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Learner Stories: Preparing for a Life in Healthcare

A student named Zafina, age 7, filled out a worksheet. She writes that she swam this summer and had a lot of fun. Her favorite things include playing piano, steak, the color red, and she wants to be a doctor. She drew a picture of swimming with yellow ducks.

Canadian teen’s career ambition sparked by Michigan Online course

Zafina Zaman, a 15-year-old high school student in Alberta, Canada, has wanted to be a doctor for as long as she can remember.

A young girl holds a book titled Children's First Book of Human Body.

“I really want to go into medicine,” she said. “The funny thing is that when you’re a little kid you tell your parents ‘I want to be a princess or I want to be a fire truck,’ but even when I was 4, I’ve always said I wanted to be a doctor.” 

One of Zafina’s earliest memories was when her mother had a cold and was sick in bed. With her father at work, she decided to try and make tea, warming water and honey in the microwave (which she was not allowed to use).  

“Later [my mom] talked to the doctor, and they told her to do exactly what I did for her,” Zafina said. “That was fireworks in my 4-year-old brain. Oh my gosh!”

With the support of her family, Zafina has been able to pursue her passion for learning and healthcare despite her youth. 

A Massive Love of Learning

While searching for ways to supplement her education, Zafina discovered her first massive open online course, or MOOC. The flexible timing of the course, “Sleep: Neurobiology, Medicine, and Society,” worked for Zafina and she completed the 12 modules over her summer break.

“They didn’t refuse me for being in middle school,” she said. “I wanted to know more about everything, and I thought, why not?”  

Zafina loved learning more about how the brain works in everyday life. “There is so much that goes behind taking a step, that one movement. It was just eye-opening to be able to see that,” she said. “The human body — how and why things work the way they do — it’s so fascinating!” 

She elected to take the optional honors track for the course, which gave her something to work toward and turned out to be motivating. The honors track option showed up on the certificate she earned upon completing the course, giving Zafina the chance to show others what she accomplished as well as perhaps inspire others to take advantage of these classes at no cost. 

“They’re not age restricted. You don’t have to be a certain age or a certain grade level or have a Ph.D. to take these courses,” she said. “They’re free to anybody and everybody. Why not take them?” 

Success on the honors track helped give Zafina the confidence to try other MOOCs, helping keep her brain occupied when the COVID-19 pandemic shut down much of traditional education. She took two more Coursera courses, “Understanding the Brain: The Neurobiology of Everyday Life” and “Medical Terminology,” which fed her fascination with how the body and the brain work and how we are able to do the things we do.  

MOOC Certificate Leads to Hands-On Experience

Once she had some health-related courses under her belt, Zafina added them to her resume and LinkedIn profile, which helped earn her a volunteer position with a local health clinic. 

As a volunteer, Zafina helps with administrative work at the front desk and books patients. She recently gained the opportunity to triage a bit, such as taking blood pressure, height, weight, and settling patients into rooms.

“My favorite thing to do is shadowing the doctors because I’m able to connect textbook studies with actual hands-on experience, and that’s been so much fun!” Zafina said. “I’ve been working there for a while now, about a year, and it’s an amazing experience. I’m so grateful I’ve had this opportunity.”

Although there are difficult and awkward moments, the time is rewarding.

“I’ve always really enjoyed helping people. They call it helpers high,” she said. “I love the feeling of being able to see when you help make a change in someone’s life, a feeling of importance and being able to see the changes that you make.”  

Thanks to the staff at the clinic who she says take time out of their day to help guide her, Zafina is gaining hands-on experience in the world of healthcare before learning to drive.

Family Matters

In addition to her interests in healthcare, Zafina also competes as a motivational speaker with Optimist International, a platform for youth to compete in public speaking. 

She’s been competing since she was 8 and has been the youngest contestant during each level. At 13 she competed against high school students to earn a spot representing Canada and the Great Plains Region in the 2022 Oratorical World Championships, still the youngest person to compete in Optimist International history. 

A young girl in a teal dress and an older woman in a silver top hold hands across a table, both gazing upward with intense expressions. Other people are seated in the background, focused downward.
Zafina Zaman, the Great Plains Regional winner, holds hands with her mom, Farheen Akbar, as they await final results at the 2022 Optimist International Oratorical World Championships. Photo by Josh Castleberry, Optimist International

Zafina feels extremely grateful to her family for their support – driving her to a local university for an anatomy class, cheering her on in competitions, and encouraging her to pursue her interest in healthcare despite her age.  

From taking care of her mother at age 4, through dressing up as a doctor for Halloween at age 9, and now considering her college plans, Zafina has never wavered from her desire to pursue healthcare. Even though she struggled through chemistry and needed to persistently work at it, the reward of learning and one day becoming a doctor makes the work worthwhile.  

Zafina attributes her successes to her family and the wonderful opportunities that have allowed her to accomplish as much as she has despite her youth. With support at home and her internal ambition, Zafina remains as committed to her goal as she was at just 4  years old.

