UAlbany Professor Tests AI Tool That Tells Teachers How to Improve
ALBANY — Jonathan Foster, a professor at the University at Albany and a former high school math teacher, is harnessing artificial intelligence to improve math instruction. However, Foster’s focus isn’t on tutoring students; instead, he’s developing an AI tool to provide constructive feedback to teachers.
“I wanted that feedback from a peer or an instructional coach but I didn’t always have access to that,” Foster said, reflecting on his time in the classroom.
Teachers often report a scarcity of feedback on their teaching practices. While new teachers frequently have mentors, these mentors typically have their own full classrooms and can only offer brief observations. Principals also observe classrooms, but these visits are infrequent. This limited oversight can hinder a teacher’s ability to refine their approach, according to Foster.
“I didn’t have the ability to collect all the data that I wanted in my classroom environment,” he explained. This is where AI steps in.
The AI tool, using cameras and audio recordings, assesses various aspects of a teacher’s performance. It monitors whether the teacher moves throughout the classroom, how frequently they use group work, and tracks the language used by both teachers and students.
“Am I engaging with student reasoning, am I asking students to explain their reasoning, am I giving my students opportunities to use rich mathematical vocabulary, am I using rich mathematical vocabulary?” Foster explained, describing the parameters the AI evaluates.
The AI’s assessments are based on the mathematical quality of instruction, a metric developed by Harvard University’s Center for Education Policy Research. This measure is often used to score teachers during supervisor observations, yet the AI tool offers the advantage of providing daily feedback.
“I hope we’re helping teachers think more critically about their practice or shift their practice to high-quality instruction,” Foster said. The AI tool can provide teachers with ongoing insights without being tied to performance evaluations.
The project, funded by a $1.4 million grant from the Bill & Melinda Gates Foundation, is led by Peter Youngs and Scott Acton of the University of Virginia. Early-career teachers are currently testing the tool and will continue to use it throughout the school year beginning this fall. Researchers, including Foster, will establish a baseline measurement and observe any resulting improvements.
“See if we notice any subtle changes in their practice,” Foster said. For instance, the AI might suggest a teacher “move around and monitor and check in on their progress more” during group work.
“Is she making those small adjustments in her practice that could become big?” he added.
While teachers have been generally receptive to the tool, Foster added that they’ve also noted that the AI isn’t perfect and doesn’t catch everything.
Foster stresses that the AI tool’s focus is on teacher development. He believes that the most effective teaching is a human endeavor.
“I see the act of teaching as such a human endeavor,” he said. “I see teaching as an inquiry and a science and an art.”
