Claims

MIT-based instruction shows a large overall positive effect on students' academic achievement in a meta-analysis of 75 Turkish experimental theses and dissertations

Claim · All claims
Evidence · 1 study (2 entries) · quant-synthesis r2 · q2 · i3 large
Currency · newest study 2016 · 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.

q2 i3 Random effects meta-analysis yields an overall effect size of d = 1.077 (95% CI 0.921–1.232), large by Cohen's classification, significantly favoring MIT-based instruction. → Baş 2016 q2 i? Effect sizes across the 75 studies were heterogeneous (Q(74) = 458.793, p < .001), so a random effects model was adopted. → Baş 2016 (2)

Evidence

Baş 2016

Baş, G. (2016). The effect of multiple intelligences theory-based education on academic achievement: A meta-analytic review. Educational Sciences: Theory & Practice, 16, 1833–1864. https://doi.org/10.12738/estp.2016.6.0015

q2 · i3 · quant-synthesis · r2

Random effects synthesis of 75 experimental theses and dissertations on MIT-based instruction in Turkey, coding pretest/posttest means and SDs into Hedges' g. The effect was "d = 1.077", significant by Z-test, and large under Cohen's (1992) classification.

"When the total number of 75 studies included in the meta-analysis were compared according to the random effects model, the standard error was found to be 0.079 and the upper limit in the 95% confidence interval was 1.232, while the lower limit was 0.921 with an effect size of d = 1.077"

Baş 2016 (2)

Baş, G. (2016). The effect of multiple intelligences theory-based education on academic achievement: A meta-analytic review. Educational Sciences: Theory & Practice, 16, 1833–1864. https://doi.org/10.12738/estp.2016.6.0015

q2 · i? · quant-synthesis · r2

Cochran's Q heterogeneity test on the pooled effect sizes. The variance "is larger than can be explained by simple sampling error", so the random effects model was adopted rather than the fixed effects model.

"This Q value indicates that the distribution of effect sizes in this collection of studies was heterogeneous, Q (74) = 458.793, p < .001"

Discussion

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