Updates to Digital Accessibility Regulations

You may have heard that recently, there have been updates to regulations implementing Title II of the American with Disabilities Act (ADA). These updates impact almost all of what we do in the online learning environment. With the aim of reducing burden for members of the disability community and providing equitable access to web content, the updates introduce technical guidelines that large public universities such as U-M must adhere to starting on April 24, 2026. We’ll discuss this further, and some exceptions to the rule, below.

Prohibiting Discrimination in Digital Spaces

The ADA is a civil rights law which blanketly prohibits discrimination on the basis of disability. More specifically, Title II of the ADA extends the prohibition of discrimination on the basis of having a disability to services, programs, and activities of state and local government entities, which includes public universities. In April 2024, rulemaking by the Department of Justice updated Title II regulations (added as a new subpart H to 28 CFR 35) by establishing specific technical standards to help ensure that all web and mobile applications are accessible.

Prior to this update, web content under Title II was required to be accessible, but public entities did not have specific direction on how to comply with ADA’s general requirements of nondiscrimination. Many organizations noted that voluntary compliance with previous digital accessibility guidelines did not result in equal access for people with disabilities. With the new guidelines in place, people with disabilities will now have equal access to all web-based content created by state or government institutions.

This is important progress for removing barriers to access in our very web-based world. Universities have become increasingly reliant on technology, whether for learning, working, or for transactions. With more than 10 millions students enrolled in some form of distance education, ensuring all students have equitable access to the same information, are able to engage in the same interaction, and can conduct the same transactions as their nondisabled peers is critical. As online learning continues to grow, it is important to remember that more than 1 in 4 people in the US have disabilities, this includes an estimated 13.9% US adults with a cognitive disability impacting their concentration, memory, or decision making, 6.2% with a vision disability, and 5.5% with a hearing disability.
This is not a solution in search of a problem; individuals with disabilities are consistently reporting challenges when accessing the web. The U.S. Department of Education’s Office for Civil Rights (OCR) noted that they have resolved and monitored more than 1,000 cases, reported by members of the public, in recent years related to digital access. These complaints addressed the accessibility of many facets of the web: public-facing websites, learning management systems, password-protected student-facing content, and mass email blasts of colleges and universities, to name a few.

Technical Standards: WCAG 2.1, Level AA

Web content is defined as the information and experiences on the web, and it now must be readily accessible and usable to those with disabilities. This includes text, images, social media, sound, videos, scheduling tools, maps, calendars, payment systems, reservation systems, documents, etc. This also applies to web content that was made by a contractor or vendor. Universities may no longer rely on alternative versions or other workarounds to address barriers to inaccessible digital content or a reactive response when a student requests accommodations.

The technical standards themselves, WCAG 2.1, Level AA, are an international set of standards developed by the Web Accessibility Initiative (WAI) of the W3C, the World Wide Web Consortium, an organization that sets standards for web design. Generally speaking, they set clearly defined standards for content so that it is perceivable, operable, understandable, and robust.

Though this is a new technical standard that all public universities must adhere to, the practice of producing and maintaining accessible content isn’t new at U-M. Since anyone at U-M can create digital content, our digital accessibility Standard Practice Guide Policy, deployed in 2022, states that any U-M developed or maintained electronic information technology (EIT) must meet the same technical standards required in updated Title II regulations. This is to ensure that these technologies are as effective, available, and usable for individuals with disabilities as those who do not have disabilities. This applies to a wide range of technologies, from web-based applications, to digital textbooks, to electronic documents. Individual U-M units are responsible for maintaining the accessibility, usability, and equity of their EIT over time, in collaboration with other U-M units.

