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Table 12 ANOVA of student learning data with Benjamini–Hochberg p-value correction and minimum effect size (Cohen’s D) that can be detected with the sample

From: How are primary school computer science curricular reforms contributing to equity? Impact on student learning, perception of the discipline, and gender gaps

Independent variable

Sum of squares

Degrees of freedom

F

Number of groups

Residual degrees of freedom

p

Min Cohen’s D

Significant difference (effect size and Dunn’s post hoc test for interaction effects)

Time

3357

1

137.9

2

2636

0.0000

0.109

Post-test > Pre-test

\(\Delta =+2.256pts\), \(p<0.0001\), Cohen’s \(D=0.457\)

Grade

4007

1

166.3

2

2636

0.0000

0.109

Grade 4>3

\(\Delta =2.468pts\), Cohen’s \(D=0.502\)

Gender

199

1

7.8

2

2636

0.0052

0.109

Boys > Girls

\(\Delta =0.551pts\), \(p=0.0015\), Cohen’s \(D=0.109\)

Time:grade

7396

3

108.0

4

2634

0.0000

0.129

See Fig. 3

Time:gender

3565

3

48.9

4

2634

0.0000

0.129

Pre-test Boys > Girls

\(\Delta =0.664pts\), \(p=0.0079\), Cohen’s \(D=0.131\)

Post-test Boys \(\sim\) Girls

\(\Delta =0.438pts\), \(p=0.0744\), Cohen’s \(D=0.091\)

Grade:gender

4248

3

58.9

4

2634

0.0000

0.129

Grade 3 Boys > Girls

\(\Delta =0.725pts\), \(p=0.004\), Cohen’s \(D=0.145\) Grade 4 Boys \(\sim\) Girls

\(\Delta =0.469pts\), \(p=0.0604\), Cohen’s \(D=0.098\)

Time:grade:gender

7660

7

48.1

8

2630

0.0000

0.148

See Fig. 3