Analyzing the associations between motivation and academic performance via the mediator variables of specific mathematic cognitive learning strategies in different subject domains of higher education

International Journal of STEM Education

Table 2 Descriptive statistics and bivariate correlations (N = 548)

	M	SD	Skew	Kurtosis	1	2	3	4	5	6	7	8	9	10	11
1. Academic self-concept	2.86	0.90	− 0.09	− 0.17	–
2. Curiosity	3.91	0.58	− 0.69	1.19	0.20	–
3. Repeating	3.59	0.95	− 0.28	− 0.60	− 0.01	0.23	–
4. Practicing	3.55	0.97	− 0.33	− 0.44	0.02	0.22	0.59	–
5. Building connections	4.01	0.74	− 0.80	1.12	0.03	0.39	0.12	0.07	–
6. Using examples	3.70	0.76	− 0.37	− 0.05	− 0.01	0.23	0.19	0.19	0.19	–
7. Connecting to practice	3.68	0.88	− 0.46	− 0.25	− 0.02	0.31	0.08	0.09	0.21	0.33	–
8. Using proofs	3.38	1.02	− 0.33	− 0.47	0.11	0.29	0.14	0.13	0.17	0.30	0.24	–
9. Simplifying	3.97	0.84	− 0.83	0.47	− 0.09	0.04	0.24	0.20	0.18	0.24	0.16	− 0.01	–
10. UEQG	4.01	0.54	− 0.38	− 0.06	0.22	0.11	− 0.01	0.06	0.13	− 0.07	0.03	0.09	− 0.02	–
11. Performance	3.70	0.89	− 0.81	0.28	0.20	0.13	0.03	0.12	0.08	− 0.04	0.04	0.07	− 0.01	0.35	–

Scales ranging from 1 (= strongly disagree) to 5 (= strongly agree). UEQG ranging from 2 (= lowest performance) to 5 (= best performance). Performance ranging from 1 (= lowest performance) to 5 (= best performance). Correlation (r) is shown below the diagonal
UEQG University entrance qualification grades