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It’s been a year since ChatGPT stormed into classrooms. Its most common users have been students looking for homework aid—or shortcuts—and teachers who use it to create tailored, on-the-spot lesson plans.

A group of researchers, though, are asking a new question: Can generative AI help teachers teach better?

New research released in November shows that when teachers engage with frequent, personalized and on-demand feedback about their teaching practice, they ask richer, more analytical questions in their mathematics or science classes. The study, conducted by researchers from the University of Maryland, Harvard University, and Stanford University, also found that teachers engaged with feedback when it was directly emailed to them, suggesting that feedback needs to be provided in a succinct and accessible manner.

With technological breakthroughs in generative AI happening at unparalleled speed, it’s useful to remember the social nature of education and the consequent importance of teachers.

The free exchange of ideas through small-group work, the laughter that takes place naturally in the classroom, the curious eyes, and the raised hands—all reflect human learning. When the social elements are missing or compromised, as they were during COVID-19 school building closures, it is challenging for schools to help students engage and learn.

Students of color continue to be disciplined at higher rates than their white peers for the same behaviors—so much so that last month the Biden Administration warned schools that inequitable discipline practices could violate federal civil rights laws.

The top 5 percent of teachers most likely to refer students to the principal’s office for disciplinary action do so at such an outsized rate that they effectively double the racial gaps in such referrals, according to new research released today. These gaps are mainly driven by higher numbers of office discipline referrals (ODRs) issued for Black and Hispanic students, compared to White students.

Chalk up another entry on the list of jobs that artificial intelligence might be able to take on in schools: instructional coaching.

New research shows that receiving feedback from an AI observer prompts teachers to engage more deeply with students during class—leading them to more regularly acknowledge student contributions and encourage their questions.

Studies published by the EDSI team before the center's founding demonstrate the effectiveness of automated feedback in improving instructional quality and student outcomes, especially for online learning. Recent papers by Liu and colleagues also show that AI-generated feedback can support teachers in reflecting and making data-informed improvements without the time constraints of traditional person-to-person coaching models. EDSI is also looking into how AI can complement this human feedback.

“It was important to establish a center that would both support AI use in improving teaching and learning and prepare students for an AI-infused future,” Liu said in a public statement. “We wanted a space that would allow us to look at persistent educational challenges, such as declining literacy rates, chronic absenteeism and diverse learning styles, and consider the unprecedented technological possibilities that could address these challenges.”