“It’s never been anything else,” she said. “It’s always been a natural field for me.”

Take the next step toward online teaching

Ready to inspire and inform learners around the world? You can learn more about online teaching and creating an online course through the Guides section of our website. The Center for Academic Innovation can help facilitate your transition to online teaching, either through our many resources or in a potential partnership.

Panorama tool offers easy, accurate remediation within Canvas

How this will help

Built-in tool can identify and fix accessibility issues
Checks that course materials meet federally mandated standards
Helps instructors design equitable lessons for all learners

Reviewing your course materials in Canvas for accessibility ensures all learners can participate without obstacles. As the importance of digital accessibility is demonstrated, the tools available to meet those requirements are more prevalent, accurate, and easier to use. 

Panorama is one such tool and is currently available on Canvas. It can scan, evaluate, and fix content directly within the learning management system. Using automatic scripts and machine learning, Panorama reviews course materials and matches them to accessibility standards for color contrast, text, graphics, tables, and other issues that can pose barriers to learning for students with disabilities. 

Like many major accessibility checkers, Panorama is built around Web Content Accessibility Guidelines, or WCAG (commonly referred to as WICK-ag), which are considered the universal standard for digital accessibility. The University of Michigan’s Digital Accessibility Strategic Initiative aims to meet WCAG and Americans with Disabilities Act (ADA) regulations by April 2026. 

Getting Started

Panorama automatically audits all of the items in the course and checks their compliance with the prescribed accessibility standards. 

Once Panorama scans every Canvas course for accessibility issues, and there are several ways to access those results and start making corrections.

Accessibility scores are also found next to each item in your course materials. Those scores appear in three colors: 

Three icons indicate accessibility levels: a red warning icon for scores below 60%, a yellow caution icon for scores between 60–90%, and a green proceed icon for scores above 90%.
  • Red – Warning icon. This indicates significant accessibility issues with this item.
  • Yellow – Caution icon. There are some issues that may be difficult for learners to navigate.
  • Green – Proceed icon. This means the item meets or mostly meets accessibility criteria, which is the ultimate goal for mandated requirements.

You can see the accessibility report for that item when you click on the accompanying icon. Instructors and designers can also open a full course report by selecting Panorama from the left-side navigation menu in your course. It should be noted that these scores are not accessible by students; they are solely to inform you as instructors or designers.

Full course reports give you a snapshot of a course’s overall accessibility and a complete list of items with their accompanying score. From this list, you can prioritize the remediation as issues are filtered by severity or content type, so you can rank the findings accordingly. 

If you are creating pages in Canvas, the Panorama accessibility tool icon, which looks like a temperature gauge, appears underneath the text box. As content is added, any accessibility issues appear as a numeric count on the icon. Clicking it opens a report where you can review a list of all accessibility issues Panorama has discovered.

A screenshot outlines three ways to access an accessibility report for a specific item. The first method is through the Rich Text Editor, shown with a gray gauge icon and a purple badge marked “1.” The second method is via the Accessibility Score Icon next to a page or file, represented by three icons: a red pentagon, a yellow triangle, and a green hexagon, each with a human figure inside. The third method is from the Accessibility Score Icon beside issues in the Course Report, illustrated with a gray gauge icon labeled “70%” in orange text.

Making Corrections

Panorama allows course designers and instructors to create, scan, and fix digital content directly in the Canvas platform.

The most common issues flagged include:

The Accessibility Report featured displays a total of 19 issues with a 0% accessibility score, categorized as 4 minor, 15 major, and 0 severe issues. Below, the "Review Issues" section lists specific problems: 1) A major issue stating "The slide does not have a title," with a "Learn more" link. 2) A minor issue about "Check reading order," accompanied by a "Learn more" link and a "Fix Issue" button. 3) Another major issue identical to the first one. Pagination buttons for navigating through the issues are located at the bottom, with page 1 highlighted.
  • Alt-text – Alternative text is a short description of an image and should be accurate, short, and contextual.
  • Tables – Tables should be used to help explain data, not create a visual layout.
  • Headings – Short text phrases that introduce sections in a document or page, and should follow a hierarchy of levels. 
  • Color contrast – Difference between lightness and darkness of two colors that improves visibility of text. 

Once you access the list of issues by clicking on the relevant icon and viewing that item’s accessibility report, instructors can make repairs using a few different options.

Fix Issue

The easiest way to update a not accessible item is to click the Fix Issue button listed on the accessibility report, if that button is available. 

Clicking the Fix Issue button launches a pop-up box that lays out what the issue is, how you can fix it, and recommends a change. Clicking Add Change will automatically make the correction.

Manual Remediation

The remediation process depends on different factors like the type of item or what accessibility problems are prevalent, so not all issues will have automated repair options. 

In those cases, instructors will have to manually correct the accessibility problem. Solutions can be found by clicking Learn More next to the listed item, which will provide step-by-step instructions on remediation. 

