220
However, the explanation of motivation contributed by efficiency cognitive style gap was
the focus of this objective. To interpret the model, students in Class C with an innovative
5-point efficiency cognitive style gap have an average 0.80 points lower total motivation
score than students with no efficiency cognitive style gap while controlling for gender
and age. Note that the total motivation scale has a 42-point range. The data suggests that
students with a higher innovative efficiency cognitive style gap score with this more
adaptive faculty member of Class C have lower levels of total motivation. That is in Class
C, as student efficiency cognitive style gap moved from more adaptive to more
innovative, students have lower levels of motivation. The model had an adjusted R2 of
.14 indicating that 14% of the variance of motivation in Class C was explained by these
three variables (p<.05). See Table 4-69 for the unstandardized coefficient (B), intercept
(Constant), and standardized coefficient (0).
Table 4-69. Class C Backward Stepwise Multiple Regression Explaining Student Total
Motivation (n=56)
Model
Construct B SE Beta t. Sign. F Sign.
(Constant) 17.18 8.99 1.91 .06 3.88 .01
Efficiency gap -0.16 0.12 -.18 -1.38 .17
Gender 2.88 1.21 .33 2.38 .02
Age 0.51 0.35 .20 1.44 .16
Note. Adjusted R2=. 14
Class D
With respect to Class D, backward stepwise multiple regression was used to
explain total student stress. The best fitting model included the variables efficiency
cognitive style gap (P=-. 15) and the demographic variable of college classification (3=-
.29). For Class D, the more important variable in explaining student stress was college
classification. However, the focus of objective 4 was to examine the relationship between