UDL by preparing both a PowerPoint presentation and recorded lecture on the same topic - this would be considered providing multiple means of representation (Burgstahler, 2015).
Many practices in web accessibility align to the core principles of UDL and inspire inclusive course design practices. For example, the Web Content Accessibility Guidelines (WCAG) promote the use of text transcriptions whenever recorded audio is used (WCAG, n.d.). Not only does this support users with hearing difficulties, but it provides a second “means of representation” for students who simply learn better from written communications (Burgstahler, 2015). In this vein, it is reasonable to conclude that web accessibility benefits not only users with disabilities, but perhaps all users. Another WCAG guideline is to mark non-essential images, such as banners and borders, as “decorative” in the HTML so that screen-readers can skip over the image (WCAG, n.d.). In my opinion, this does not adequately provide a second means of representation. If the image is marked as “decorative,” the student who cannot see will have no idea the decoration exists because their screen-reader will skip over it. Although the decorative element may be non-essential to understanding the content, surely it enhances the document in some way, even if only by providing a pop of color in the corner of the page. A substitute for decorative elements for those who cannot see, in my opinion, is music. If instead of seeing a flash of color, the user with visual impairment hears a flash of sound, a similar message could be conveyed and perhaps the student with the visual impairment would feel that their needs were considered in the design of the instructional content. Additionally, the learner who gains better context from auditory stimuli (rather than visual stimuli) has another means of representation to go off of (Burgstahler, 2015). Again, the principles of UDL and the Web Content Accessibility Guidelines benefit not just those with disabilities, but all users.
Since accessibility practices support all users, it is worth considering the impact that web accessible course content has on students with disabilities. While the literature addresses the need for web accessibility on university websites (Alahmadi & Drew, 2017), to my knowledge there is a paucity of literature concerning the impact of web accessibility on student academic performance.
Some research supports Universal Design for Learning has had positive impacts on student performance. For example, AlRawi et. al. (2022) conducted a review of the literature on the effectiveness of UDL. They found that the UDL interventions were effective in teaching academic, behavioral, and social skills to students with intellectual disabilities (AlRawi et. al., 2022). Thus, some literature points to the efficacy of UDL instruction; however, there is a paucity of literature concerning the efficacy of web accessibility as it pertains to student academic performance.
Other research (Opitz Savi & Rowland, 2008) shows that adolescent students respond better to accessible websites, but this research does not address course materials and academic performance specifically. Collectively, there is enough evidence to suppose that accessibility may contribute to student academic performance. However, more research is needed.
The purpose of this study is to better understand how accessibility promotes the academic performance of students. Instructional designers speak of web accessibility both as an intervention strategy for students with disabilities (Coyne et. al, 2017) and an instructional design practice. Although web features that promote accessibility were initially conceived to assist users with disabilities, in my own experience they enhance the overall usability of the web for everyone. In this vein, it is possible that accessibility may promote better learning for students with disabilities as well as students without disabilities. This study will focus on a general population of students, some of which have self-reported intellectual and/or physical disabilities. If the findings show that web accessibility has a significant impact on student academic performance in general, it may further incentivize instructors to apply accessibility best practices in their coursework and digital learning spaces. Further, the study may help differentiate “web accessibility” from “usability” in the literature (WCAG, n.d.) and further contextualize discussions of diversity, equity, and inclusion in postsecondary academics.
This study will be conducted in the field. The setting is a 7-week online course consisting of participants who are undergraduate distance education students at St. Thomas University.
Name of organization and location where action research will take place: The study will take place at St. Thomas University, a private Catholic university operating in Miami Gardens, Florida.
Detailed description of the organization: The University’s mission statement reads “St. Thomas is a Catholic university with rich cultural and international diversity committed to the academic and professional success of its students who become ethical leaders in our global community” (St. Thomas University, 2024). It is the cultural and international diversity of the University that make it an ideal setting for this research, which could measure the impact of accessibility on students from many walks of life.
While the literature addresses the need for web accessibility on university websites (Alahmadi & Drew, 2017), to my knowledge there is a paucity of literature concerning the impact of web accessibility on student academic performance. Web accessibility consists of built-in features on web pages and digital documents that give users with disabilities access to the web. The Web Content Accessibility Guidelines (WCAG3), which are the leading guidelines for ensuring web-accessible content, describe ‘access’ as the ability to perceive, operate, and understand the web, and the ability for websites to communicate with assistive technologies such as screen readers (WCAG, n.d.).