If the issues are with a source file, you can download the file, make corrections as advised, then upload it again using the update document feature in the accessibility report. Panorama rescans the item, then registers the item’s new accessibility score. 

Panorama for Students

Panorama also generates alternative formats for materials in Canvas so students can select the format that works best for them, ensuring equitable access to course content. These files are individualized and only available to the user who created them. Learn more about these accessibility services offered to students.

Don’t Delay

Since reviewing and updating every page, document, and activity in your courses can take time, accessibility advocates advise planning time to work with Panorama and improve content over multiple months to meet your deadline.

While ideally it’s recommended to build accessible content at the beginning, remediation will still need to occur. Working through your materials ahead of time means you won’t be scrambling to make everything accessible on the first day when, for example, a student using a screen reader can’t access a PDF. Trying to remediate content on demand is not only an added stress for instructors, but also forces the student to wait and risk falling behind in the class. 

So, avoid the scramble and the burnout and start using Panorama to check your course materials. Those working with faculty emphasize that progress, not perfection, is the current goal. With such a large volume of materials to review, accessibility advocates hope to see broad improvement rather than 100% accessibility ratings for a handful of courses.

As new guidelines are released, Panorama will update to meet those standards. This means that the sooner instructors implement its usage, the better they’ll be prepared to meet the needs of incoming students.

Grackle

Grackle is a Google workspace tool that checks the accessibility in Google Docs, Sheets, and Slides. Grackle can be added as an extension for U-M Google accounts.

Practical Tips

  • Share your experiences and issues with the ITS Service Center. Any problems are sent to the vendor for corrections and updates.
  • Register for a training session or take the Canvas Accessibility with Panorama course from the Canvas Accessibility Service.

Resources

University of Michigan

Additional Resources

For those who don’t have access to Canvas and Panorama, there are external resources that can help check your course’s accessibility.

  • WAVE Web Accessibility Evaluation Tools (wave.webaim.org) are available as a browser extension, subscription-based or stand-alone products that identify issues in web content.
  • Axe accessibility testing tools (deque.com/axe) include a free browser extension as well as more in-depth products.

Americans with Disabilities Act Title II Web and Mobile Accessibility

Generative AI (GenAI) tools are becoming increasingly popular for a wide variety of uses, including in classrooms. Whether you’re generating images, building slides, or creating summaries of readings, it’s important to be thoughtful about the tools you’re using and the impact they can have on both your students and our world as a whole.

Bias

A GenAI tool is only as good as its training data; if that data contains content that is racist or sexist, we shouldn’t be surprised when the GenAI tool develops the same kind of bias. Bias can come in a variety of different types: stereotypical, gender, and political. All of these biases can lead to certain groups being inaccurately featured more or less in outputs.

Bloomberg tested the biases present in the Stable Diffusion text-to-image generator in 2023. When they prompted the model to create representations for jobs that were considered “high-paying” and “low-paying,” the images generated of high-paying jobs were typically of people with lighter skin tones. People with darker skin tones featured more prominently in images of low-paying jobs. Bloomberg found similar results when they looked at the gender of the people in the images. Stable Diffusion generated three images of men for one image of a woman. When women did appear in the generated images, they were typically in lower-paying and more traditional roles, like housekeeper. Prompts for jobs like “politician,” “lawyer,” “judge,” and “CEO” led to images that were almost entirely light-skinned men.

Harmful Content

Besides being biased, GenAI can produce content that is harmful in a variety of ways. GenAI can hallucinate content that is not based on actual data, and is instead fictitious or unrealistic. It can be used to produce artificial video or audio content impersonating a person’s likeness. When this kind of video and audio content is done with permission of the person, it’s commonly called “synthetic media.” When people create artificial video or audio content of someone without their permission, it’s referred to as a “deep-fake.” Deep-fakes are often used to harass, humiliate, and spread hate-speech. GenAI has made the creation of deep-fakes easy and cheap, and there have been several high-profile cases in the US and Europe of children and women being abused through their creation. 

Policymaking efforts to combat the proliferation of and harm caused by deep fakes have become common both in the U.S. and abroad, with proposals often including disclosure requirements for the use of synthetic media, at least for certain activities. While educational uses of these technologies are unlikely to be restricted or banned, users should strongly consider disclosing the use of these technologies by default in the interest of transparency and in anticipation of any future requirements to do so that may apply. It may also be worthwhile to consider whether companies offering these products are well positioned to comply with this quickly evolving regulatory landscape as well as whether they are making reasonable efforts to help prevent the misuse of their products.  

Data

The collection of data used to train GenAI models can raise a variety of privacy concerns, particularly around personal and proprietary data. Some personal data collection can be declined, although the methods of how to do so are often buried in lengthy terms of service that most users don’t read. Those terms of service also cover how the GenAI tool can use the data that you put into the tool via prompting, so you should be cognizant of the kind of information you’re feeding it.

