Classifying provided examples is more effective for learning relational categories than reading or generating examples¶
Claim · All claims
Evidence · 1 study · causalr2·q3·i3large
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 i3 Classifying provided examples led to better learning outcomes than reading or generating examples on the generation, inference, and definition recall tasks of the knowledge test. → 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 · i3 · causal · r2
A randomized experiment with N = 83 student teachers assigned to reading (n = 25), generating (n = 27), or classifying (n = 31) example formats. The planned contrast favoring classification was significant, "V = 0.290 (Pillai’s trace), F(4, 77) = 7.86, p < .001, ηp2 = 0.29", on all tasks except classification.
"The multivariate analysis was significant, V = 0.290 (Pillai’s trace), F(4, 77) = 7.86, p < .001, ηp2 = 0.29. Follow-up univariate analyses showed that the planned contrast was significant for all types of the tasks of the knowledge test with the exception of the classification task"
Discussion¶
Related Claims¶
- Reading provided examples is not more effective than generating examples for learning relational categories — related
- Correctness of generated and classified examples during learning correlates selectively with posttest task performance — related
- Generating examples produces overconfident judgments of learning, especially for principles and procedures — related
- Interleaving is especially useful for inductive, subtle pattern learning without a clear verbal rule, but can equal or exceed blocking in rule-based domains too — a broader claim this one bears on
- Learning relational categories becomes more difficult as the complexity of the knowledge type increases — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
classifying-examples-beats-reading-generating-relational-categories |
title |
Classifying provided examples is more effective for learning relational categories than reading or generating examples |
description |
Classifying provided examples is more effective for learning relational categories than reading or generating examples |
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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