The current literature nearly broaches the impact of accessibility on student academic performance, but only broadly by investigating the impacts of Universal Design for Learning (UDL).
Universal Design for Learning (UDL) is a customizable instructional planning framework that applies Universal Design (UD) principles to the affective, recognition, and strategic networks of the brain to promote learning (CAST, 2018). UD has its roots in the field of architecture, specifically on designing buildings and roads that allows access for everyone, including those with disabilities . Similarly, UDL strives to design instruction that gives all students access to the general instructional method regardless of their disability status (AlRawi et. al, 2022). To promote UDL, the instructor should provide multiple means of engagement (to accommodate differences in the brain's affective networks); multiple means of representation (to address differences in recognition networks); and multiple means of action and expression (to address differences in strategic networks) (CAST, 2018). UDL interventions are instructional strategies related to these principles. For example, an instructor might promote UDL by preparing both a PowerPoint presentation and recorded lecture on the same topic - this would be considered providing multiple means of representation (Burgstahler, 2015).
Some research supports Universal Design for Learning has had positive impacts on student performance. For example, AlRawi et. al. (2022) conducted a review of the literature on the effectiveness of UDL. They found that the UDL interventions were effective in teaching academic, behavioral, and social skills to students with intellectual disabilities (AlRawi et. al., 2022). Thus, some literature points to the efficacy of UDL instruction; however, there is a paucity of literature concerning the efficacy of web accessibility as it pertains to student performance.
Other research (Savi & Rowland, 2008) has shown that adolescent students respond better to accessible websites, but this research does not address course materials specifically.
Collectively, there is enough evidence to suppose that accessibility may contribute to student academic performance. However, more research is needed.
Participants will be recruited as volunteers and sign an informed consent. They will be assigned a participant number by a non-researcher. Then, their name will be erased from records and kept confidential.
Participants will consist of 60 diverse undergraduate students who are enrolled in St. Thomas University for the Fall 1, 2024 semester in a distance education (online) program.
The gender distribution will be 30 self-identified male and 30 self-identified female participants. Male and female participants will be split evenly among the control and experimental groups. Students who self-identify as “other” (and write in their gender identity) or “prefer not to say” will be split evenly among the control and experimental groups.
Participants will also indicate if they have an intellectual disability (ID) or physical disability (PD). They will be split among the control and experimental groups as evenly as possible according to their disability type.
Participants who “prefer not to say” will also be split evenly among the groups. Students will be asked to write in their race and will be split evenly among the control and experimental groups according to their responses. Since the point of the study is to survey the impact of web accessibility in a diverse population of students, there is no exclusion criteria as long as the demographics above are equally represented.
How does web accessibility impact student performance?
To what extent does web accessible course content promote student academic performance among a neurodiverse and culturally diverse population of undergraduate distance education students?
Group differences. I want to know if a group of diverse learners that is given accessible course materials achieves a higher mean score than one that is presented with materials that are not accessible.
Accessible course materials that have been reviewed for web accessibility compliance using AChecker, an accessibility compliance software. Course materials include Word documents, PowerPoints, YouTube videos, MP3s, MP4s, Canvas web pages, and external websites that are linked in the course. Accessibility is expressed as a percentage in each material, then an average is calculated for the control course and experimental course.
Scale of measurement:
Ratio (Percentage compliant with Web Content Accessibility Guidelines)
Student performance (grades measured in points) on level-appropriate assessments. Operational definition of assessments: Specific discussions, assignments, and quizzes that prompt students to demonstrate a module learning outcome (MLO).
Scale of measurement: Interval (measured in points).
This is a quasi-experiment. I hypothesize there will be a positive relationship between student academic performance on assessments and the accessibility score of the course they take.
The purpose of this study is to better understand how accessibility promotes the academic performance of students. Instructional designers speak of web accessibility both as an intervention strategy for students with disabilities (Coyne et. al, 2017) and an instructional design practice. Although web features that promote accessibility were initially conceived to assist users with disabilities, in my own experience they enhance the overall usability of the web for everyone. In this vein, it is possible that accessibility may promote better learning for students with disabilities as well as students without disabilities. This study will focus on a general population of students, some of which have self-reported intellectual and/or physical disabilities. If the findings show that web accessibility has a significant impact on student academic performance in general, it may further incentivize instructors to apply accessibility best practices in their coursework and digital learning spaces. Further, the study may help differentiate “web accessibility” from “usability” in the literature and further contextualize the conversation surrounding equity in postsecondary academics.
