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 7 Unstandardised regression parameters for the perception and background to performance SEM (n=1583, November 2021, \(\chi ^2(124)=221.462\), \(p<0.001\), \(chi^2/{\text{df}}=1.79\), \({\text{CFI}}=0.951\), \({\text{TLI}}=0.923\), \({\text{RMSEA}}=0.022\), 90%\(ci=[0.017, 0.027]\), \({\text{SRMR}}=0.026\))

	Model
	Estimate	Std. Err.	Z	p	R²
Percentage (/100)					0.136
CS perception	\(-0.29\)	1.31	\(-0.22\)	0.824	0.707
Tablets perception	\(-0.04\)	0.99	\(-0.04\)	0.969	0.372
Robots perception	0.96	1.11	0.86	0.387	0.411
General self-efficacy	1.54	0.69	2.22	0.027
Gender (\(0=\) boys, \(1=\) girls)	\(-1.57\)	1.06	\(-1.47\)	0.141
Grade	7.53	0.53	14.19	0.000
Number of CS education periods SI	0.09	0.13	0.70	0.483
Number of ICT education periods	\(-0.02\)	0.08	\(-0.20\)	0.842
Number of Robotics education periods	\(-0.29\)	0.42	\(-0.68\)	0.496

Please note that on the smaller sample CS utility did not correlate highly with interest and self-efficacy and had to be removed from the model. For the full set of model parameters see Table 14 in Appendix B.2