Motivation, conceptual understanding, and critical thinking as correlates and predictors of metacognition in introductory physics

Figures & data

Figure 1. Normal P-P plot of regression standardize the residuals.

Figure 2. Scatter plot.

Table 1. Correlation among metacognition, critical thinking, and conceptual understanding, and motivation

	1	2	3	4
Metacognition	1.000
Critical Thinking	.163*	1.000
Conceptual Understanding	.311**	.348**	1.000
Motivation	.439**	.071	.027	1.000

Note: ** p < .01, * p < .05.Correlation coefficients are based on Pearson’s product-moment correlation. N = sample size.

Table 2. Regression coefficients and correlations between predictor variables and metacognition

Model	Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Correlations			Collinearity Statistics
	B	Std. Error	Beta			Zero-order	Partial	Part	Tolerance	VIF
(Constant)	.543	.573		.948	.346
Critical Thinking	.007	.022	.032	.321	.749	.163	.036	.030	.875	1.143
Conceptual Understanding	.066	.023	.288	2.851	.006	.311	.304	.270	.879	1.138
Motivation	.532	.118	.429	4.517	.000	.439	.451	.428	.995	1.005

Note: Dependent Variable: Metacognition

Table 3. A one way ANOVA results for the relationship between predictors and metacognition

Model		Sum of Squares	Df	Mean Square	F	Sig.
	Regression	8.668	3	2.889	10.524	.000^b
	Residual	21.964	80	.275
	Total	30.632	83

Note: ^a: Dependent Variable: Metacognition

^b: Predictors: (Constant) Critical thinking, Conceptual understanding, Motivation

Table 4. Model summary for the relationship between predictors and metacognition

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Durbin-Watson
1	.532^a	.283	.256	.52398	1.745

Note: ^a: Predictors: (constant), critical thinking, conceptual understanding, motivation

^b: Dependent Variable: Metacognition