Edtech developers and vendors make claims that artificial intelligence can transform how students learn and how educators teach. But a recent Stanford University report found the evidence behind claims of efficacy remains limited — and can raise new concerns about how and if students are truly learning, according to a Government Technology article.
Despite the swift adoption of AI in schools, rigorous research on its impact on teaching and learning remain limited, the report emphasized. Most studies examine whether students using AI tools perform better, yet they do not isolate whether the tech itself caused those gains.
Stanford researchers relied on approximately 20 high-quality causal studies designed to determine whether AI directly drives changes in student outcomes.
“Causal research is the best way to tell how a tool, like an AI tool, impacts students and educators, and so that’s a different question than what you get by looking at survey data or just kind of descriptive outcomes,” says Lily Fesler, senior researcher at the AI Hub for Education at Stanford University, who co-authored the report.
That distinction matters for school leaders making decisions about adopting AI. Without causal evidence, improvements could be driven by factors like teacher experience, student motivation or classroom context, rather than the tool itself.
“I think the headline is, it’s still too early to know if this is doing school faster … or if it’s reimagining. I think research shows hints of both,” says another co-author of the report, Chris Agnew, who serves as managing director of the AI Hub for Education. “The headline is mixed, and it requires real intention and much further research.”
Much of the existing research reflects tools that are currently available, which are largely one-to-one, chatbot-style products, says Agnew. That data often does not capture how AI is actually implemented in classrooms.
Evidence for benefits of AI in education exists, but it mainly points to specific and limited benefits, particularly when students have access to step-by-step support and immediate feedback, according to both Agnew and Fesler.
Fesler says studies show AI tools can help students improve performance on structured tasks, such as improving math practice problems and providing feedback on student writing. AI also can reduce the time teachers spend on tasks like grading, lesson planning and feedback generations — sometimes by as much as 30 percent — without lowering lesson quality.
“We know that (AI) does save teachers time, but that doesn’t necessarily mean that teachers are spending less time [working] at home,” Fesler says. “So that means they’re reinvesting that time and spending it on other things that they think can support student learning in their classrooms.”
Agnew says there is broader potential in expanding access to AI and giving students more control over their learning. “I think there’s a real sense of agency that it can build in individuals,” he says, adding that AI could help support students with diverse learning needs.
What happens when AI is no longer available? This is the report’s most consistent concern.
Students often perform better while using AI tools but they struggle to replicate those results independently, and in many cases, gains appear to weaken or disappear once the tool is removed.
“Evidence is more mixed on whether students continue to perform well when the tools are taken away,” says Fesler.
“If students are really relying on the AI tools to just do the assignment for them, they’re thinking a little less, engaging less, during the task,” Fesler says. “Their performance on the task can improve … but they’re not necessarily internalizing and learning from that experience.”
“Areas that I’m concerned about are … the offloading of fundamental skill development, the erosion of critical thinking and a changing sense of self because of technology in young people,” says Agnew.
Tools that guide students through reasoning tend to produce better outcomes than those that generate answers outright. “It really depends on the pedagogical design of the AI tool,” Fesler says. “There are certainly ways that students can be cognitively engaged when using an AI tool, but it’s not a given. It needs to be designed into the tool.”
“I think any product that is making strong outcome claims should be heard cautiously, because, as we know, the research is very early,” Agnew says. Leaders should press vendors on whether tools improve learning independently and not just performance while students are using them.
Researchers also caution against replacing core elements of teaching with technology. “AI, being a tool that has promise, does not mean it’s better for kids to spend more time just in front of computers or their phone,” Fesler says. Relationships and in-person learning remain central.
Government Technology
