Participants substantially overestimated their performance in all trace conditions, with the largest overestimation under full traces¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr2·q3·i1–i3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
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q3 i3 Perceived performance significantly exceeded actual performance in every condition (Answer-only d = .85; Full-trace d = 1.21; Summary-trace d = .97). → Fernandes 2026
q3 i1 The magnitude of overestimation differed significantly by condition, with Full-trace showing the largest bias (M = 2.44) versus Answer-only (M = 1.74). → Fernandes 2026 (2)
Evidence¶
Fernandes 2026¶
Fernandes, D., Buschek, D., Tankelevitch, L., Kosch, T., & Welsch, R. (2026). Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition. https://arxiv.org/abs/2605.25856 doi:10.48550/arxiv.2605.25856
q3 · i3 · causal · r2
Global performance estimates collected after all ten problems exceeded achieved performance in each condition; the Full-trace overestimation test printed d = 1.21, with Answer-only d = .85 and Summary-trace d = .97 reported alongside.
"InFull-tracecondition, participants estimated 7.91 items correct (𝑆𝐷= 1.71), while achieving 5.46 correct items, also showing significant overestimation,𝑡( 182)= 16.35,𝑝<. 001,𝑑= 1.21."
Fernandes 2026 (2)¶
Fernandes, D., Buschek, D., Tankelevitch, L., Kosch, T., & Welsch, R. (2026). Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition. https://arxiv.org/abs/2605.25856. doi:10.48550/arxiv.2605.25856
q3 · i1 · causal · r2
Omnibus ANOVA on overestimation (perceived minus achieved) was significant with η² = .021; Tukey-adjusted comparisons showed Full-trace overestimation significantly larger than Answer-only (Mdiff = 0.70, padj = .003), while Summary-trace did not differ from either.
"the magnitude of overestimation differed significantly by condition,𝐹( 2, 556)= 5.83,𝑝=. 003,𝜂2 =. 021."
Discussion¶
Related Claims¶
- Access to AI advice roughly doubled reported confidence in answers in one experiment — the general claim this finding bears on, with the studies behind it
- Full reasoning traces impaired task performance relative to both answer-only and summary-trace conditions in AI-assisted LSAT reasoning — related
- Full reasoning traces worsened calibration bias and Brier scores relative to both other conditions — related
- Hedonic appeal, not trust, carries the indirect path from trace exposure to performance overestimation, consistent with a processing-fluency account — related
- No trace format supported calibrated self-evaluation: perceived-achieved correlations were low and non-significant in all conditions — related
- Reasoning-trace exposure raised trust and hedonic appeal without performance benefits, shifting subjective appraisal of the interaction — related
- Summary traces preserved task performance at the answer-only baseline while elevating subjective appraisal — related
- Estimation errors for partner AI use are directionally biased for specific task types at t2 but not at t3 — related
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Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
overestimation-largest-under-full-traces |
title |
Participants substantially overestimated their performance in all trace conditions, with the largest overestimation under full traces |
description |
Participants substantially overestimated their performance in all trace conditions, with the largest overestimation under full traces |
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 |
2 — fernandes-2026, fernandes-2026-2 |
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