When people talk about AI in schools, they mostly talk about a few places: top universities, well-funded school districts in cities, and tech accelerators with fancy websites. What’s going on in small towns, farming communities, and parts of Ohio and Kansas where broadband is still a luxury and a computer science teacher is worth their weight in gold doesn’t make the news very often. That is the exact gap that Wright State University wants to fill. It was just given $2.5 million by the U.S. Department of Education to do this.
The federal grant lasts for four years and comes from the Department’s Fund for the Improvement of Postsecondary Education. It helps a project that is officially named “Strengthening American Competitiveness with AI Education.” The name sounds a bit formal, which is typical for federal project names, but the goal is real. Together with Kansas State University and the University of Florida, Wright State is building a pipeline for AI literacy that starts in school with rural students, gets more in-depth in college, and continues into the workforce. It’s not a very exciting plan. There isn’t a famous backer. But it could be one of the most important education programs to start this year.
The project’s leader, Cogan Shimizu, an assistant professor of computer science at Wright State, made it clear: the goal is not just to teach students how to use an AI tool by clicking the right buttons. They will learn how these systems work, where they fall short, and when to believe in them. “Students won’t just learn how to use AI,” Shimizu said, “but also how AI systems work, how to reason about them and their behaviors, when they can be trusted and when they are the best tools for the job.” That difference between “use” and “understand” is more important than it seems at first.
Neurosymbolic AI is one of the more interesting parts of this project from a technical point of view. Together, neural systems like machine learning and large language models are used in this method, along with symbolic systems like knowledge graphs and expert reasoning structures. In real life, the point is dependability. When AI tools are used in schools, they should make fewer mistakes, not more. Neurosymbolic methods are made with this stability in mind. This is a smart choice for a school setting, and it shows that the people working on the project know what’s at stake.
As I watch this happen, I get the impression that rural areas have been forgotten in the national conversation about AI. Shimizu agreed with this and said that both Ohio and Kansas have large rural populations full of people who are really interested in starting their own businesses but who are having a harder time getting the kind of AI education that students in cities take for granted more and more. The fact that Kansas State already has a network in place in rural Kansas makes the partnership feel less like a school project and more like a real attempt to reach out.
The project will also teach people how to teach. Teacher training will start this summer with the goal of helping them use AI in the classroom while also giving them a basic understanding of how the technology works. Every year, three students from Wright State will directly join the effort. They will help plan the curriculum, build AI tools, and gain teaching experience. There is a real feedback loop between learning and doing because of that small number.
It’s still not clear how far the effects will spread or if four years will be enough time to make a real difference in places where school resources have been tight for decades. But Wright State Provost Jim Denniston’s way of putting it—that this is about national competitiveness, not just local chance—makes sense. By 2026, learning about AI will no longer be a fun activity. It’s more like a skill for survival. And students who don’t get it as kids aren’t just behind the times. It costs too much for them to go into the future.
