Regression Results
Multiple linear regression was used to determine whether intrinsic motivation and effort regulation are predictive of student procrastination. Intrinsic motivation and effort regulation were measured by online graduate students’ scores on the respective scales on the MSLQ, and entered as the independent or predictor variables. Student procrastination was measured by the online graduate students’ total score on the PASS, and entered as the dependent variable. The sample size for the analyses was 81 representing all online graduate students who completed the surveys.
Preliminary examination of the results indicated there was no extreme multicollinearity in the data (all variance inflation factors were less than 2). Exploratory analysis also indicated that the assumptions underlying the application of multiple linear regression (independence, normality, heteroschedasticity, and linearity) were met. The regression results indicated that the set of independent variables significantly influenced 19.8% of the variance in learner-centered beliefs (F(2, 78) = 2.751; p < .001) (see Table 1) with an effect size was particularly large for this small sample at .25. Both of the independent variables had a significant unique influence on procrastination. In order of importance, they were effort regulation (t = -2.63, p < .01) and intrinsic motivation (t = -2.34, p < .05).
The negative correlation between intrinsic motivation and effort regulation as they relate to procrastination (-.36 and -.38, respectively) indicate that as intrinsic motivation to learn and effort regulation decrease, procrastination increases. Beta weights and partial correlations are presented in Table 1.
Table 1
Regression Analysis of Procrastination on Intrinsic Motivation and Effort Regulation
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Variable b Beta Partial t
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Intrinsic Mot. -3.82 -.25 -.24 -2.34**
Effort Reg. -4.56 -.29 -.27 -2.63*
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Note. *p < .01. **p < .05. R2 = .198. R2 change = .178.