EDCI136 - Waylon McCarthy

When I hear ‘accessibility’, I think of wheelchair ramps, braille subtexts, and the described video message before TV shows as a kid. However, Charlie Watson’s talk at UVic about digital accessibility and assistive technology made me realise how widespread – and vital – accessibility is.

Watson, who oversees the Adaptive Technology Program at UVic’s Centre for Accessible Learning, covered everything from high-tech gadgets like braille displays to minor yet significant adjustments we may make in a Word document or a Zoom chat in his informative presentation.

Watson’s criticism of the phrases adaptive and assistive technology was the first thing that caught my attention. In reality, these tools are part of a continuum, but we frequently isolate “special” technology for individuals with disabilities from the tools that everyone uses, such as screen magnifiers or voice dictation. Consider using automated subtitles in a noisy café or text-to-speech while driving. Everyone benefits from accessibility, or put so bluntly by Watson: “Ability is temporary. You will be disabled one day. Design for that now.”

We need to stop expecting people to change to fit our systems. We need to design systems that fit people. Whether that’s ensuring captions are accurate, documents are screen-reader friendly, or diagrams aren’t cluttered and color-dependent, small changes go a long way. As someone who never thought twice about hyperlink text, I now cringe when I see “Click here.” Charlie’s point about screen reader users encountering a wall of meaningless links hit hard: access starts with intentional design.

It was impressive how many options were showcased, ranging from dictation software and other keyboards to immersive reading modes and haptic visuals. The fact that so many are already included in devices or are publicly accessible, such as Otter.ai for transcriptions or Microsoft Edge’s Immersive Reader, was even more startling. Access isn’t always the problem; awareness is.

Charlie also reminded us that innovation doesn’t have to be costly by bringing up the community-built 3D printed technology. It can be open-source, creative, and cooperative.

Charlie’s presentation was a call-in rather than merely a how-to. A reminder that charity is not the same as accessibility. It’s fairness. The “selfish” reason to care is that accessible design benefits everyone, including the exhausted reader, the ageing professor, the parent with a sleeping infant, and the overworked student. When the digital world shifts towards equity and usability, we all gain.

Marginalization of minorities has been prevalent in practically every institution, framework, and principle of social development in Western history. It has only been recently that significant action has been taken to heed equity and diversity in these areas, which has in some cases resulted in major overhaul of such structures. Despite this however, the issues still manifests itself almost everywhere, most significantly so in the more complex aspects of society; income, judicial systems, politics, etc. When these systems have been under development with little consideration of these minorities for so long, it takes significant time and effort to effect meaningful change.

Without consideration of equity and diversity from the very beginning, the disparity it generates only becomes more and more magnified as the system develops. This is why when development emerges in new areas, it is vital to take careful consideration of diversity seriously and immediately. One of these frameworks is digital literacy: the digitization of the modern world is fairly recent, and overlaps with the combatting of underrepresentation and systemic marginalization and prejudice. Therefore, as digital literacy becomes a more pervasive issue and undergoes significant development and institutionalization, a rare opportunity emerges to make diversity and inclusion a fundamental element of digital literacy, where every progression and expansion proceeds with its consideration. This is not to say that there is no injustice or inequity already established in digital literacy, but it makes it so much easier to tackle these issues when they are not so anciently entrenched.

Maha Bali is one of the many advocates bringing light to this issue and affirming its vitality. She suggests a variety of methods for attacking inequity in digital literacy, as well as proactive methods to maintain equity for the future. One of these is a model she calls the ‘Rumi Cheese Model’, based off of the Swiss Cheese Model, a widely accepted and acclaimed accident causation and risk analysis model. The Swiss Cheese Model likens a system to multiple slices of Swiss cheese stacked consecutively, in which each each layer represents a failure defence, and each hole represents a lapse or weakness in the defense. The model theorizes that the failure of a system is never due to a fault in any one defence, but rather that it occurs where the ‘holes’ in multiple defences align when they are compounded.

