Non-verbal intelligence measures (Raven, WISC Block Design) are non-significant math predictors when well-specified spatial and memory measures are in the model¶
Claim · All claims
Evidence · 1 study · associationalr2·q3
Currency · newest study 2014 · not yet checked against its sources · not reviewed by a person
Subclaims¶
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q3 i? Raven and WISC Block Design remained non-significant even when entered without the other non-verbal IQ variable, and did not change model R2. → Szűcs Dénes 2014
Evidence¶
Szűcs Dénes 2014¶
Szűcs Dénes, Devine Amy, Soltesz Fruzsina, Nobes Alison, Gabriel Florence. (2014). Cognitive components of a mathematical processing network in 9-year-old children. Developmental Science. https://doi.org/10.1111/desc.12144
q3 · i? · associational · r2
Model refinement regressions (M2–M5, N = 98) adding IQ variables to the five significant predictors; only WISC Vocabulary was significant (M2 β = 0.18, p = .0156), while Raven and Block Design were non-significant and model R2 stayed at 0.68.
"Raven (Table4; M4 and Figure2D) and WISC Block Design (Table4; M5 and Figure2E) remained non-significant even when they were entered into the regression without the other non-verbal IQ variable."
Discussion¶
Learner Variables¶
- General Cognitive Ability — predictor: learners who differ on it differ in outcomes
Related Claims¶
- Results provide no support for the IQ-achievement discrepancy model of dyslexia; non-verbal IQ correlated with all Year-1 language measures — related
- Neither IQ nor WMC significantly predicted early mathematics when both were in the same model, explaining only about 5% of variance — related
- In latent-variable SEM models, intelligence — not working memory — is the significant direct predictor of academic outcomes in both childhood and early adulthood — reports the opposite
- When previous academic achievement is controlled, intelligence predicts only later reading comprehension and age-10 mathematics, and WMC predicts nothing additionally — related
- IQ and working memory are reliable predictors of academic achievement at the beginning of school when domain knowledge is not controlled — reports the opposite
- Number sense measures are non-significant predictors of math once more robust predictors are included — related
- Block Play Predicts Math Achievement — related
- Previous domain knowledge accounts for most of the variance in later achievement, considerably reducing the predictive impact of IQ and WM — related
- Verbal STM/WM and several executive and sensorimotor measures show no robust relation with math in children with normal reading skill — related
- Visuo-spatial working memory and inhibition jointly predict mathematics performance in 9–10-year-old children — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
nonverbal-iq-nonsignificant-math-predictor |
title |
Non-verbal intelligence measures (Raven, WISC Block Design) are non-significant math predictors when well-specified spatial and memory measures are in the model |
description |
Non-verbal intelligence measures (Raven, WISC Block Design) are non-significant math predictors when well-specified spatial and memory measures are in the model |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2014 |
generated |
by process:wiki-ingest on 2026-10-17 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — szűcs-dénes-2014 |
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