Recently, the Cisco 2024 Data Privacy Benchmark Study revealed that most organizations are limiting the use of GenAI, with some banning it entirely, because of data privacy and security issues. This is likely because 48% of employees surveyed admitted to entering non-public company information into GenAI tools. There’s also a general lack of transparency around what kinds of data sets have been used to train GenAI tools. Although some explicitly state where their training data comes from, many are vague about what the training data was and how they accessed it.

Copyright

Right now, many believe that using content, like books, images, and videos, to train GenAI falls under fair use in the U.S., but there are currently multiple lawsuits challenging this notion. If companies are unable to leverage fair use to acquire training data, the effectiveness and availability of GenAI is likely to decrease dramatically. The cost of obtaining licenses for the incredible amount of data needed will likely drive all but the biggest companies out of the market.

The outputs created by GenAI can have their own copyright issues, depending on how much they pull from the training data. If the image generated by GenAI, for example, is substantially similar to an image in the training data, there could potentially be some liability for copyright infringement if or when the image is used. Many GenAI tools are attempting to avoid this by refusing to generate content that is similar to copyrighted material, but there are ways for creative prompters to get around these restrictions.

Although many GenAI tools claim to be trained on openly licensed content, studies show that when asked about licensing requirements, 70% of the tools didn’t specify what license requirements were for the generated work, and if they did, the tool often provided a more permissive license than what the original creator intended.

The use of GenAI brings up ethical issues around authorship that are often related to copyright but are separate. For example, when using information gathered from GenAI, there may be an ethical obligation to cite the original source to avoid claims of plagiarism. GenAI doesn’t typically provide citations, and when it does, those citations are frequently incorrect. There are also concerns about the displacement of human authors and artists by GenAI; this frequently comes up when GenAI is used to create works in the style of certain artists or authors.

Environmental Impact

GenAI has a huge environmental impact. Research has shown that training the early chatbots, such as GPT-3, produced as much greenhouse gas as a gasoline powered vehicle driving for 1 million miles. Generating one image using GenAI uses as much energy as fully charging your phone. ChatGPT alone consumes the same amount of energy as a small town every day. On top of that, the data centers needed to house the training data and infrastructure for these tools require large amounts of electricity and water to keep them from overheating. Right now, it’s nearly impossible to accurately evaluate or know the full extent of the environmental impacts of GenAI.

Equity

There are a variety of different types of equity concerns when it comes to GenAI. Most GenAI tools are trained on data from data rich languages and are less likely to include non-standard dialects or languages. There are also access and efficacy disparities. Not everyone will have access to GenAI tools, whether it’s because of the cost, a lack of internet access, or because there are accessibility issues with the tool. Underrepresented or underserved groups may find their experiences missing from the training data, which is only optimized for some groups, not all, limiting the efficacy of the outputs.

Finally, it’s important to remember that all of the legal and ethical issues discussed so far have a disproportionate effect on marginalized groups. For example, negative environmental effects tend to be felt the worst in more vulnerable communities. Considering the major impact GenAI has on the environment, how are we going to work with these groups to help ensure they’re not further harmed?

Conclusion

Overall, there are pretty significant legal and ethical issues we should consider before using GenAI tools. This doesn’t mean that we shouldn’t use GenAI tools; it means that we should be thoughtful about when, how, and why we’re using them. And we should know that the way we use them might change in the not so distant future. The current lawsuits will take years to work their way through the legal system, and depending on how they shake out, GenAI tools may have to go through some major changes when it comes to their training data.

Practical Tips

Here are five tips for navigating through these complex issues:

  1. Investigate the reputation of the GenAI tool and the company that created it. Perform an online search for any potential legal or ethical issues. Add search terms like “complaint,” “violation,” or “lawsuit” with the company’s name, and be sure to read product reviews.
  2. Check the terms of service. Review the terms of service and privacy policies before using GenAl. Caution should be taken before publishing materials created through GenAI.
  3. Protect sensitive data. In addition to data shared for training purposes, it should be assumed, unless otherwise stated, that data shared when using GenAI tools will be accessible by the third party tool provider and affiliates. Data sharing must adhere to U-M policies. 
  4. Consider the ethics/limitations. Continue to remember, and remind your students, that GenAI tools are often biased, as the technology is designed to output common results based on its learning model. GenAI can also “hallucinate,” so specific claims should always be verified before sharing.
  5. Consult resources and ask for help. We are still swimming in uncharted waters. Utilize resources available here at U-M, including training and workshops on GenAI that are hosted across U-M. There is also a new GenAI as a Learning Design Partner series led by U-M instructors that is freely available via Coursera.

Brad is a 38-year-old man who is thinking about the future after leaving the Canadian Army. He has hands-on job experience in logistics and transportation but only a few college credits and no degree. He enrolled in the open online course “People, Technology, and the Future of Mobility” to learn about new technologies and get an overview of their possible impacts. He feels confident in his ability to learn independently online but dislikes reading and might struggle to spend time on the course due to heavy job demands.    

