Data about disabled students, in a tool they could not use
An accessible reporting system for IDEA data at the Rhonda Weiss Center, built with 80 stakeholders. They included the disabled people the data is about, who had rarely been in the room when these tools were designed.
- Role
- Accessibility and user experience lead
- Year
- 2023–2024
- Built with
- Design tokens, U.S. Web Design System, Data visualization, WCAG
States report data to the federal government about children with disabilities under the Individuals with Disabilities Education Act — Part B for school-age students, Part C for infants and toddlers. Who is being served, under what category, with what outcomes, and where the gaps are. It is how the country finds out whether children with disabilities are actually getting the education they are entitled to.
The tools for reading that data were, with some regularity, unusable by people with disabilities.
That is not an irony worth being clever about. It is a straightforward failure with a specific cost. The people with the strongest claim to understanding this data are disabled adults, parents of disabled children, advocates, and researchers who are themselves disabled. They were the ones most likely to be locked out of it.
What we built
I led accessibility and user experience at the Rhonda Weiss Center for Accessible IDEA Data (opens in a new tab), which AEM Corporation leads under a multiyear grant from the U.S. Department of Education's Office of Special Education Programs. The Center's job is not to publish the data itself. It is to help states publish it accessibly, which is a harder and more durable problem than fixing one tool.
We built an accessible reporting system, developed with around 80 stakeholders, including disabled people.
Two decisions shaped the rest of it.
We put accessibility decisions into design tokens, extending the U.S. Web Design System rather than building beside it. A color that passes contrast is not a preference someone applies correctly; it is a value a downstream team inherits whether they are thinking about it or not. The same goes for focus treatment, text sizing, and the palettes used for categorical data. That last one matters enormously in a reporting tool. A chart with color as its only channel excludes people before they have read a number.
We tested with disabled participants continuously — over thirty studies, including blind and neurodivergent participants — rather than validating at the end. That is a deliberately expensive choice and the only one that finds the problems that matter. Automated checking finds a missing label. It does not tell you that your table of state-level outcomes is technically navigable and practically impossible to hold in your head at screen-reader pace.
The delivered tool reached the highest applicable conformance level. I am careful with that sentence: it is a statement about the tool we delivered, on the criteria that applied to it, and not a claim about everything the department publishes.
Data visualization is where accessibility usually quits
Most teams do reasonably well on forms and navigation, then hit charts and give up. The honest answer is expensive: a visualization needs a real non-visual equivalent, not alt text saying "bar chart."
Equitable data representation was most of the design work here, and I have spent a fair amount of time since arguing it publicly, at CSUN and Closing the Gap among others. The short version: the question is not how to describe the picture. It is what the reader is trying to find out, and what the shortest path to that answer looks like when the picture is not available. Those are frequently different structures, and the second one is rarely just a table.
Why this one stays with me
Most accessibility work is about not excluding someone from a transaction. This one was about who gets to participate in an argument — about whether the education system is serving disabled children, using the evidence that is supposed to settle it.
A parent who cannot read the report cannot challenge the report.
Where this goes
The pattern I would take everywhere from this is the token one. Whenever an accessibility decision can be made once, centrally, and inherited, it should be. The alternative is asking hundreds of people to remember it. They will not, and no one will find out until someone is already shut out.
It is the same argument I now make about design systems in code and about machine-readable standards. This was where I first watched it work at the scale of a federal reporting program, with the people it was about in the room.
Gallery
About the drawing
The drawing for this piece was generated, not chosen. Hashing the piece’s name fixes one point on the color wheel; the other two follow from it. The same name always gives the same three colors.
#255f90#25358a#d7bb61The line under the drawing marked “Meant to show” is written by a person, not the model. A generated drawing keeps what is large and loses what is small, so the detail that decides who someone is can go missing, and a picture only reaches people who can see it. Where the drawing and that line disagree, the line is the intent.
Or press ←the left arrow and →the right arrow.