The research question investigated was:
Is the relationship between math teacher's self-efficacy and perceptions of collective responsibility moderated by math teachers perception of principal support?
The following hypothesis were formulated:
Ha0 : The relationship between math teacher's self-efficacy and perceptions of collective responsibility is not moderated by math teachers perception of principal support.
Ha1: The relationship between math teacher's self-efficacy and perceptions of collective responsibility is moderated by math teachers perception of principal support.
A multiple regression was run to text the linear relationship between the independent and dependent variable (math teacher's self-efficacy and perceptions of collective responsibility), and further to test for the moderating effect of the moderator variable (math teachers perception of principal support). All the variables were continuous, making regression analysis suitable. Below is the regression equation for the study:
Yi = b0 + b1X1i + b2X2i + Ei
The output depicting the moderation is shown in table 1 below.
The b coefficient of .165 suggests that high teacher perception of collective responsibility is associated with high math teacher self-efficacy. These variables have a positive significant association (r=.178, P=.000) (Cohen et al., 2013). When teachers perceptions of principal support is added to the equation, the b-coefficient becomes 0.063 and r=0.00. These results affirm a significant positive association . It is therefore evident that the added variable (teachers perception of principal support) has a positive moderation effect on the relationship between math teacher's self-efficacy and perceptions of collective responsibility. The relationship is affirmed by a beta co-efficient of .063 when teachers perception of collective responsibility is excluded from the regression equation, as shown in the table below.
Table 2: Excluded variables
The resulting regression equation is:
Self-Efficacyi = 0.065 + .165 Collective responsibility + .062 Principal support + 0.08
Regression equation assumes that there is no multicollinearity, and so it is necessary to do collinearity statistics. From the table below, eigenvalues are closer to 1 than 0, affirming that the predictors are not highly correlated. That is, there is no problems of collinearity, and therefore the results in the regression reliably hold.
Table 3:Test for Collinearity
Implication for social Change
Teacher self-efficacy is crucial for promoting confidence in service delivery and teaching of mathematics. Math educators and policy makers should promote math teacher perception of self responsibility while also enlisting principals support to enhance self efficacy.
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. London: Routledge.
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