Lavonda enjoys her job in marketing but does not always feel comfortable meeting with clients. She hopes that taking the “Feedback Fundamentals” open online course will help improve her communication skills and put her in a better position for career advancement. Although she has a master’s degree in marketing, she has not taken formal classes in many years. She has never taken online classes before, and at 55, she worries she won’t be able to learn the technology needed to complete the course.  

Mohamed is a third-year engineering student in Syria who enrolled in “Community Organizing for Social Justice” because of the increased violence and injustice he sees. He knows very little about organizing and motivating people. However, he wants to work toward giving others more peaceful and equitable lives. His studies keep him busy, though, so he wants to find ways to stay motivated and make a difference in his community.  

An immensely wide variety of learners are attracted to the flexibility and low cost of massive open online courses. A single MOOC might contain learners from six continents with ages spanning teens in high school to retired adults. The range of learner demographics found in open online courses begs for an awareness of some key differences between learners’ levels of content knowledge, motivation, and engagement strategies learners bring to any given course.

Background Knowledge

Do your online learners learners share the same background and expertise? Not likely. The heterogeneity found in MOOCs means that people enter their courses with a wide range of content knowledge and background experience. These learners did not all attend schools with similar requirements and do not all live in the same regions, as reflected in the above examples of learner personas, so MOOC  “learners cannot be assumed to possess a common body of expertise and thus may approach a task with varying levels of understanding and experience” (Quintana et al, 2020). Faculty creating open online courses should take this broad range of content knowledge into account to make it accessible for diverse learners.

Motivation

Open online course learners are driven by various motivations for taking courses.  Building new skills for a career transition, professional development, and social activism are all typical motivations for learners enrolling in open online courses. Students also use them to supplement their formal training, casual interest in learning more about something (Milligan & Littlelohn, 2017), or a desire to connect with others (Zheng et al, 2015). 

Engagement Strategies 

Learners approach open online courses differently than traditional students might approach their residential courses. Some could have very little time to devote to the course each week and spend months rather than weeks to finish. Others may quickly and independently complete the required course readings, avoiding videos or optional material. Some will watch videos and only look at readings when necessary. Some learners will enjoy participating in discussions to request or offer help to peers, while others will not engage in forum discussions at all, so faculty should consider various possible activities and experiences their future learners might find engaging.  

Meaningful Connections

The flexibility and open access options of open online courses attract a variety of learners from around the globe. Some may be graduate students, undergrads, or high school students, but many others may not be students at all but working professionals with full-time jobs and/or families. To engage and maintain the interest of these learners, online content should focus on learners making meaningful connections between the theories faculty teach and how learners will use that theory in their own lives. 

References

Milligan, C. & Littlejohn, A. (2017). Why study on a MOOC? The motives of students and professionals. International review of research in open and distributed learning, 18(2)

Quintana, R.M., Halye, S.R., Magyar, N., & Tan, Y. (2020). Integrating learner and user experience design: A bidirectional approach. Learner and user experience research.  

Zheng, S., Rosson, M.B., Shih, P.C., & Carroll, J.M. (2015). Understanding student motivation, behaviors, and perceptions in MOOCs. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 1882-1895). ACM.

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:

  1. 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.
  2. 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.
  3. 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:

Jenni Patterson is a Design Manager Senior at the Center for Academic Innovation. In this interview, Jenni speaks with us about her role at CAI, the GenAI short courses, and how to get started with a short course.

Tell us a little bit about your role at the Center for Academic Innovation

I’m a Design Manager Senior here at CAI, and in this role I oversee the project management of various online learning initiatives in our non-credit and MOOC space. My job is to keep each project team – the faculty member, Learning Experience Designer, and Media Designer – aligned and on track as we move toward the project’s launch date. I initially focused on developing Teach-Outs, but in Fall 2023 I shifted to focusing on the project management of our new short courses.

You mention the short courses – tell us a little bit about what a MOOC is, and how the short courses are different from a regular MOOC?

A MOOC, or Massive Open Online Course, is a free, online course that is open to unlimited learners from all around the world. Here at CAI, our MOOCs typically take a learner 3-8 weeks to complete, expecting around 4-6 hours of effort each week. Short courses, as you can imagine by their name, are much briefer learning experiences! We expect a short course to take a learner just 1-5 total hours to complete. The goal of a short course is to provide learners the opportunity to dive into a very focused, yet still high quality, course. Where a traditional MOOC may have several learning objectives, a short course may have only two or three, or in some cases just one. This focus lends to a shorter learning experience.

Why are you so excited about these short courses? Why should faculty want to consider working on a short course?

I’m excited about these short courses because they are a great opportunity for faculty to share their expertise with our community of learners in a short, digestible way. Whether faculty have created an online course before or are new to the process, I hope they’ll consider working on a short course because it’s a great opportunity to develop an online learning experience, start to finish, in just a few months.

The current round of short courses are all focused on Generative AI. Why do you think GenAI lends itself to this format? Who will be most interested in these courses?