Limited Exceptions to the Ruling

If we build our content accessible, adhering to these guidelines, we are greatly reducing the chances that an individual with a disability is unable to access our content. Similarly to a curb cut in a sidewalk, not only can a person with a wheelchair access the street or sidewalk, but so can bicyclists and strollers. This concept applies to web content as well:If we build accessible web content, everyone can benefit. Given this, there are very few, limited exceptions to WCAG 2.1, AA conformance requirements that are further explained in the Fact Sheet: New Rule on the Accessibility of Web Content and Mobile Apps Provided by State and Local Governments. Note: please defer to guidance from your university for interpretations of these exceptions. In summary, some exceptions that come up in your teaching include:

Archived web content:
Oftentimes, there is web content that is not currently used as it’s outdated, not needed, or repeated somewhere else. If the content was created before the compliance date, only kept for reference/recordkeeping, is held in a special area for archived content, and it has not been changed since it was archived, then it would not need to meet WCAG 2.1 Level AA. An example could include a 2019 report on the enrollment data for an online degree program that hasn’t been updated and is stored in an “archived” section of a website.
Content posted by a third party:
When a third party, which is not posting due to contractual arrangements with the university, posts content on a university website or mobile app, these standards likely do not apply. For example, if a student comments on a discussion board within your course, it will probably fall under this exception.
Preexisting conventional documents:
These documents, such as old PDFs, word processing documents, spreadsheets, or presentations, that were made available prior to the ruling date AND are not currently being used An example could include a PDF for a research symposium event in 2022 that was still posted on the university’s website.

Other exceptions include password protected documents for a specific individual and preexisting social media posts made prior to the compliance date.

Common Questions

What if a student reports they cannot access my web content, despite WCAG 2.1, Level AA conformance?

This is definitely possible, as every person’s needs are different. One wouldn’t have to change their web content in this case, but would need to provide an equivalent alternative to that individual.

Can we just depend on a learner’s accommodation request?

This is considered an undue burden to a person with a disability by having them constantly request access to web content as resolutions to requests could take several days or weeks to comply. By designing web content to be accessible upon its creation, individuals with disabilities will have an equal opportunity to access content.

Are there resources and trainings available to learn more about digital accessibility that are tailored for instructional faculty?

At U-M, there are many opportunities to learn about a variety of accessibility topics, including those relevant to faculty, found on the Accessibility Training page maintained by ITS and ECRT. Additionally, there are many great resources available to increase the accessibility of your web content including:

The Roundup on Research series is intended for faculty and staff who are interested in learning more about the theories, frameworks, and research in online and technology-enhanced teaching and learning.

If you have been anywhere where teaching is involved, you have probably heard mention of “learning styles.” “I’m a visual learner” vs. “I’m a hands-on learner” or “My instructor didn’t teach in my learning style” are all the types of commentary that are common when some individuals talk about their own learning. Although it is deeply appealing to be able to categorize individuals into easy methods of learning, unfortunately, it is deeply flawed, has little empirical evidence to support it, and might cause more problems than it solves.

What are Learning Styles?

To best understand why learning styles are problematic, it is important to clearly define learning styles. The idea of learning styles is that there are stable, consistent methods that individuals take in, organize, process, and remember information, and by teaching those methods, students learn better.

One popular concept in learning styles posits that the modality of information is critical – a “visual” learner learns best by seeing versus an “auditory” learner who learns best by having things spoken or described to them. Learning style theory would suggest that by using visual aids, a visual learner would organize and retain information better than say, an auditory learner. The implication is that matching modality information to the modality of learning style is critical to student success.

A note: there are additional and related concepts of “cognitive styles,” “learning strategies,” and “learner preferences” that can sometimes be used interchangeably with “learning styles.” For this article, “learning styles” refers specifically to the theory that there are ways that individuals learn best. In contrast, learning preferences suggest that there are ways people prefer to receive information, but it may not impact learning.

At face value, the concept of learning styles makes sense. Individuals learn differently. Most educational settings are trying to reach large numbers of students in personalized ways. It would be useful to have an easily applied theory that would help all students learn! As educators, we want to recognize the “uniqueness” of each student and help learners in any way we can. This desire has led educators to look for easier ways to navigate the complexities of teaching. Unfortunately, learning is not that simple.

Do Learning Styles Really Exist?

In general, most learning style theories make two presumptions:

Individuals have a measurable and consistent “style” of learning, and
Teaching to that style of learning will lead to better education outcomes, and conversely, teaching in a contradictory method would decrease achievement.

