Identifying accessibility factors affecting learner inclusion in online university programs

Abstract

As postsecondary online programs increase, the accessibility of online course content becomes a serious issue in higher education. There is currently little information about how postsecondary institutions address online course accessibility. This exploratory mixed-methods study examined the degree to which university online course checklists represent accessibility criteria and which criteria were most and least represented in university checklists. Further, this study also examined the relationship between several university factors. This review of university online course checklists against the Web Content Accessibility Guidelines criteria revealed some areas that may warrant closer inspection for researchers and universities. Results indicated that online program enrollment was linked with how the university handled accessibility compliance and how they trained faculty regarding online course accessibility. These findings have implications for how learner inclusion in online programs can be impacted at the university level.

Keywords:

• online education
• accessibility
• course design
• students with disabilities
• inclusion

Disclosure statement

No potential conflict of interest was declared by the authors.

Additional information

Notes on contributors

Rita Fennelly-Atkinson

Rita Fennelly-Atkinson is an adjunct professor at Sam Houston State University and the Director of Micro-credentials at Digital Promise. She identifies as disabled and has worked at the intersection of education and technology to create inclusive and accessible learning environments for learners for the past 20 years.

Kimberly N. LaPrairie

Kimberly N. LaPrairie is the director of the Instructional Systems Design and Technology doctoral program at Sam Houston State University. She has over 20 years of education experience focusing on technology integration to improve educational and training systems in organizational settings, instructor effectiveness, and content accessibility.

Donggil Song

Donggil Song is an associate professor of engineering technology & industrial distribution, College of Engineering at Texas A&M University. His research lab focuses on artificial intelligence engineering for human learning, human-centered artificial intelligence, and machine learning–based mixed-reality artificial intelligence systems.