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