In other words, if you are a visual learner, you should learn best if you see things, regardless of the situation. If you are a kinesthetic learner, you will learn best if you can physically manipulate something, regardless of the topic. However, neither of these two assumptions shows any grounding in research. These two propositions are where we can see the concept of learning styles breaking down.

Are Learning Styles Measurable and Consistent?

Did you know that there are actually over 50 different theories of learning styles by various researchers? Researchers have been trying for years to find a correlation between individuals and how to help learning. Some theories suggest the modality of learning matters (like the common VARK theory) while others propose details like time of day and temperature of the room define a learning style. One study that suggested using a cell phone was a learning style (Pursell, 2009). Just the number of different styles makes it difficult to measure and make sense of an individual style.

In addition, most learning style inventories rely on a student’s self-report about how they perceive they learn best. These self-reports are generally not validated in any way. Generally, humans tend to be poor judges of our own learning. Therefore, these surveys are generally measuring “learner preference” rather than “learning style.” You may think you are an auditory learner but until it is validated that you objectively learn better through audio format, it is a preference, not a style.

Also, when reporting results, many studies will rely on “student satisfaction” as a measure of success, or rely on students’ reflections as a measure of success in a class. For example, many measures of learning styles will ask students how they believe they learn best. Unfortunately, satisfaction with a class or a student’s recollections of success are subjective measures, and generally not accurate (Kirschner & van Merriënboer, 2013, Kirschner, 2017). While understanding a learner’s preference is useful as is understanding student satisfaction with a lesson, it does not have the same weight as necessitating teaching to that preference.

Finally, ”styles” are unstable and unreliable. The research on learning styles has suggested that these preferences may be unstable – they be topic-specific, but they also change over time (Coffield et al., 2004). That means that although an individual may be a kinesthetic learner in history this week, that person is a visual learner in math when talking about calculus (but not about geometry), or prefers to learn how to ride a bike kinesthetically instead of reading about it in a book. This questions whether a learning style is a “trait” (or something stable and persisting for a person) or a “state” (something that is temporary and may change). Learning styles as a state of mind are not particularly useful. How can a teacher know the preference of an individual student today in a given subject?

Does Teaching a Learning Style Result in Better Learning?

Even more importantly, however, is the second assumption – does teaching to an individual’s learning style lead to achievement? Simply put, there is no evidence that supports teaching to a person’s specified learning style results in better learning (Alley, et. al., 2023; Cuevas, 2015; Kirschner & van Merriënboer, 2013; Krätzig & Arbuthnott, 2006; Pashler et al., 2008; Rogowsky et al., 2020). No study has shown that teaching to an identified learning style results in better retention, better learning outcomes or student success. Instead, we see that teaching to a self-identified learning style has no impact on learning in children or adults (Krätzig & Arbuthnott, 2006; Paschler et al., 2008; Rogowsky et al., 2015, Rogowsky et al., 2020). Some research suggests that some students performed better on tasks when taught in a different modality than their self-identified “learning style” (Krätzig & Arbuthnott, 2006, Rogowsky et al., 2020). Most studies of learning styles use a methodology that uses multiple styles to all learners – meaning that there is no way to isolate learning style to teaching method. This leads us to ultimately conclude that while the concept of learning styles is appealing, at this point, it is still a myth.

Alternate Explanations to Learning Styles

Anecdotally, there are many stories about the success of leveraging “learning styles.” If learning styles are not empirically supported, how are these successes explained? There are alternative explanations for why teaching in multiple methods increases achievement that do not prescribe students into style categories. Multi-modal learning explains how learning improves with various methods of teaching.

