Furthermore, differences of scores between classes were expected and supported by

authors of the instruments. For example, Kirton (2003, p. 75) provides evidence that self-

selected courses may be more adaptive or innovative depending on the nature of the

course. If students in each course were disproportional regarding the number of young

women, there may be higher levels of stress (Gadzella and Guthrie, 1993). Authors of the

MSLQ (Pintrich, Smith, Garcia, McKeachie, 1991) claim that "responses to the questions

might vary as a function of different courses" (p. 5). Finally, student engagement is an

outcome of teaching practices and may vary with individual differences found among

faculty members (Kuh, Hayek, Carini, Ouimet, Gonyea & Kennedy, 2001). Given the

above reasons, the data were not analyzed to examine the effect of different types of

instrument administration.

 Data Analysis Procedures

 Data were analyzed according to the following objectives and presented in

chapter 4 with respect to study objectives and classes.

Research Objective One

 Research objective one was to describe selected faculty and students according to

their selected demographic variables. Student participants were asked demographic

questions found on the NSSE including age, gender, college classification, full-time

status, number of similar courses taken and major. Student participants were also asked

how many problem sets were assigned during a typical week that took more than an hour

to complete. Faculty participants were asked to respond to demographic items including

age, gender, and years of teaching experience. To achieve objective one, data were

entered into SPSS statistical software for Windows and analyzed using descriptive

statistics (frequencies and measures of central tendency).