Cutting curbs and other thoughts on universal design (#1126)
One of the more important modern trends in education is one to
embrace what is often call Universal Design for Learning
[1]. It
stems from the idea that the changes we make to support those who
are disabled or differently abled can also have positive impacts
on others. For example, if you caption your videos [2], you not
only support people who are hard of hearing [3], but also non-native
speakers, people in noisy environments who might benefit from being
able to read rather than hear, and more. For that particular case,
you also achieve indirect benefits: A captioned video is easier to
search [4] and, for some subset of the population, being able to
read and listen simultaneously provides benefits toward comprehension.
There are a host of relatively low-cost UDL-like strategies that I like to see people embrace: Ask students to serve as note-takers for your classes, provide slide decks ahead of talks and classes, include reasonable alt text along with your images, make sure your PDFs include text as text and not as images [5]. Things like that.
Given all these examples, I’m always surprised at what many people
choose as the prototypical example of universal design (broader
than universal design for learning): curb cuts. At first, the
story sounds good.
Cities cut out the curbs at the ends of sidewalks and replaced them
with ramps so that people in wheelchairs and electric scooters can
more easily get around. And then, suddenly, we discover that lots
of people benefit: parents with strollers, workmen with hand trucks,
skateboarders, more. So we see articles with titles like
The Curb Cut Effect: How Making Public Spaces Accessible to People With Disabilities Helps Everyone
.
But you know what? The story isn’t that simple, and so the simple
presentations frustrate me. The thing is, curb cuts aren’t a
technology that end[s] up benefiting all of society
. Why not?
Here are some examples.
At least as originally constructed, curb cuts created a problem for
a different disabled group: the blind. Unsurprisingly, if you are
used to identifying where the sidewalk ends by your cane hitting
the curb, and the curb goes away, it’s a lot harder to know when
you should stop. Early solutions to this new problem, such as
changing the texture of the cement, seem to have proven less than
successful.
I believe the raised plastic-like domes
that now appear on many
curb cuts address the issue, but they have their own issues, such
as the expense of replacing them.
It also appears that many of the early curb cuts were in California. And that means that people didn’t think about another effect of curb cuts. That’s right, Midwesterners, ice! Curb cuts are wonderful at creating a pool of water that freezes. Once again, the textured domes provide more traction. But I see an awful lot of ice at the bottom of curb cuts. I slipped on one the other day.
I don’t mean to criticize curb cuts; I agree that they are an
important innovation to keep people mobile and it’s worth the cost
to add and maintain a surface to ensure that curb cuts are safe(r)
for the blind and in winter. But they are not something that
helps everyone
. So why do people use them as the generic example?
Is it perhaps because other, more universally beneficial, instances
of UD, such as video captions, require individuals to spend effort,
rather than just some anonymous governmental entity charged with
putting them into place?
In any case, no matter what the example, remember that (a) it’s worth your effort to make things accessible and (b) most of what you do to make things accessible will have important indirect benefits. But make sure you consider the possible risks to other groups, too.
[1] I think equitable grading is likely to be another. Some say
active learning, but I don’t think of active learning as a modern
trend
anymore. Active learning practices have been in place for
decades.
[2] And you should!
[3] Including me.
[4] And to make available for search engines to index and therefore for people to find.
[5] I am amazed at how much born digital
text ends up as images,
rather than as text.
Version 1.0 of 2021-02-24.