This quasi-experimental study follows a nonequivalent control group design. The control and experimental groups will not be assigned totally at random, to ensure a demographic balance of intellectual diversity, race, gender, etc. in both groups to increase internal validity of results (Patten & Newhart, 2018). The diagram below represents the nonequivalent control group design:
————————
0 X 0
------------------------
0 0
————————
The dashed line represents that the groups are not assigned at random (Patten & Newhart, 2018). Threats include mortality, selection, and interaction of selection, and history. (Patten & Newhart, 2018). However, this research study is more interested in the internal validity of results thus it is necessary to assign the groups.
The literature surfaced only a few previous studies that addressed the impact of web accessibility on user performance. Opitz Savi, et. al (2008) recorded the “navigational effectiveness” and “response accuracy” of accessible websites, then assigned users randomly to a control (non-accessible) and experimental (accessible) group. This study used a two (accessible vs. non-accessible) by two (students with learning disabilities vs. students without learning disabilities) factorial design (Opitz Savi et. al, 2008). Responses were analyzed using MANOVA.
Instead, my study will use a different approach:
In my study, instruments will include:
The courses will be reviewed for the accessibility scores using AChecker, an accessibility compliance software. Both courses will have the same course content. The AChecker software will rate the courses based on their compliance with the Web Content Accessibility Guidelines (WCAG3).
The final grades (expressed in percentages) will be recorded after the course completes.
To analyze the data, I will calculate the mean, median, mode, range, and standard deviation for the independent and dependent variables as indicated below.
Student performance (grades measured in points) on level-appropriate assessments. Operational definition of assessments: Specific discussions, assignments, and quizzes that prompt students to demonstrate a module learning outcome (MLO).
I will then use a T-test to determine if there is a significant relationship between the two variables - the mean course performance score and the mean accessibility compliance score (Patten & Newhart, 2018).
The T-test is the best option because it will help me determine the relationship between course performance and accessibility compliance score.
Hypothesis: There is a significant relationship between the students’ final grades and the accessibility compliance score of the course.
Null Hypothesis: There is no relationship between the students’ final grades and the accessibility compliance score of the course.
I will record the T-test in Excel. Excel will calculate the p-value (Roger Williams University, n.d.).
Academic Performance: The final grade (expressed as a percentage) a student earns in a course.
Accessibility Compliance Score: The percentage a webpage, website, or digital content complies with the Web Content Accessibility Guidelines (Alahmadi & Drew, 2017).
Accessibility Compliance Software: A type of software, such as AChecker, that scans and scores web pages based on their compliance with the Web Content Accessibility Guidelines. (Alahmadi & Drew, 2017).
AChecker: The accessibility compliance software used in this study. It scans and scores web pages based on their compliance with the Web Accessibility Content Guidelines.
Control Group: In my study, the control group is a group of distance education students taking an online course in which the course materials (such as assessments, discussions, PDFs, Word Documents, PowerPoints) receive below a 30% accessibility compliance score from AChecker.
Distance Education (DE): Learning taking place entirely on the web, through a Learning Management System (LMS). The LMS used in this study is Canvas.
Experimental Group: The experimental group is a group of distance education students taking a course in which the course materials (such as assessments, discussions, PDFs, Wod Documents, PowerPoints) receive between a 90-99% accessibility compliance score from AChcker.
Instructional Design: A discipline involving the construction of educational materials (my own definition.)
Intellectual Disability (ID): “A disability characterized by significant limitations in both intellectual functioning and adaptive behavior as expressed in conceptual, social, and practical skills. This disability originates during the developmental period, which is defined operationally as before the individual attains age 22” (Schalock et. al, 2021).
Module Learning Outcome (MLO): What the student should be able to do by the end of the module (week) in a course. Typically, this is what they will demonstrate in an assessment (written assignment, discussion, presentation, or other learning activity.)
Neurodiverse: Describes a population that represents a range of intellectual abilities.
Non-Equivalent Control Group Design: A quasi-experimental design in which the control group is not randomly selected (Patten & Newhart, 2018).
Quasi-Experiment: An experimental design used to explore cause-and-effect relationships. (Patten & Newhart, 2018).
St. Thomas University: A private Catholic University located in Miami Gardens, Florida.
T-test: A statistical analysis that determines if there is a significant relationship between two variables (Patten & Newhart, 2018).
Universal Design for Learning: A customizable framework that encourages instructors to provide options for students, so as to accommodate a range of ability related to the brain’s affective, recognition, and strategic networks (CAST, 2018).
Web Accessibility: The degree to which digital content can be accessed by users with disabilities (Alahmadi & Drew, 2017).