Learning requires sustained attention. Therefore, if an educator can capture and maintain students’ attention, students’ learning outcomes likely improve. Providing engagement with content in multiple forms – be it through hands-on activities, or different modalities – makes students pay attention to content in different ways, and requires learners to integrate knowledge in new ways. If an educator is using multiple methods and modalities, it’s just more interesting, and students pay more attention, which leads to better learning. Mayer and colleagues (2001, 2003) have extensively studied how students learn with visuals and audio, and the interaction of the two. What he and his colleagues suggest is that by providing dual streams of information in multiple methods engages learners to work harder at understanding the material, which leads to better learning. It may be that the research on learning styles is actually showing that teaching with different modalities is just more interesting to students rather than catering to a particular style of learning (Krätzig & Arbuthnott, 2006).

Why Learning Styles are Dangerous

While the intentions of learning styles are good, the implications of learning styles are more destructive than helpful. On the positive side, reflecting on how one learns is always a lesson. However, by focusing on a style suggests that learners are passive vessels at the whim of the method of teaching. Ultimately, most educators want students to actively engage in their learning. The best learning takes place when an individual can connect and incorporate information into his or her personal experiences and understanding. By focusing on a student’s learning style we reinforce a simplistic view of learning. Learning styles suggest that individuals have one way to learn best. Unfortunately, learning is complex, and not easy. This is hard and takes time! It has very little to do with the way information is handed to a learner, but rather, how the learner processes that knowledge once they have it. It is important to remember – learning is within the control of the learner.

Thinking Critically About Learning Styles

If learning styles do not impact an individual’s ability to learn, why is there so much talk about them? Articles and books are still being published about learning styles and how to tailor teaching to reach every style. Research on teaching and learning is a complicated discipline, and being able to examine theories and concepts like learning styles critically is important to anyone working in education. The challenge is to keep a skeptical eye when you hear about research supporting learning styles and ask the right questions to make sure you are getting good information.

What Should you Think About the Next Time you Encounter Learning Styles in the Wild?

What framework of learning styles are they referring to? Some are more empirically vetted than others. The most popular learning style VARK (Visual-Auditory-Read/Write-Kinesthetic) is also the least validated. Find out more about the learning style being discussed.
How are they measuring both learning style and success? Are they self-reported? Are they looking at academic results or a self-report of satisfaction with learning?
Is the study carefully controlled? Many studies fail to tailor the learning to a particular style. Rather, the lesson uses all the styles to reach all the students. There is no way to truly measure success.
Learning styles can be controversial with some people. They aren’t necessarily harmful if they encourage people to reflect on teaching and learning in different ways. They can be harmful if students believe that their learning is outside their control.

References

Alley, S., Plotnikoff, R. C., Duncan, M. J., Short, C. E., Mummery, K., To, Q. G., Schoeppe, S., Rebar, A., & Vandelanotte, C. (2023). Does matching a personally tailored physical activity intervention to participants’ learning style improve intervention effectiveness and engagement? Journal of Health Psychology, 28(10), 889–899.

Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Should we be using learning styles? What research has to say to practice: Learning & Skills Research Center.

Cuevas, J. (2015). Is learning styles-based instruction effective? A comprehensive analysis of recent research on learning styles. Theory and Research in Education, 13(3), 308–333.

Kirschner, P. A. (2017). Stop propagating the learning styles myth. Computers & Education, 106, 166–171.

Kirschner, P. A., & van Merriënboer, J. J. G. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 169–183.

Krätzig, G. P., & Arbuthnott, K. D. (2006). Perceptual learning style and learning proficiency: A test of the hypothesis. Journal of Educational Psychology, 98(1), 238–246.

Lau, W. & Yuen, A. (2009). Exploring the effects of gender and learning styles on computer programming performance: Implications for programming pedagogy. British Journal of Educational Technology. 40(4), 696-712

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43-52.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.

Pursell, D. P. (2009) Adapting to student learning styles: Engaging students with cell phone technology in organic chemistry. Journal of Chemical Education. 86(10), p1219-1222.

Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2015). Matching learning style to instructional method: Effects on comprehension. Journal of Educational Psychology, 107(1), 64–78.

Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2020). Providing Instruction Based on Students’ Learning Style Preferences Does Not Improve Learning. Frontiers in Psychology, 11.