Although the Swiss Cheese Model finds its most prominent applications in safety protocol, such as emergency response protocols and aviation safety, or in engineered systems, such as computer software and complex machinery, Bali applies the model to digital literacy. She does so however, with a caveat, which allows the mechanical nature of the model to be applicable to the socially delicate and complex nature of digital literacy. The ‘Rumi Cheese Model’, likens the protection of digital literacy from the adulateration of inequity to slices of Rumi cheese rather than Swiss, with the difference being that Rumi cheese contains black peppercorns that Swiss does not, but with all of the same holes that Swiss cheese does. The black peppercorns are a polarizing incorporation; some love them while others find them to ruin the cheese. This polarization is analogous to the human variability associated with diversity, where no one ‘defense’, or accomodation, is favourable for the demographic to which the accomdation was designed for. In the Swiss Cheese Model, a defense can either fail or withstand; there is no in-between, which does not hold true in the context of digital literacy. This emphasises the importance of humanizing digital literacy in establishing and maintaining equity, diversity, and inclusion, rather than simplifying it or attempting to conform it to a mechanical model.

After diving into the recent conversations and literature around generative AI in education, I find myself both energized and conflicted. Lucas Wright’s practical use of AI for day-to-day tasks like drafting emails and managing knowledge repositories gave me a tangible sense of how AI can alleviate mental clutter and help streamline routine academic workflows. Meanwhile, Mariel Miller’s discussion on AI as a collaborator in learning – capable of offering personalized, accessible, and even creative support – paints a hopeful picture of what’s possible when students engage with AI thoughtfully and critically. But she also warns of over-reliance, reminding us that learning isn’t just about completing tasks — it’s about doing the hard cognitive work ourselves. I’ve realized that efficiency, while tempting, can come at the cost of deeper understanding if we’re not mindful of how and when we use these tools.

Layered on top of that was the speculative article from the Asian Journal of Distance Education, which creatively explores both utopian and dystopian futures of AI in learning. It made me reflect on how we, as learners, are shaping that future every time we choose to engage with AI — whether for convenience or creativity, enhancement or escape. One of the most thought-provoking takeaways for me was the idea that AI should serve as a partner, not a replacement — supporting human agency rather than diminishing it. There’s no doubt we’re at a turning point. I’m now more committed to asking better questions when I use AI, thinking not just about what I’m getting out of it in the moment, but how it’s impacting my growth long-term. If we can hold onto that awareness, maybe we really can find a balance that honors both human curiosity and machine efficiency.

Learning Python has been an emotional rollercoaster for us. Never in my life have I experienced such intense frustration followed by pure glee and satisfaction about 5 minutes later. Today was our second session in saga of learning Python, in which we had aimed to create our first small project together. Because we were having trouble coming up with a project that would be achievable within our scope, as we aren’t very familiar with the extent our skills can be applied yet, we asked generative AI chatbot ChatGPT to think of a small beginner level project to challenge us with, and it came up with: the infamous number-guessing game. Of course, we were up for the challenge!

Although we already had some idea of what our code would need to look like based off of what we already knew, we did have to refer back to some W3Schools tutorials for refreshers on certain things, such as != and += notations for making statements. Today, we also learned how to use the Python shell as opposed to the main console, and we learned how to create a file and learned how to run a file in the shell. We were having trouble understanding this concept, so we called longtime friend and Python enthusiast Nik.

After a few unsuccessful runs with Nik troubleshooting in between, we finally found success! Here is the code to our new game:

The player enters random numbers until they guess the correct one, getting hints on which way to steer their guessing based off of their last guess. To avoid crashing, we also have a protective line for non-integer entries. Here is an example of someone playing our game:

The feeling of triumph when we pressed ‘Run’ and red text didn’t show up was a feeling like no other.

Goals for Next Session

Now that we have started built ourselves a solid foundation in Python, and seeing as we are now in our final month of classes, Lyndsay and I will be starting our final project in our next few learning sessions. Although our learning has by no means progressed to the point that we were aiming for when we started this process, we want our final project to be part of the learning process as well, rather than simply a reflection/ show of what we had learned beforehand. Today was actually really fun, and now Lyndsay and I are itching to get started on our next task!