I think GenAI lends itself really well to the short course format. During the ChatGPT and Generative AI Teach-Outs, we heard from our community of learners that they wanted to learn more about GenAI as it related to their specific industries and personal contexts. The GenAI short courses allow U-M to provide this specialized content to our learners.

We think learners will be interested in these courses because they offer GenAI content beyond the many foundational GenAI courses we’re seeing. We’ll be offering GenAI short courses from a variety of perspectives – from programming to business and law to social work – allowing learners from different backgrounds to learn about GenAI in a context specific to them.

If a faculty member was interested in creating a short course, what would they need to do?

Faculty who are interested in creating a short course (or any type of project with CAI!) should contact our Partnership Development team at [email protected]. When you connect with them, they’ll want to know a bit about your idea and who you believe may be most interested in taking the course. From there, they’ll work with you to help imagine the course and to discover which product type (short course, regular MOOC, etc.) is best suited to meet the goals for the learning experience.

What should people expect from working with the Center for Academic Innovation?

The staff here at CAI is eager to help bring your project idea to life! On a typical design team, you’ll be working with a Design Manager (project manager), Learning Experience Designer (who supports course development and design), and Media Designer (who manages filming, production, and media assets). We work together, both synchronously and asynchronously, meeting weekly to review course development progress while also completing individual tasks between meetings. We are committed to working collaboratively with our faculty partners to create exemplary online learning experiences!

Copyright exists to promote progress by securing time-limited exclusive rights for creators of original literary and artistic works, including movies, songs, software, photographs,and architecture. On the other hand, facts and ideas do not fall under copyright protection, including methods of operations or systems. A work is copyrighted as soon as it is fixed in a tangible medium, or created in a way that is saved in some way. For instance, if you come up with a new song and sing it at an open mic night, that song is not protected until you either write it down or record it. Specific exceptions to copyright, such as using material in a classroom or making preservation copies for libraries, exist in the US. Fair use is the broadest of these exceptions (or user’s rights) and provides flexible guidelines to help determine how you can appropriately use the work.

If your use is not allowed under an exception to copyright law, permission is needed from the copyright holder. This can be difficult, especially when works are posted online and not connected with a person’s name or contact information. Even if creators were okay with people using their works under certain circumstances, there was no easy way to convey those permissions to the general public. In 2001, Creative Commons created a suite of licenses that would help bridge these gaps and make it easier for creators to give permission for their content and for the general public to find works they can easily reuse. Creative Commons licenses work within the existing copyright landscape, not against it, and explicitly allow for fair uses of the works, even if that fair use would contradict the other terms of the Creative Commons license.

Between 2001 and today, Creative Commons has grown, not only as an organization, but as a movement. The licenses are now used on nearly two billion works online across nine million websites. Creative Commons licenses increase access and “…give every person and organization in the world a free, simple, and standardized way to grant copyright permissions for creative and academic works; ensure proper attribution; and allow others to copy, distribute, and make use of those works” (About Creative Commons). 

Layers of Creative Commons Licenses

There are three layers of the Creative Commons Licenses. First, a legal code that is a base layer that provides terms enforceable in court. Next, there’s a human readable layer that summarizes the legal code and is easy to understand for non-lawyers.  Finally, there is a machine readable layer that is a summary of key features that technology, such as search engines, understand, allowing for filtering of works by Creative Commons license.

License Elements

There are four license options to pick from when choosing a Creative Commons license: Attributions (BY); Share Alike (SA); Non-Commercial (NC); and No-Derivatives (ND).  More detail about each type of license is outlined below, along with information about the two public domain tools Creative Commons has created.

  • The Attribution license (CC BY): allows people to use and adapt the work for any purpose (even commercially) as long as credit is given to the creator. This is the least restrictive Creative Commons license.
  • The Attribution-ShareAlike license (CC BY-SA): allows people to use and adapt the work for any purpose (even commercially) as long as credit is given to the creator and any adaptations made are shared under the same or a compatible license.
  • The Attribution-NonCommercial license (CC BY-NC): allows people to use and adapt the work for any noncommercial purpose as long as credit is given to the creator.
  • The Attribution-NoDerivatives license (CC BY-ND): allows people to use the work for any purpose (even commercially), as long as they give credit to the creator and do not create adaptations or derivatives of the work. This includes making any major changes, creating translations, or creating sequels. Under this license, people may adapt the work for their own personal use but may not share any adaptations publicly.

The four license types can be mixed and matched depending on the preferences of the copyright holder. It’s important to remember that all Creative Commons licenses require attribution. 

There are also two Public Domain tools: CC0 and the Public Domain Mark.

  • CC0: Allows creators/owners of a work to waive copyright and put their work in the public domain. This is different from a CC license because it is a choice to opt out of copyright protection.
  • Public Domain Mark: Universal label that shows a work is no longer covered by copyright. Popular with museums, this mark is for works that are free of known copyright restrictions around the world.

Get Involved!

