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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.
High-impact tutoring has the strongest evidence base of any approach for improving student learning, and contributes to increased engagement and attendance. As far as proven education solutions go, it’s a pretty darn good one, and has rightfully been a bipartisan priority since the pandemic.
But federal pandemic relief money that helped fuel the expansion of such programs dried up in September, and recent research has sparked debates about the high-impact tutoring’s effectiveness when implemented at scale. This includes an evaluation of Metro Nashville Public Schools’ tutoring program that reported small gains for students and a meta-analysis of large high-impact tutoring programs that showed challenges in maintaining evidence-based practices.
An AI-powered tutoring assistant increased human tutors’ capacity to help students through math problems and improved students’ performance in math, according to a Stanford University study.
The digital tool, Tutor CoPilot, was created by Stanford researchers to guide tutors, especially novices, in their interactions with students.
The study is the first randomized controlled trial to examine a human-AI partnership in live tutoring, according to the researchers. The study examines whether the tool is effective for improving tutors’ skills and students’ math learning.
At a White House event today, Domestic Policy Advisor Neera Tanden, in coordination with the U.S. Department of Education (Department), AmeriCorps, and the Everyone Graduates Center at the Johns Hopkins University, will announce that the National Partnership for Student Success (NPSS) has exceeded President Biden’s call to recruit an additional 250,000 adults into high-impact student roles by summer 2025 to support academic success for all students. These roles range from tutors, mentors, student success coaches, postsecondary transition coaches, and wraparound/integrated student support coordinators. As of the end of the 2023-2024 school year, an additional 320,000 adults have stepped into these roles in schools, exceeding the President’s goal and doing so a year early.
Students whose tutors used Tutor CoPilot were 4 percentage points more likely to progress through math tutoring session assessments successfully compared to students whose tutors did not have AI assistance, the study found.
The approach particularly benefited lower-rated and less-experienced tutors, researchers said. Students of lower-rated tutors who used the AI assistance increased their math proficiency up to 9 percentage points on average compared to students learning from lower-rated tutors without AI assistance.
The study included 900 tutors and 1,800 elementary and secondary school students from a large school district in the South. Stanford partnered with tutoring company FEV Tutor to pilot the tool’s implementation.
Here’s how it works: A tutor presents a subtraction problem to a student. If the student answers incorrectly, the tutor can activate Tutor CoPilot, which will recommend that the tutor ask the student to identify the numbers in the problem or suggest the student draw the items that need to be subtracted.
An AI-powered digital tutoring assistant designed by Stanford University researchers shows modest promise at improving students’ short-term performance in math, suggesting that the best use of artificial intelligence in virtual tutoring for now might be in supporting, not supplanting, human instructors.
The open-source tool, which researchers say other educators can recreate and integrate into their tutoring systems, made the human tutors slightly more effective. And the weakest tutors became nearly as effective as their more highly-rated peers, according to a study released Monday.
Tutored by Teachers ("TbT"), a leading provider of personalized virtual instruction, has been awarded the prestigious Tutoring Program Design Badge from the National Student Support Accelerator ("NSSA"). This recognition highlights TbT's commitment to maintaining rigorous standards in tutor selection, program efficacy, and school partnerships. It also supports the company's ongoing expansion as TbT introduces new instructional supports designed to meet the evolving needs of diverse student populations.
You can’t argue with data. Research shows that high-dosage tutoring is one of the most effective ways to help students make academic progress. Yet few students actually receive it. A recent study from Stanford University demonstrated the many positive effects of tutoring, including increased reading and math scores, attendance and a feeling of belonging. Teach For America’s (TFA) tutoring program, the Ignite Fellowship, finds and develops tutors who connect virtually with students during the school day. Fellows, who are paid for their work, are supported by a school-based veteran educator to customize instruction. Seventy-one percent of the 3,500 students across the country being tutored by Ignite fellows meet their semester-long reading and math goals.
Since 2022, public schools in the District of Columbia have been working to mitigate Covid learning disruptions by establishing and ramping up high-impact tutoring (HIT) efforts. Data on the outcome of these efforts are beginning to emerge, and a new report from the National Student Support Accelerator (NSSA) shows some minimally encouraging signs.
NSSA is an offshoot of the Stanford Accelerator for Learning and Systems Change for Advancing Learning and Equity, an initiative focused on researching how tutoring can best benefit students. Its new report looks at the first full year of HIT implementation in D.C. schools during 2022–23. Tutoring efforts that year concentrated on math and English language arts (ELA) for students in all grades and was focused on schools—both district and charter—with the greatest concentrations of students identified as at risk. It’s interesting to note that “at risk” doesn’t generally mean academic risk for schools in the district, but rather centers primarily on student socioeconomic status and homelessness, in the context of this wholly-academic intervention. Pre-existing academic need appears not to have been a driving force in choosing where tutors were placed, although some data suggest that academic performance may have influenced teachers’ decisions on which students to refer for tutoring.