26.73 points while controlling for student stress. Again, the measure of total engagement

used in this study had a range of 24 to 96 points. The data suggests that students in Class

G having higher scores on total motivation have higher scores on total engagement while

controlling for student stress. However, there was no indication that cognitive style gap

significantly contributed to the explanation of variance of student engagement in Class G.

The adjusted R2 for the model was .22 signifying that 22% of the variance of the

dependent variable was attributed to students' total stress and total motivation. The model

was significant (p<.05). See Table 4-83 for the unstandardized coefficient (B), intercept

(Constant), and standardized coefficient (0) determining student engagement of Class G.

Table 4-83. Class G Backward Stepwise Multiple Regression Explaining Student Total
 Engagement (n=63)
 Model
 Construct B SE Beta t. Sign. F Sign.
 (Constant) 17.53 7.58 2.31 .02 9.58 .00
 Total Motivation 0.81 .24 .38 3.31 .01
 Total stress 0.13 .06 .25 2.24 .03
Note. Adjusted R2=.22

Class H

 For Class H, student engagement was explained by using backward stepwise

multiple regression to identify independent variables that best contribute to a fitting

model. Four variables were identified that contributed to the explanation of Class H

student engagement. Those independent variables include rule/group conformity style

gap (P=.40) number of similar courses previously taken by the student (P=-.26), total

motivation (p=.47) and total stress (P=.30). In this model, the independent variable

offering the most explanation to the variance of student engagement was total motivation.

However, the focus of the objective was to examine the relationship between cognitive

style gap and student engagement. In Class H, students having an adaptive 5-point