The Creative Commons Global Network is part of the open movement focusing on collaboration and sharing works across the globe. You can learn more about the movement and how to get involved in your local Creative Commons Chapter at their website.

Resources

Visit Openverse or take a look at the Center for Academic Innovation Finding Useable Materials Guide to help you find openly licensed third party materials. 

The Copyright Team at the Center for Academic Innovation is always available to answer any questions you may have about Creative Commons licenses, including licensing your own work and using the works of others. Feel free to contact us at [email protected].

How this will help

Examine the pros and cons surrounding ChatGPT
Navigate the concerns of LLM as well as the potential benefits for learners and instructors

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.

The rapid shift to emergency remote instruction during COVID-19 left many instructors questioning how best to assess students, even well after classes resumed. Concerns about academic integrity left some wondering if using online tests made students more likely to violate academic integrity rules. Online test proctoring made news in many higher education settings as a way to ensure academic integrity. However, others have argued it is a violation of students’ privacy.

What is Online Proctoring?

You may be familiar with proctoring in a face-to-face or residential setting where a designated authority oversees an exam in a controlled, specified environment. Similarly, online proctoring is a service that monitors a learner’s environment by either a person or an artificial intelligence algorithm during an online exam. However, the environment an online proctor oversees is a learner’s personal environment. This monitoring can take the form of videotaping, logging students’ keystrokes, browser data, location data, and even biometric data like test-taker eye movements.

Advocates of online proctoring cite concerns about academic integrity in the online environment as a reason to implement proctoring (Dendir & Maxwell, 2020). Some even suggest that students do not mind the additional security because they believe it supports the integrity of the test and/or degree.

Concerns and Research

While onsite-proctoring for academic integrity may seem reasonable, there have been questions about monitoring a learner’s home environment. Monitoring a learner’s home environment has the potential for harm. Online proctoring can be perceived as invasive by students, as personal information about one’s location and physical data is recorded that is not otherwise necessary for an exam. Several institutions, like U-M Dearborn and University of California Berkeley, have placed limitations on, if not discontinuing altogether the use of third-party proctoring services. Institutions cite issues of accessibility, bias, concerns about student privacy, and institutional culture as reasons to discourage third-party proctoring. Student and faculty groups have publicly advocated for institutions to discontinue security features like locked-down browsers and third-party monitoring. At the University of Michigan Ann Arbor, third-party proctoring generally involves a separate fee and may be expensive, but still available through vendor partners.

Most of the academic research involving the use of online proctoring has focused on academic integrity, rather than the impact of proctoring itself. Wuthisatian (2020) found lower student achievement in online proctored exams compared to the same exam proctored onsite. Those students who were the least familiar with technology and the requirements for setting it up performed the most poorly. In addition, students who have test anxiety may experience even more anxiety in certain proctoring situations (Woldeab & Brothen, 2019). With further research, we may find the problem may not necessarily be proctoring, but rather the burden and effort of technology on students when taking an online exam.

Problems with internet connections or the home testing environment may be beyond students’ control. The lack of ability to create a “proper” testing environment raised students concerns about being unjustly accused of cheating (Meulmeester, Dubois, Krommenhoek-van Es, de Jong, & Langers, 2021)

Alternatives to Proctoring

Ultimately, only the instructor can determine whether proctoring is the right choice for a class and sometimes proctoring may be the best choice for your discipline, field, or specific assessment. Particularly in a remote setting, it may feel like the integrity of your assessment (particularly a test) is beyond your control, so proctoring may feel like the only option. However, there are alternatives to proctoring exams, from using exam/quiz security measures, to re-thinking a course’s assessment strategy to deemphasize exams. If you are concerned about how and what you are assessing, the Center for Research on Learning and Teaching provides resources and consultations to discuss academic integrity and different methods of assessment. We also recommend CAI’s Faculty Proctoring document if you have questions about proctoring.

Resources

How this will help

Understand how copyright impacts the items you include in your course
Learn how to verify third-party content availability

The copyright law exceptions for teaching are different for teaching online than they are for teaching face-to-face courses. Assumptions about copyright that you may have about teaching in a face-to-face setting may not apply in the same way to online teaching. When you use third-party content (something created by someone else), you need to consider whether copyright law allows you to use the content.

Imagine these situations: 

  • You have a brief movie clip that you’d like to use in your face-to-face class as a way to illustrate a concept.
  • You found an image online that does a great job of illustrating the cycle of poverty.
  • You have an article that you’d like to share with your class. In your face-to-face course, you would print it out and share with students.

These are just a few ways that third-party content is typically used in courses. When using these types of content in online courses, you should think about how copyright law affects your use.

Copyright law restricts how you can use third-party content in online courses more than in face-to-face courses. It is important to consider copyright law in online course creation; if third-party content is used in a way that does not comply with copyright law, it could be taken down (disrupting the course), the unit could be forced to pay for the use, or U-M could possibly be sued.

