Table 3 Indicator validity.

Construct/Item	Indicator weight	Factor loadings/Cross-loadings
Construct/Item	Indicator weight	AISE	CT	ESC	GUC
Artificial intelligence self-efficacy (AISE)
AISE1	0.139	*0.872*	0.789	0.670	0.576
AISE2	0.119	*0.807*	0.691	0.544	0.549
AISE3	0.139	*0.909*	0.787	0.660	0.594
AISE4	0.131	*0.900*	0.733	0.618	0.606
AISE5	0.119	*0.855*	0.652	0.580	0.557
AISE6	0.121	*0.882*	0.663	0.571	0.600
AISE7	0.123	*0.886*	0.674	0.582	0.596
AISE8	0.128	*0.850*	0.668	0.664	0.556
AISE9	0.132	*0.854*	0.707	0.676	0.546
Critical thinking (CT)
CT1	0.197	0.707	*0.877*	0.608	0.590
CT2	0.213	0.760	*0.928*	0.682	0.619
CT3	0.205	0.736	*0.925*	0.689	0.552
CT4	0.212	0.766	*0.908*	0.678	0.610
CT5	0.202	0.707	*0.862*	0.698	0.544
CT6	0.129	0.462	*0.570*	0.455	0.327
Engineering students’ creativity (ESC)
ESC1	0.164	0.702	0.702	*0.841*	0.527
ESC2	0.149	0.604	0.652	*0.907*	0.514
ESC3	0.160	0.655	0.698	*0.925*	0.535
ESC4	0.153	0.640	0.660	*0.910*	0.514
ESC5	0.157	0.636	0.683	*0.920*	0.528
ESC6	0.156	0.639	0.683	*0.938*	0.507
ESC7	0.160	0.667	0.691	*0.928*	0.525
Generative artificial intelligence usage competence (GUC)
GUC1	0.159	0.463	0.450	0.389	*0.644*
GUC2	0.181	0.501	0.517	0.462	*0.830*
GUC3	0.154	0.425	0.449	0.383	*0.780*
GUC4	0.143	0.398	0.408	0.364	*0.768*
GUC5	0.192	0.524	0.527	0.530	*0.803*
GUC6	0.208	0.636	0.566	0.492	*0.843*
GUC7	0.218	0.656	0.602	0.520	*0.865*

Factor loadings are indicated by values in bold and italics; CA, Cronbach’s alpha; CR, Composite Reliability; AVE, Average Variance Extracted.

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