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

International Journal of STEM Education

Table 11 Hierarchical linear model for student learning (dependent variable: Delta between pre- and post- test scores, n=989) with significant variables in bold

	Estimate	95% ci	Std. error	Degrees of freedom	t-value	p-value
(Intercept)	7.11	[5.08, 9.15]	1.04	922	6.86	p < 0.0001
Pre-test score	− 0.379	\([-0.52, -0.24]\)	0.0722	922	\(-5.25\)	p < 0.0001
Gender (girls)	0.697	\([-1.62, 3.01]\)	1.18	922	0.591	0.555
Grade (4)	1.15	\([-1.97, 4.27]\)	1.55	45	0.741	0.462
NCS	0.122	\([-0.43, 0.68]\)	0.275	45	0.442	0.661
Pre-test score:gender (girls)	\(-0.0221\)	\([-0.20, 0.16]\)	0.0906	922	\(-0.243\)	0.808
Pre-test score:grade (4)	\(-0.0383\)	\([-0.24, 0.16]\)	0.101	922	\(-0.377\)	0.706
Gender (girls):grade (4)	\(-0.880\)	\([-4.52, 2.76]\)	1.86	922	\(-0.474\)	0.636
Pre-test score:NCS	\(-0.00386\)	\([-0.04, 0.04]\)	0.0198	922	\(-0.194\)	0.846
Gender (girls):NCS	\(-0.346\)	\([-0.96, 0.26]\)	0.311	922	\(-1.11\)	0.267
Grade 4:NCS	\(-0.260\)	\([-1.22, 0.70]\)	0.478	45	\(-0.544\)	0.589
Pre-test score:Gender (girls):Grade (4)	0.0308	\([-0.23, 0.29]\)	0.131	922	0.235	0.814
Pre-test score:gender (girls):NCS	0.0224	\([-0.03, 0.07]\)	0.0255	922	0.876	0.381
Pre-test score:grade (4):NCS	0.00979	\([-0.05, 0.07]\)	0.0326	922	0.300	0.764
Gender (girls):grade (4):NCS	0.195	\([-0.91, 1.30]\)	0.562	922	0.347	0.729
Pre-test score:gender (girls):grade (4):NCS	\(-0.0129\)	\([-0.09, 0.07]\)	0.0412	922	\(-0.313\)	0.755

\(R^2=0.285\), \({\text{RMSE}}=2.89\), \({\text{AIC}}=5132\), \({\text{BIC}}=5225\), log-likelihood\(=-2547\). NCS number of CS activities taught. Random effects \(\sigma ^2=8.85\), \(\tau _{class}=0.00\), \(\tau _{school}=1.50\) for 55 classes in 7 schools