student engagement in each of the nine classes. Demographic variables included students'
age, gender, number of similar courses taken and college classification. Backward
stepwise multiple regression was employed for analysis of the data to provide evidence of
support for the theoretical framework of this study. Said differently, data analysis will
examine if student engagement in the classroom can be explained by cognitive style
construct gaps, stress and motivation. Finally, all students who participated in the study
were grouped together to further explain student engagement. Objective five conclusions
will be discussed after a brief presentation of the findings.
Class A
For Class A, backward stepwise regression was used to explain student
engagement with independent variables of cognitive style gap constructs, total stress,
total motivation and student demographic. The best fitting model with the most
explanation of student engagement used five independent variables including sufficiency
of originality cognitive style gap (P=-. 19), total motivation (P=.25), total stress (P=.39),
number of similar courses (P=.26) and college classification (p=.30). The model had an
adjusted R2 of .34 signifying that 34% of the variance of student engagement in the class
was from these five variables (p<.05).
Class B
Considering Class B, backward stepwise regression was used to explain student
engagement with independent variables of cognitive style gap constructs, total stress,
total motivation and student demographic. The best fitting model with the most
explanation of the dependent variable left two variables including rules/group conformity
cognitive style gap (P=.33) and total motivation (P=.38). The model had an adjusted R2 of