Access to an LLM assistant during practice did not significantly lower subsequent unaided test performance¶
Claim · All claims
Evidence · 1 study · causalr3·q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? AI-only participants did not have significantly lower odds of answering a final test item correctly than control participants (OR = 0.80, p = .244). → Sebastian Maier 2026
Evidence¶
Sebastian Maier 2026¶
Sebastian Maier, Kai Schwabe, Manuel Schneider, and Stefan Feuerriegel. (2026). Designing Against Deskilling: Metacognitive Feedback Reduces Cognitive Offloading to LLM Assistants. arXiv. https://arxiv.org/abs/2609.20143 doi:10.48550/arxiv.2609.20143
q3 · i? · causal · r3
Confirmatory test of H1 comparing the AI-only condition (M = 0.62, SD = 0.34) with the no-AI control (M = 0.65, SD = 0.32) on the six unaided test items, using item-level mixed-effects logistic regression. The article reports no significant difference; equivalence was not tested.
"AI-only participants did not have significantly lower odds of answering a final test item correctly than control participants (𝑏=− 0.22,𝑆𝐸= 0.32,𝑂𝑅= 0.80, 95% CI[0.42, 1.51],𝑧=− 0.69,𝑝=. 244)"
Discussion¶
Related Claims¶
- How genAI is used, not who uses it, predicts whether independent performance declines or improves — the general claim this finding bears on, with the studies behind it
- Greater answer offloading during learning is associated with lower subsequent unaided performance (exploratory) — related
- In one preregistered experiment, metacognitive feedback on learners' own LLM use lowered the odds of answer offloading and raised the odds of a correct unaided answer on one-sided tests, with 95% intervals reaching no effect — related
- An effort-based reward did not significantly reduce answer offloading or improve unaided performance — related
- Unguarded answer-giving AI harmed unaided exam performance while a guarded version of the same model erased the harm (Bastani et al., 2025, as reported) — reports the opposite
- GenAI use weakens effort adjustment to incentives on subsequent unaided reasoning — related
- Prior genAI access shows only exploratory evidence of poorer subsequent unaided reasoning, within the no-incentive condition, and no preregistered main effect — related
- AI-assisted performance during skill-building does not transfer to subsequent unassisted performance — reports the opposite
- AI support can improve task performance while weakening users' metacognitive accuracy and leaving their own reasoning unimproved — related
- Participants deprived of relevant relational knowledge in Stage 1 take longer on the subsequent network-reasoning task — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
llm-access-no-significant-lower-unaided-performance |
title |
Access to an LLM assistant during practice did not significantly lower subsequent unaided test performance |
description |
Access to an LLM assistant during practice did not significantly lower subsequent unaided test performance |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — sebastian-maier-2026 |
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