Claims

Erroneous examples improve conceptual understanding by forcing comparison with correct models.

Claim · All claims
Evidence · 2 studies · 1 causal r?, 1 quant-synthesis r? · q3
Currency · newest study 2017 · not yet checked against its sources · not reviewed by a person

Studying a hypothetical peer's incorrect solution and being prompted to find, explain, and fix the error leads to deeper conceptual understanding, as it requires learners to discriminate between correct and incorrect features of a problem.

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? Analyzing and explaining errors in erroneous examples improves conceptual knowledge and procedural transfer more than studying correct examples alone. → Rittle-Johnson 2017 q3 i? In a brief tutoring session, comparing correct and incorrect examples improved fourth- and fifth-grade students' (N = 74) correct procedures and key concepts for decimal magnitude more than comparing correct examples only. → Durkin & Rittle-Johnson 2012

Evidence

Primary evidence link: https://doi.org/10.1007/s11858-017-0834-z

Rittle-Johnson 2017

Rittle-Johnson, B. (2017). Promoting self-explanation to improve mathematics learning: A meta-analysis and instructional design principles. ZDM Mathematics Education, 49(4), 599–611. https://doi.org/10.1007/s11858-017-0834-z

q3 · meta-analysis · i? · no source text available to check; the entry prints no effect size · n=N/A · quant-synthesis · r?

The meta-analysis highlights erroneous examples as a key instructional tool for prompted self-explanation, finding that it is particularly effective for improving conceptual understanding and transfer.

Durkin & Rittle-Johnson 2012

Durkin, K., & Rittle-Johnson, B. (2012). The effectiveness of using incorrect examples to support learning about decimal magnitude. Learning and Instruction, 22(3), 206–214. https://doi.org/10.1016/j.learninstruc.2011.11.001

q3 · peer-reviewed experimental study · i? · no effect size in the abstract · n=74 fourth- and fifth-grade students · causal · r?

Fourth- and fifth-grade students (N=74) learned decimal magnitude in a brief tutoring session. Comparing correct and incorrect examples improved correct procedures and key concepts relative to comparing correct examples only; the published abstract reports no interaction with prior knowledge. This page's earlier n=116 and “middle-schoolers” descriptions do not match the source abstract.

Studies bearing on this claim

Does setting an incorrect or non-matching case beside a correct one help learners more than correct examples alone? This table gathers the studies behind this claim and the 5 narrower claims that bear on it: 9 distinct studies (4 causal, 2 quant-synthesis, 1 review, 1 design, 1 qualitative), q2–q4, 1 of 9 with an effect size coded. One row per study, codes as each entry records them; no effect is averaged and no verdict is drawn. Built by scripts/synthesize_claim.py from eval/synthesis/; a row that looks wrong is fixed on the claim it comes from.

Study Design Effect as recorded Bears on this claim through
Rittle-Johnson 2017 q3 · quant-synthesis · r? i? this claim
Durkin & Rittle-Johnson 2012 q3 · causal · r? i? this claim
Alfieri et al. 2013 q4 · quant-synthesis · r? i2 · medium effect, d=0.50, 95% CI [.44, .56] Comparing cases side by side improves learning and transfer by a moderate average amount, (qualifies)
Gentner et al. 2003 q3 · causal · r? i? Comparing cases side by side improves learning and transfer by a moderate average amount, (qualifies)
Rittle-Johnson & Star 2007 q3 · causal · r? i? Comparing cases side by side improves learning and transfer by a moderate average amount, (qualifies)
Loibl 2017 q3 · review · r? i? PS-I fosters learning only if specific design features (contrasting cases or building inst (supports)
Deliang Wang and Cunling Bian 2026 q2 · design · r2 i? Students perceived the teacher’s modeling with contrasting cases as a turning point that r (supports)
Wei J and Shang Y 2026 q2 · causal · r? i? Error correction supports learning when it requires substantive cognitive work such as exp (qualifies)
rq3-reflections q3 · qualitative · r3 i? Students report code understanding, debugging, and AI-limitation awareness as primary lear (qualifies)

Discussion

A design precaution, not a finding of the studies recorded here: erroneous examples may be confusing or overloading for learners with no prior knowledge of the topic, so some designers reserve them for learners with at least some prior knowledge. Neither entry tests this: the Durkin & Rittle-Johnson (2012) abstract reports no interaction with prior knowledge.

Page metadata
Field Value
type claim
id erroneous-examples-build-conceptual-knowledge
title Erroneous examples improve conceptual understanding by forcing comparison with correct models.
status review
evidence_strength moderate
newest_evidence 2017
generated by process:wiki-ingest on 2026-04-06
trust unverified — no one has confirmed this page's content
sources 2 — rittle-johnson-2017, durkin-rittle-johnson-2012

Frontmatter is the page's machine-readable record — see the Schema & Guide.