After a much needed relaxation in Mexico over reading break, Lyndsay and I were ready to jump into our project. Python is widely versatile and expansive, so we did not find a linear, rigid learning approach to be appropriate. Instead, Lyndsay and I are going to try to implement as many learning methods as possible to experiment and find wat’s right for us.

For our first session, we familiarized ourselves with the resource W3Schools, a free educational website with various tutorials. We worked through 5-7 tutorials, each time gaining a new basic Python skill. We first worked through the introductory tutorials, learning the fundamental commands, before moving on to some more specific tutorials. We learned how to work around Python syntax, we learned how to make comments, and we learned how to assign variables and what the basic variable types were. We also are now able to make mathematical commands, which we supplemented a more exhaustive list of commands using ChatGPT, and we also learned about the different data types, such as float and string data.

Goals for Our Next Session

For our next session, we are aiming to complete a small project. Lyndsay and I have decided to either create an interactive quiz to showcase our conceptual understanding thus far, or possibly to create a functional budget tracker. Although functionally it is likely to be relatively frivolous, we find it important for our learning progress to have a tangible milestone such as something like this, and we think it will be a fun way to make the learning process more engaging and challenging.

Every piece of media that I consume – whether that be a meaningless Instagram post or a formal article – I can’t help but wonder: is this AI? I catch myself at times doing a double-take, almost overlooking something to be real before really taking a good look. The attempts of a bot to imitate a human used to be something of a comedy even a year ago, but now I sometimes need to look at something 3 or 4 times, even supposed live footage sometimes, before I can come to a conclusion. This prompts me to question: “How many people saw this an believed this was real?”, “How many AI posts have I glossed over that I will never know about?”. And it only gets worse as time progresses, getting more accurate and terrifying every day.

But it’s not as simple as ‘human or not human?’. Misguidance can just as easily be achieved the human way, and this way is much less likely to be accidental. Attention is therefore vital for the consumption of all types of media.

Many methods have been developed by experts to keep people equipped, however, a variety of which were shared with us by digital literacy expert Mike Caulfield. One of these cases was the SIFT method (short for Stop, Investigate, Find, Trace), a method of information verification. The idea is that upon being exposed to a source, one should first stop to consider the context of their situation and the content of the source, before investigating the nature of the author. This step is not only important simply to assess the credibility and authority of creator, but also to analyzes any important aspects of their identity that should alter one’s interpretation of the source. Then, the reader should attempt to find other related sources (ideally from more credible sources) that may support or refute the information put forth by the source in question, or simply even to give the reader more context for a better understanding. Finally, it is important to attempt to trace any references made by the author back to their original context. This allows the reader to properly assign the credit of a reference in its true, full context, without any nuances contrued by the author.

The internet has at once become the most useful and prospective but also the most destructive influence on knowledge in the present day. Before the internet, the ability of information to become widespread was an integral function of its credibility and verifiability. With the increasing pervasiveness of the internet, the spread of knowledge and dissolution of censorship is at an all-time high, but it instills a devastating trend. Creators feel less and less of a need to to cite information that they pass of, and people no longer feel the need to reference information from credible sources. I see it in everyone around me; my friends, family, peersare becoming lazier and lazier. The goal for so many is to complete their work as quickly and painlessly as possible, and this is perfectly facilitated by internet access. It is something that immensely rewards those with evaluative thinking and logical rationale while at the same time totally discouraging the individual from critical thought and developing the skills to best use it.

It is for this reason that I find verification methods like these to be so useful. Not particularily because people lack the verification skills to properly assess online sources (although many do), but because so many people lack the initial exertion to attempt to think critically about a source; good interpretation of sources can be taught and learned, but the willingness to employ these skills is not nearly as simple. People who possess these skills are almost as easily taken victim by misinformation because they do not apply them – almost every Canadian teen has been educated in this way to some extent, I still observe this issue in almost every aspect of my life; in myself at times. While the fundamental importance of skills taught by the SIFT method are undeniably important, I find methods like these to be so valuable because it triggers the reader to employ a second thought, to genuinely evaluate the information they are given, rather than thoughtlessly meandering by.