It is safe to say that by now, you have seen many articles/posts, opinions, and stories about ChatGPT—and the larger AI-Language Learning Models (LLMs)—in relation to higher education and teaching/learning in particular. These writings included several perspectives ranging from raising concerns to celebrating new opportunities and a mix of the former and the latter. Also, these writings continue to evolve and grow rapidly in number as new AI-powered LLMs continue to emerge and evolve (e.g., Google’s new AI LLMs: Bard).

The intent of this piece is not to add another article sharing tips or concerns about ChatGPT. That being said, this article (1) summarizes the major concerns about ChatGPT and (2) the ideas about its positive implications based on what it is published to date.

Concerns about ChatGPT

Faculty, scholars, and higher education leaders have raised several concerns about ChatGPT. These concerns stem from possible ways it can be used.

Using ChatGPT to cheat by asking it to write essays/answer open-ended questions in exams/discussion forums and homework assignments (December 19th, 2022 NPR Story) (December 6th, 2022 Atlantic Story) (January 16 New York Times Story).
Using ChatGPT to author scholarly works which conflict with the ethical standards of scientific inquiry. Several high-impact/profile journals have already formulated principles to guide authors on how to use LLMs AI tools and why it is not allowed to credit such tool as an author—any attribution of authorship carries with it accountability for the scholarly work, and no AI tool can take such responsibility (January 24th, 2023 Nature Editorial).
ChatGPT can threaten the privacy of students/faculty (and any other user). Its privacy policy states that data can be shared with third-party vendors, law enforcement, affiliates, and other users. Also, while one can delete their ChatGPT account, the prompts they entered into ChatGPT cannot be deleted. This setup threatens sensitive or controversial topics as this data cannot be removed (January 2023 Publication by Dr. Torrey Trust).
ChatGPT is not always trustworthy, as it can fabricate quotes and references. In an experiment conducted by Dr. Daniel Hickey at Indiana University Bloomington, Instructional Systems Technology department, “ChatGPT was able to write a marginally acceptable literature review paper, but fabricated some quotes and references. With more work such as including paper abstracts in the prompts, GPT is scarily good at referencing research literature, perhaps as well as a first-year graduate student.” (January 6th, 2023, Article by Dr. Daniel Hickey)

Excitement about ChatGPT

At the other end of the spectrum, there have been several ideas that express interest and excitement about ChatGPT in higher education. These ideas stem from how they can be used ethically and in a controlled manner.

Using ChatGPT to speed up the writing of drafts for several outlets (reports, abstracts, emails, conference proposals, press releases, recommendation letters, etc.) ChatGPT can produce elaborated writing that must be edited to remove any possible inconsistencies or inaccuracies (December 7th, 2022 Social Science Space story)
Using ChatGPT in the process of brainstorming ideas for curriculum design, lesson planning, and learning activities. The tool can provide some novel ideas or remind educators of some instructional techniques and strategies that they had heard about in the past (January 23rd, 2023, Article by Dr. David Wiley).
Using ChatGPT to provide students tutoring/scaffolds. The tool can act like a virtual tutor who does not simply give the answer to the student but rather scaffold them to reach the correct answers by themselves. (Sal Khan, founder/CEO of Khan Academy, Spring 2023 TED Talk)
Teaching with ChatGPT to train students on using AI tools and models, provide opportunities to exercise critical thinking skills, and improve their technological literacy (January 12th New York Times story).

Concluding Thoughts

There are major concerns about ChatGPT and the larger AI-powered Language Learning Models (LLMs) phenomenon. These concerns are legitimate and are opposed by notable ideas about the positive implications of AI-powered LLMs in higher education classrooms. As we aspire to make evidence-based educational and learning design decisions, one should carefully review the research that has been done on AI in relation to higher education up to this point and engage with the gaps as opportunities to expand knowledge and find new opportunities and risks.

Our University’s newly formed advisory committee on the applications of generative AI is a good example of how higher education institutions ought to recommend the use, evaluation, and development of emergent AI tools and services. Additionally, discussions about generative AI and its implications on education happening in public venues are necessary to strengthen the public-facing mission of the University, where input from educators, students, and members of the community is welcome.