Web Content Accessibility Guidelines 3 (WCAG 3): International web standards that ensure the perceivability, operability, understandability, and robustness of web pages for users with varying degrees of physical and intellectual disabilities. Developed by the World Wide Web Consortium (WCAG, n.d.).
Web accessibility is an important issue facing institutions of higher education. The growing number of students with intellectual disabilities (Alahmadi & Drew, 2017), particularly in distance education settings, sheds light on the need for accessible course materials in digital learning spaces. Accessibility practices may be challenging to implement in the classroom and lecture hall due to the lack of accessibility training provided to instructors. AlRawi & Alkahtani (2022) synthesize this into the claim “teachers are not ready to include students with disabilities, even if they are included in the classrooms.” Thus, there is a pressing need to compel instructors to implement web accessibility into their classrooms.
In combination with training, the notion that accessible digital content promotes academic performance in all students (not only those with disabilities) may compel college instructors to take on the ambitious task of revising course content according to best practices in instructional design.
Thus, this research study attempts to answer the question: To what extent does web accessible course content promote student academic performance among a neurodiverse and culturally diverse population of undergraduate distance education students?
A positive relationship between accessible course content and academic performance may reinforce the notion that accessibility helps everyone. In addition, it may be good evidence that the Universal Design for Learning - which suggests that instructors plan for various learning styles and intellectual differences when designing their instruction (CAST, 2018) - is an instructional design best practice.
Alahmadi, T., & Drew, S. (2017). Accessibility evaluation of top-ranking university websites in world, Oceania, and Arab categories for home, admission, and course description webpages. Journal of Open, Flexible and Distance Learning, 21(1), [7–24.].
AlRawi, J. M., & AlKahtani, M. A. (2022). Universal design for learning for educating students with intellectual disabilities: a systematic review. International Journal of Developmental Disabilities, 68(6), 800–808. https://doi.org/10.1080/20473869.2021.1900505
BMJ. (2024). Chi-squared tests. In Statistics at Square One. BMJ. https://www.bmj.com/aboutbmj/resources-readers/publications/statistics-square-one/8-chi-squared-tests
Burgstahler, S. (2015). Universal Design in Higher Education: From Principles to Practice. Harvard Education Press.
Cao, S., & Loiacono, E. (2022). Perceptions of web accessibility guidelines by student website and app developers. Behaviour & Information Technology, 41(12), 2616–2634. https://doi.org/10.1080/0144929X.2021.1940278
CAST (2018). Universal Design for Learning Guidelines version 2.2. CAST. http://udlguidelines.cast.org
Coyne, P., Pisha, B., Dalton, B., Zeph, L. A., & Smith, N. C. (2012). Literacy by Design: A Universal Design for Learning Approach for Students With Significant Intellectual Disabilities. Remedial and Special Education, 33(3), 162-172. https://doi.org/10.1177/0741932510381651
Fennelly-Atkinson, R., LaPrairie, K. N., & Song, D. (2022). Identifying Accessibility Factors Affecting Learner Inclusion in Online University Programs. Distance Education, 43(4), 556–573. doi.org10.108001587919.2022.2141607.
Opitz Savi, C., Savenye, W., & Rowland, C. (2008). The effects of implementing web accessibility standards on the success of secondary adolescents. Journal of Educational Multimedia and Hypermedia, 17(3), 333-356. Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/p/25272/
Patten, M. L., & Newhart, M. (2018). Understanding research methods: An overview of the essentials (10th ed.). Routledge.
Rehabilitation Act of 1973, 29 U.S.C. § 701 (1973).
Roger Williams University. (n.d.). Running a t-test in Excel. https://www.rwu.edu/downloads/fcas/mns
Schalock, R. L., Luckasson, R., & Tassé, M. J. (2021). Twenty questions and answers regarding the 12th edition of the AAIDD manual: Intellectual disability: Definition, diagnosis, classification, and systems of supports. American Association on Intellectual and Developmental Disabilities.
St. Thomas University. (n.d.). Home. St. Thomas University. https://www.stu.edu
Web Content Accessibility Guidelines (WCAG). (n.d.). What is WCAG? https://wcag.com/resource/what-is-wcag/
.jpg)
The article explores how Universal Design for Learning (UDL) and artificial intelligence (AI) can work together to create inclusive, data-informed instructional design.
Read more
By supporting belongingness, attachment with peers, and connectedness in online learning spaces, course designers can shift instruction from impersonal to transformational.
Read more