Ryan Hansen , director of digital learning at Utah’s Davis School District , used an OpenAI tool to analyze a year of school results and prepare feedback for teachers. As a child, Hansen hated sitting still in class. Stories and field trips drew him in; he needed something he could see and touch. When he became a high-school biology teacher, he had students build DNA models from licorice ropes and marshmallows. If he couldn’t take them out into the world, he would bring something of it into the classroom.
After moving into administration, he entered a doctoral program at Utah State. An interesting point made during a lecture could send his mind racing through its applications; by the time he returned to the lecture, the teacher had moved on. Recordings let him rewind and rejoin the class. When advanced statistics outpaced his preparation, YouTube explanations helped him through. Those were two moments when technology supported his own learning.
At the Title I middle school where he was principal, serving low-income families, teachers of the same subject agreed on short daily quizzes and assignments. Those checks determined how children spent a flexible period: students who needed help returned to a teacher, while those caught up could return to music or try a hobby class. Hansen says the school’s year-to-year growth in math and English became the highest in Utah, even though its students weren’t outscoring those in wealthier neighborhoods. That’s where he saw the power of data-driven classrooms.
He later spent several years helping people with intellectual and physical disabilities find work, using technology to support communication and learning. A new superintendent then brought him in to direct digital learning and open an online school.
After a recent OpenAI workshop, Hansen uploaded a full year of the online school’s results, asking which subjects students struggled with and where teachers needed support. He can ask follow-up questions of the data to investigate those patterns. After years of trying tools to make sense of school data, he can begin by uploading a spreadsheet and asking questions instantly.
He says that sometimes a high failure rate in a teacher’s classes could once go unnoticed for months, until parents complained. But earlier analysis could give a principal a chance to investigate and help that teacher change course. He has shown his online-school principal how AI can draft feedback identifying a teacher’s strengths and areas to improve, giving their next conversation a starting point. He plans to train other principals in the coming weeks to examine their own schools’ results.
He wants teachers to use that speed to shorten the lapse between a child’s misunderstanding and responsive follow-on support. AI can help identify who needs more practice and draft the resources for it, while preparing new plans for children ready to advance. In special education, he sees the possibility of turning complex assessments into individualized learning goals; a teacher has already asked him for help drafting such a plan. She expects that help to save hours of work translating test results into learning goals for a child.
