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Using Data Science to investigate discrimination – Part 1, Mobility

I was mobility impaired for a while, and one thing that struck me quite painfully was how much further I had to go to access the “accessible” features of many public places. Using the ramp instead of the stairs could mean many metres to replace just 3 steps, as in this example outside CSIRO’s Kensington campus, in Perth. There’s a ramp for every set of 3 steps. I didn’t actually measure the increase in distance involved in using the ramp instead of the stairs, but it was considerable.

A long series of shallow outdoor steps, with three steps in each set, up to a large building in the distance. There are trees on either side of the steps, and switchback ramps that go from one level to a next.
A close up of one of the switch back ramps. It is shallow, since it only needs to be three steps high, but it goes several metres out, has a hairpin turn, and comes several metres back.

There are other ways that so called accessible features are less accessible than you might think. It’s not just ramps. Consider how much further you have to go to use the lift instead of the stairs – in some train stations, there’s only a lift at one end, which could be a surprisingly long way from where you need to be. Next time you are at a door with a button to press to exit, notice how far the button is from the door. When every step is painful, or difficult, those distances really add up.

Why am I talking about accessibility for mobility impaired folks on an education blog? Because a great way to get kids thinking and talking about mobility impairment when it’s outside their own experience is to get them to measure how much further someone in a wheelchair has to travel to navigate their school. (You could also use a local shopping centre, library, or other public building.) How much further to use the lift? How long are the ramps compared to the stairs? How far to the button to activate the “automatic” door? How much further to the “accessible” toilets? You can use a measuring wheel if you have one, or other tools such as a step counter or measuring tape. Devising a way to make the measurements accurate and reliable can be part of the project.

(Accurate meaning it does actually measure the distance involved, and reliable meaning you get the same measurement each time you measure. They are not necessarily the same, for example if you weigh yourself with one hand on the doorpost to steady you, you might manage to get the same weight reliably each time, while not actually getting an accurate measure of your weight, since the doorpost takes some of your weight.)

You could have kids measure the distance they normally walk around the school over a whole school day day or a week, or measure particular pathways – say, from the canteen to the library, or from the gym to the science labs – and then remeasure the distance for the same schedule or destinations using accessibility measures such as lifts and ramps. Many students could measure the same paths, and then explore the reasons for different results, such as the accuracy and reliability of the measuring tools, and how much the path taken just varies as people walk.

At this point you can get the students to write out and critique their method, to consider what they are measuring and when. Are they considering movement around the classroom? What about trips to the toilet? To the water fountain? During breaks outside? What might interfere with their measurements, and what accessibility features or issues might they have missed? Have they thoughtlessly included steps in any of their wheelchair routes? How could they test their paths?

Once they have their measurements, it’s time to figure out a standardised distance per day. They might choose to use the average of all of their measurements – considering whether they need to toss out some measurements for being wrong, or remeasure some distances to check. Or they might use the average of a particular path. There are a range of ways to summarise the results, and it’s a nice opportunity to explore the pros and cons of each approach.

Remember that the important number is the difference between a standard path taken by a student on foot and the path taken by a wheelchair user, not the total for the wheelchair user. How much harder are we making wheelchair users work to access the same spaces?

Students can then use the value per day to calculate how much further a student in a wheelchair has to travel in a week, a month, or a whole school year, to access the same spaces as everyone else. As a team, the class could then design new accessible features to remove some of the extra distance, and present them to school leadership.

There is, of course, more to discrimination than easily measurable metrics like these, but metrics can be a starting point. A crowbar to use as leverage. And a useful way to track progress.

What I love about projects like this is the opportunity for students to consider issues that don’t normally impact them, and then quantify them, and come up with ways to improve those numbers. There are so many opportunities, too, to consider measurement errors, issues with different ways of summarising the results, and other ways they could have approached the problem. This is no textbook example that produces a perfect curve. This is a real problem with real complexity.

You can see that this kind of project can easily cover curriculum in a wide range of subjects, when you consider the issues involved. Building design, social inclusion, persuasive writing, problem solving, critical thinking. Maths, Digital Technologies, Science, English, Geography. With shifts of focus you can build a project like this into a cross curricular extravaganza, or a single subject project.

And, as always, kids learn that data is a tool they can use to measure problems, communicate them, and try to fix them!

You can fund the development of projects like this at https://givenow.com.au/adsei/

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