Higher Education Institution

FEV Tutor further evolved last year when it announced a new AI-enhanced platform, Tutor CoPilot. The tool makes tutors more effective by giving them guiding questions to ask students. In a randomized trial, the National Student Support Accelerator at Stanford University, which studies tutoring models, found that when less-experienced tutors used the AI support, student math scores increased an average of 9 percentage points. 

Over the past couple of years, scaling well-researched solutions has been shown to also counter the negative effects of the pandemic, Loeb said, from widening achievement gaps and missed school time, to poorer social and emotional development. Her team recently launched the National Student Support Accelerator (NSSA) to address educational inequities resulting from the pandemic. NSSA conducts research on the most promising tutoring practices and works with district leaders and others to provide research-backed guidance on implementing high-impact tutoring. 

“Our students deserve this work,” Loeb said. “From our research, we learn so much about how to engage students and accelerate their learning. The practical, easy-to-use learnings from research need to reach decision makers so that our students can benefit.”

Tips by Text and NSSA are part of SCALE, Loeb’s new initiative at the Stanford Accelerator for Learning, a university-wide effort addressing some of the most challenging issues in education through research, partnerships, and technological innovation. 

In early 2024, initial reports indicated that tutoring might not only help kids catch up academically after the pandemic but could also combat chronic absenteeism. More recent research, however, suggests that prediction may have been overly optimistic.

Stanford University researchers have been studying Washington, D.C.’s $33 million investment in tutoring, which provided extra help to more than 5,000 of the district’s 100,000 students in 2022-23, the second year of a three-year tutoring initiative. When researchers looked at these students’ test scores, they found minimal to modest improvements in reading or math.

“We weren’t seeing a ton of big impacts on achievement,” said Monica Lee, one of the Stanford researchers. “But what we were seeing at that point in time were promising findings that the tutoring might be doing something for attendance.” 

Today, Mayor Muriel Bowser and the Office of the State Superintendent of Education (OSSE) announced a new round of grant and contract awards totaling more than $7 million to fund high-impact tutoring (HIT) programs for over 6,000 students across 90 DC Public Schools and public charter schools during the 2024-25 school year. This strategic investment includes $4.3 million in grants to 16 DC local education agencies (LEAs) and over $3 million in contracts with 11 qualified HIT providers and one strategic supports partner.  

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Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.  

That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil. 

The paper suggests that tutoring initiatives may successfully adapt to the challenges of cost and scale. Another hopeful piece of evidence appeared this spring, when Stanford University researchers found that a “small burst” program in Florida produced meaningful literacy gains for young learners through micro-interactions lasting just 5–7 minutes at a time. If the success of such models can be replicated, there’s a chance that the benefits of tutoring could be enjoyed by millions more students.

Generative AI, including Language Models (LMs), holds the promise to reshape key sectors like education, healthcare, and law, which rely heavily on skilled professionals to navigate complex responsibilities. In education, for instance, effective teacher training with expert feedback is crucial yet costly, limiting opportunities to enhance educational quality on a larger scale.