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.20. This signifies that 20% of the variance of student engagement in the class was from
these two variables (p<.05).
Class C
In order to explain student engagement of Class C, backward stepwise multiple
regression was employed to find the best fitting model utilizing the independent
constructs of cognitive style gap and variables total stress, total motivation and student
demographics. Data analysis found that sufficiency of originality cognitive style gap
(P=.20), total motivation (p=.45) and age (P=.22) best contributed to total engagement of
Class C. The model was statistically significant (p<.05) and the adjusted R2 was .24.
Class D
To explain student engagement of Class D, backward stepwise multiple
regression was used to determine the independent variables that best fit into a model.
Data analysis found that only total motivation (p=.38) best explained student engagement
of Class D. The model was significant (p<.05) and the adjusted R2 was .13, indicating
that the independent variable contributed 13% of the variance in explaining student
engagement of Class D.
Class E
Backward stepwise multiple regression was employed to explain student
engagement in Class E given the independent variables of cognitive style gap constructs,
total stress, total motivation, and selected student demographic variables. After data
analysis, the best fitting model was made using three variables: number of similar courses
taken by the student (P=.40), total stress (P=.27) and age (P=.45). The adjusted R2 of the
model was .26 signifying that 26% of the variance was explained by the three variables.