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Computer science professor was on an airplane when he invented a 3D game editor for blind and visually impaired children.

Stefik revealed, in a characteristically nonchalant manner, how his dislike of flying and a need to otherwise preoccupy his mind led to the creation of a complex — and extremely useful — tool.

“I guess I hate planes and it keeps me sane to ignore everything and invent something or another,” he said. “I invent a lot of stuff on planes.”

Those quiet sparks turn into real innovations in computer programming at his ������ lab. His goal? To create user-friendly programming technologies for all, including those with disabilities.

His humble outlook is also present when Stefik talks about some of the lab’s more recent accomplishments, like winning a $500,000 Google grant to build innovations in block-based coding or making data science more accessible for blind students in a classroom.

When Stefik embarked on his research in 2006, accessible programming tools for K-12 education were rare. Two decades later, they still are. His lab, now housed in ������’s new Advanced Engineering Building, is one of the few nationwide tackling this challenge. But, accessibility is gaining traction. Just last April, the U.S. Department of Justice issued a landmark rule strengthening requirements for web and mobile app access for people with disabilities. 

Stefik’s sometimes unseen work might have something to do with it, though he’d never take credit for it. The inventions are best described as mathematical algorithms working behind the scenes to, for example, automatically generate scientific visualizations of data that are screen reader friendly.  

, as named by the Computer Science Teachers Association, Stefik is also the creator of , the world’s first evidence-oriented programming language. The open source platform is used by novice programmers and employed by computer science teachers in classrooms. In 2022, all public high schools and charter schools in Nevada began offering — by state mandate — Board of Education-approved computer science classes.

The merging of these two issues — computer science education and accessibility — is the centerpiece of the aptly named Quorum Lab, which has proven to be a bit ahead of its time. Let’s take a peek inside.

The Quorum Lab: A New Home in AEB

Tucked away and separate from the expansive, open-concept lab spaces in ������'s Advanced Engineering Building, the Quorum Lab looks like a normal office space with three sets of cubicles. But it feels more private and secluded compared to the interconnected second and third floor labs that dominate the new building.

But, just because it’s set apart doesn’t mean the interdisciplinary collaborations are any less frequent or important, Stefik noted.

“I’ve collaborated with an amazing array of unique people on my teams or in their orbit including a blind neuropsychologist, mechanical engineers with expertise on tactile perception, deaf consultants on robotic telescope arrays, astronomers, mathematicians that program proofs with their eyes, deaf-blind undergraduates that communicate only through text messages, and blind children,” Stefik said.

Before moving into AEB, Stefik requested space that offered the same level of privacy as his old lab, crucial for the human-factor research at the heart of Quorum Lab’s mission.

“When I got to ������ there weren’t a whole lot of engineers who were doing human factor-style research — it’s more common in fields like psychology,” he said. “But in the line of research I was pursuing at the time, I needed a space where we could actively observe people with disabilities using the technologies we were hoping to create.”

All the college could offer at the time was a space that likely no one would want: “a dark, dank, squatty room,” Stefik recalled.

“I was like, ‘Perfect, it’s exactly what we need,’ and I wasn’t saying it facetiously,” Stefik said.

The Big Goal

Stefik and his team conducted countless studies in that room, recruiting participants with a variety of disabilities, including people who are deaf, blind or visually impaired, those with physical disabilities, or other conditions. They tested out technologies that would make it easier for them to code or, more recently, interact with and interrogate data science like bar charts and scatter plots.

Ultimately, Stefik's research is aimed at workforce development. These technologies could help young students with various disabilities eventually enter college programs and fill jobs in the highly in-demand field of programming.

“Despite being 16% of the world population, according to the World Health Organization, researchers have spent little time examining the population in the context of computer science education, either as students or as educators,” wrote Stefik, Ph.D. student Hannah Williams, and colleagues in a 2024 paper. “Researchers rarely ask about disability, for a variety of reasons. Indeed, when we talk about computer science for all, disability is often ignored. Some work has shown that there are accessibility barriers with programming languages, curriculum, and pedagogy, but gaps remain.”

has been leading the charge to fill the gaps. In addition to Stefik, the lab is run by two full-time software engineers, William Allee, and Gabriel Contreras, and three computer science Ph.D. students, Hannah Williams, Timothy Kluthe, and Tim Rafalski.

“We want to make this stuff possible to learn early on in high school or even younger, so that they don’t feel locked out of a space when they’re looking at colleges or possible career paths,” said Kluthe.

In addition to bringing participants to ������, Stefik and his research team have traveled to them. Last year, the team traveled to Washington state to work with visually impaired teachers at an annual conference. They also worked with high school students with a wide variety of disabilities at the DO-IT Summer Camp as part of a long-term collaboration with Brianna Blaser and Richard Ladner at the University of Washington. 

“Oftentimes, these disability issues sound niche, but they’re not. In our studies, we try to find a sweet spot in regard to how we best help everyone,” Stefik said. 

The team conducts some studies specifically with individuals with disabilities, which often inspire new ideas for helping others. From there, they step back and consider what universal principles can be applied to benefit everyone.

“The classic example is at the supermarket,” Stefik said. “It is true that people with wheelchairs benefit from curb cuts, but so does anyone using a shopping cart. This same idea applies way more often than people realize.”

A good example in computer science is block-based programming. Block-based programming is a kind of coding that’s easier for everyone to learn — not just those with disabilities. Instead of working with lines of text, block-based programming involves users manipulating codes by dragging and dropping blocks, which is more intuitive and friendly for novice coders. 

Originally designed as a purely visual tool, Stefik’s team — led by Allee and Contreras — spearheaded a way to make these visual ideas accessible even to users who cannot see the screen.

“Accessibility is often interpreted incorrectly to mean that it’s only for people with disabilities,” Stefik said. “But what disability work often highlights is that the system is messed up for everybody. Improvements help us all.”

Next Steps

The lab recently gained visibility with Google. Stefik and collaborators at the University of Washington from the tech giant to increase accessibility of Blockly, a block-based programming tool, for users with disabilities. Stefik’s project aims to help developers create more inclusive Blockly products.

This year, the team will travel to the Alabama School for the Blind and collaborate with researchers from Saint Louis University to teach young learners “an hour of code” — a programming activity that takes an hour to complete — that the team recently created using block-based language. The lesson will be focused on data science, with charts that are completely accessible.

“The state-of-the-art practice in data science today is just giving images a label, which has the buzzword of alt-text,” Stefik said. “With alt text, if you cannot see the chart, you have to hope a human being described it to you correctly, and that’s not very reliable. We invented a technology where when you generate a visualization, like a chart, you don’t label anything at all. It just uses behind-the-scenes math and algorithms to make it accessible automatically.

“I like to think about a future where people with disabilities only read about old technologies not being accessible and think it's odd,” he said. “I really do want them to say, ‘Oh right, I heard that old charts or visualizations were not accessible — how strange.’”

Kluthe remembers the first time he and his colleagues demonstrated the technology to a group of visually impaired teachers.

“One of the participants was amazed about being able to make their own chart from real data, and they were going to pass it off to a friend who was also visually impaired,” Kluthe said. “It really makes it feel like you’re helping people.”