Claims

Reading provided examples is not more effective than generating examples for learning relational categories

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2022 · 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? The planned contrast testing whether reading examples beats generating examples was not significant on the multivariate test or any univariate follow-up. → Tim M. Steininger 2022

Evidence

Tim M. Steininger 2022

Tim M. Steininger, Jörg Wittwer, Thamar Voss. (2022). Classifying Examples is More Effective for Learning Relational Categories Than Reading or Generating Examples. Instructional Science. https://doi.org/10.1007/s11251-022-09584-7

q3 · i? · causal · r2

In the same N = 83 experiment, the learning-by-reading hypothesis was tested with a planned contrast (reading +1, generating −1, classifying 0). The result was "not significant, V = 0.038 (Pillai’s trace), F(4, 77) = 0.76, p = .277"; no effect size beyond ηp2 = 0.04 was interpreted.

"The multivariate analysis was not significant, V = 0.038 (Pillai’s trace), F(4, 77) = 0.76, p = .277 ηp2 = 0.04. Follow-up univariate analyses were also not significant (see Table 3). Hence, reading examples was not more effective than generating examples."

Discussion

Page metadata
Field Value
type claim
id reading-not-superior-to-generating-examples
title Reading provided examples is not more effective than generating examples for learning relational categories
description Reading provided examples is not more effective than generating examples for learning relational categories
status review
evidence_strength moderate
newest_evidence 2022
generated by process:wiki-ingest on 2026-10-18
trust unverified — no one has confirmed this page's content
sources 1 — tim-m-steininger-2022

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