Third-Party Content

Faculty members are in a great position to help avoid these risks by asking the following five questions for each piece of third-party content they consider using in their course:

  1. Are there contractual terms, terms of service, or terms of use that limit my use?
  2. Is the third-party content uncopyrightable or in the public domain?
  3. Is the third-party content already licensed for my use?
  4. Is my use of the third party content a fair use?
  5. Can I ask for permission to use the third party content?

1. Are there contractual terms, terms of service, or terms of use that limit my use?

Inform yourself of any contractual terms that might affect the use you want to make (e.g., read the terms of use of the website you’re relying on for access to the work). Ultimately, it is for you to decide whether to follow the terms you’ve agreed to or try to negotiate a different set of contractual terms. If you ignore contractual terms, remember that there may be legal consequences; reach out to the Office of General Counsel if you have any questions.

If the answer to this question is yes, move to question five.

2. Is the third-party content uncopyrightable or in the public domain?

Copyright does not protect everything. Some things are fundamentally not copyrightable. For instance, copyright does not protect any idea, procedure, process, system, method of operation, concept, principle, or discovery. To be protected by copyright, the work needs to embody some spark of creativity and not be purely factual. Works that are not protected by copyright can be used without any restrictions.

This is especially important when you want to use third-party content like charts and graphs in your course. If the chart is not copyrightable, it can be used freely because there are no copyright restrictions. Examples of non-copyrightable charts and graphs are available in the OpenMichigan Casebook.

Some third-party content is no longer protected by copyright, either because the copyright term has expired or because the copyright holder has dedicated the work to the public domain. In the US, as of 2020, all works published in the US before 1925 and all works created by federal government employees are in the public domain. Works published between 1925 and 1989 could also be in the public domain for not following formalities that were required at the time. Consult Cornell’s Copyright Term and the Public Domain in the US chart to see if the third party content you want to use might fall into this category of works.

If the third-party content is uncopyrightable or in the public domain, stop here. If not, move to question three.

3. Is the third party content already licensed for my use?

Your use of a copyrighted work might be covered by a pre-existing license. The most common type of public licenses is a Creative Commons (CC) license [Link to Creative Commons]. CC licenses are blanket licenses that give everyone the ability to use the content as long as they follow the rules outlined by the copyright holder. All CC licenses require attribution. More details can be found in AI’s How To: Attributions guide.

There are also online resources that the U-M library has already purchased. If your online course is for registered U-M students, you can take advantage of these resources in your online course by providing students with the link to the resource (commonly, ebooks and journal articles, but also some image banks) in the library’s catalogue. This will authenticate the student and allow them to view the resource.

For more information about what library resources may be available for your course, contact your subject specialist librarian. 

If the third-party content is already licensed for your use, stop here. If not, move to question four.

4. Is my use of third-party content a fair use?

There might be some third-party content you want to use that is protected by copyright and isn’t openly licensed. If there is no adequate replacement and the third-party content is crucial to the course, you should consider whether the use is a fair use. If the use is a fair use, the third-party content can be included in the course without permission.

Fair use is a user’s right that encourages certain favored uses (like criticism, commentary, and education) without the permission of the copyright holder. Fair use is context specific; there are no brightline rules here. For example, it’s a widely believed myth that 10% of a work can be used under fair use. This is not always true. Sometimes, using 10% of a work is not a fair use. Sometimes, using 100% of a work is a fair use. It is very dependent on the specific use you are making.

For each fair use analysis, consider the following four factors:

  • the purpose of the use
  • the nature of the copyrighted work;
  • the amount used; and
  • the effect on the market

For more information about fair use and some helpful guidance on how to apply the fair use analysis, consult the Library Copyright Office’s Fair Use page.

If your use of the third-party content is a fair use, stop here. If not, move to question five.

5. Can I ask for permission to use the third party content?

If the third-party content is copyrightable, not openly licensed, and your use would not be a fair use, you should ask the copyright holder for permission to include the content in your course. Third-party content can be used in any way if the copyright holder gives you permission to make those uses. When asking for permission, make sure to be clear about how the material will be used, how many people will view it, and how long the content will be used. This will help the copyright holder make an informed decision on whether or not they want to allow the use and how much they want to charge for it (if at all). Although not legally required, it is a good idea to get the permission and terms in writing and save the writing for future reference.

The Library Copyright Office has a Sample Permission Letter that can easily be adapted to fit the needs of the specific course. More information about requesting copyright permission can be found in the Obtaining Copyright Permissions research guide.

If you cannot ask for permission to use the work, you should not include the work in your course. Instead, try looking for a replacement that’s under an open license. AI’s guide on Finding Usable Materials is a helpful place to start.

Practical Tips

The U-M Library Copyright Office is available if you have questions or would like to learn more about how copyright affects what you use in your course. They can be contacted at [email protected]. You can also schedule an appointment with one of their specialists.

Resources

University of Michigan

CAI- How to flip your content: Designed for those building MOOCs, this document can help you find additional open education resources

CAI- Finding usable materials

CAI- Open Educational Resources

Contributors: U-M Library & Academic Innovation