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have lower levels of motivation. However, the adjusted R2 was .03 for the model

indicating that only 3% of the variance of motivation was attributed to the three

independent variables. See Table 4-77 for the unstandardized coefficient (B), intercept

(Constant), and standardized coefficient (0) for explanation of motivation for all students.

Table 4-77. All Students Backward Stepwise Multiple Regression Explaining Student
 Total Motivation (n=502)
 Model
 Construct B SE Beta t. Sign. F Sign.
 (Constant) 27.92 0.81 34.38 .00 5.20 .01
 Efficiency gap -0.04 0.02 -.08 -1.80 .07
 Gender 0.97 0.37 .12 2.61 .01
 Number of similar
 courses 0.41 0.18 .10 2.29 .02
Note. Adjusted R2=.03

Summary of Findings for Objective Four

 This study used backward stepwise multiple regression to examine if cognitive

style gap contributed to the explanation of student stress and student motivation.

Considering the explanation of student stress in adaptive courses, Class A provided

evidence that students in these classes with a more innovative cognitive style construct

had increased levels of total stress. The same was true for Class D. Note that Class D was

taught by a middle score faculty member, but scored 94 for total cognitive style

designating him adaptive by one point. For innovative courses, Classes H and I provided

evidence that students in these classes with a more adaptive cognitive style construct had

increased levels of stress. The data suggests that Kirton's (2003) A-I theory was upheld

in Classes A, D, H and I as a cognitive style construct gap did explain some variance of

stress in these four courses.

 Class C was taught by a more adaptive faculty member, but the data suggests that

students having an innovative sufficiency of originality cognitive style gap have lower