faculty member have lower total engagement scores. 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). See Table 4-78 for the unstandardized coefficient (B), intercept
(Constant), and standardized coefficient (0).
Table 4-78. Class A Backward Stepwise Multiple Regression Explaining Student Total
Engagement (n=56)
Model
Construct B SE Beta t. Sign. F Sign.
(Constant) 5.64 9.45 0.60 .55 6.62 .00
Sufficiency of originality
gap -0.16 0.10 -.19 -1.57 .12
Total Motivation 0.53 0.25 .25 2.16 .04
Total Stress 0.27 0.08 .39 3.39 .00
Number of similar
courses 3.07 1.40 .26 2.20 .03
College classification 2.88 1.10 .30 2.61 .01
Note. Adjusted R2=.34
Class B
Considering Class B, backward stepwise regression was used to explain student
engagement with independent variables of cognitive style gap, total stress, total
motivation and student demographic variables. 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 most important independent
variable in this model was total motivation, however the focus of this study was to
examine the relationship between dissimilar cognitive style and student engagement. For
students in Class B with an innovative 5-point rules/group conformity gap have an
average 1.80 points higher engagement score than students with no rules/group
conformity gap controlling for student motivation. Note that the scale used to measure of
total engagement used in this study comprised 72 points. The data suggests that students