Effect sizes of multiple intelligence practices are highly heterogeneous across studies¶
Claim · All claims
Evidence · 1 study · quant-synthesisr2·q3
Currency · newest study 2015 · 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 homogeneity test showed heterogeneous distribution of success data (Q=518,665, p<0,001; I2 above 75%). → Eyüp Yurt & Seyat Polat 2015
Evidence¶
Eyüp Yurt & Seyat Polat 2015¶
Eyüp Yurt & Seyat Polat. (2015). The Effectiveness of Multiple Intelligence Applications on Academic Achievement: A Meta-Analysis. Journal of Social Studies Education Research 6(1), 84-122. https://eric.ed.gov/?id=EJ1105368
q3 · i? · quant-synthesis · r2
Homogeneity test across the 81 comparisons in the meta-analysis. The article reports the Q statistic and states that I2 values bigger than 75% show the distribution of effect values is "highly heterogeneous".
"On the other hand, Q value which was calculated with homogeneity test showed that distributions of the success data have a heterogeneous structure (Q=518,6 65, p<0,001)."
Discussion¶
Related Claims¶
- Effect sizes across primary studies are highly heterogeneous (Q = 283.659, I² = 77%), justifying the random-effects model — related
- Effect sizes across the included studies are highly heterogeneous (I² = 91.37%), indicating moderating factors — related
- Individual studies of digital story effects are highly heterogeneous, requiring a random effects model — related
- Effect size distributions across AR-in-education studies were heterogeneous (Q=35.692, I²=60.776%), requiring a random effects model — related
Page metadata
| Field | Value |
|---|---|
status |
review |
generated |
by process:wiki-ingest on 2026-10-31 |
trust |
unverified — no one has confirmed this page's content |
Frontmatter is the page's machine-readable record — see the Schema & Guide.