Negative example standards do not reliably improve judgment accuracy and significantly decrease relative accuracy in evaluating self-generated examples¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr2·q3·i1small
Currency · newest study 2023 · 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? Negative example standards showed no statistically significant main effect on bias or absolute accuracy. → Linda Froese 2023
q3 i1 Negative example standards significantly decreased rather than increased relative accuracy. → Linda Froese 2023 (2)
Evidence¶
Linda Froese 2023¶
Linda Froese, Julian Roelle. (2023). Expert example but not negative example standards help learners accurately evaluate the quality of self-generated examples. Metacognition and Learning. https://doi.org/10.1007/s11409-023-09347-w
q3 · i? · causal · r2
In the same ANCOVA on absolute accuracy, negative example standards showed no significant main effect, "F(1, 122) = 0.57, p = .450, ηp2 < .01". For bias the main effect was also non-significant (p = .057), though it became significant when the prior-knowledge outlier was retained.
"By contrast, there was no statistically significant main effect of negative example standards, F(1, 122) = 0.57, p = .450, ηp2 < .01, and also no statistically significant interaction effect, F(1, 122) = 1.57, p = .213, ηp2 = .01."
Linda Froese 2023 (2)¶
Linda Froese, Julian Roelle. (2023). Expert example but not negative example standards help learners accurately evaluate the quality of self-generated examples. Metacognition and Learning. https://doi.org/10.1007/s11409-023-09347-w
q3 · i1 · causal · r2
On relative accuracy, negative example standards had a significant but detrimental effect, "F(1, 114) = 4.45, p = .037, ηp2 = .03"; the authors report the resulting gamma correlation of G = -.02 indicates learners could not discriminate quality levels.
"We also found a statistically significant main effect of negative example standards, F(1, 114) = 4.45, p = .037, ηp2 = .03. Surprisingly, contrary to Hypothesis 1b, negative example standards decreased rather than increased relative accuracy."
Discussion¶
Related Claims¶
- Example quality does not significantly moderate the effects of the standards on judgment accuracy when aggregated across concepts — related
- Idea unit standards do not enhance judgment accuracy in evaluating self-generated examples — related
- Expert example standards improve university students' judgment accuracy (bias, absolute accuracy, and relative accuracy) when evaluating self-generated examples — related
- Providing expert example standards enhances absolute judgment accuracy in evaluating self-generated examples — related
- Providing expert example standards reduces bias in learners' evaluations of self-generated examples — related
- Expert example standards did not significantly enhance relative accuracy in evaluating self-generated examples — related
- Benefits of expert example standards depend on example quality: largest for incorrect examples, absent for correct ones — related
- Learners are substantially overconfident when evaluating the quality of their self-generated examples — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
negative-example-standards-inconsistent-effects |
title |
Negative example standards do not reliably improve judgment accuracy and significantly decrease relative accuracy in evaluating self-generated examples |
description |
Negative example standards do not reliably improve judgment accuracy and significantly decrease relative accuracy in evaluating self-generated examples |
status |
review |
evidence_strength |
mixed |
newest_evidence |
2023 |
generated |
by process:wiki-ingest on 2026-10-19 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — linda-froese-2023, linda-froese-2023-2 |
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