predictors when the variance
3. Results
As a first step in understanding the factors that influence performance in college,
we examined the zero-order correlations between the different assessments of col- lege GPA (i.e., cumulative, fall semester) and the variables that we anticipated
would predict college GPA. The full set of correlations between the measures
can be found in Table 1. In general, the relationships between the different assess-
ments of GPA and the predictors were quite similar across the measures of GPA.
Whereas neither of the assessments of GPA was associated with the amount of
time students studied, they were both positively associated with high-school
GPA (and SAT scores for cumulative GPA). In addition, consistent with expecta-
tions, attending classes and having an organized approach to planning were asso- ciated with a higher cumulative GPA. Attending classes was also associated with a
higher fall semester GPA. For fall semester GPA, studying in a quiet environment
was related to a higher GPA. Further, across the assessments of GPA, working
long hours at a job and spending more hours partying or at clubs were associated
with a lower GPA.
It is also worth noting that the amount of time that students spent studying was
negatively related to their SAT scores. This finding is consistent with the idea that
students who have superior prior knowledge and skills coming into the college could
Table 1
Intercorrelations between measures
2 3 4 5 6 7 8 9 10
1. GPA fall 2000 .55* .02 .25* .17 .27* .17 .27* �.24* �.22* 2. Cumulative GPA — .11 .33* .24* .28* .26* .17 �.30* �.28* 3. Study time — �.05 �.26* .04 .20 �.21* .14 .11 4. High-school GPA — .39* .13 .01 �.01 �.17 �.19 5. SAT scores — �.07 .01 �.11 �.05 �.10 6. Attendance — .12 .03 �.06 �.31* 7. Planning — �.01 .10 .06 8. Study environment — �.05 �.03 9. Hours of work — �.03 10. Hours partying —
Note. N ranges from 83 to 88 depending on missing data. * p < .05.
106 E.A. Plant et al. / Contemporary Educational Psychology 30 (2005) 96–116
attain a given GPA with less study time than those with weaker prior knowledge and
skills. Also, students who studied in a quiet environment with few distractions
tended to study for less time than those who studied in a less ideal environment.
Not surprisingly, students who spent more hours at parties and clubs tended to at-
tend a smaller percentage of their classes. Finally, high-school GPA and SAT were
reliably correlated.
3.1. Examination of cumulative GPA
Having established that the zero-order correlations were consistent with predic-
tions, we were interested in examining which of the potential predictors were inde-
pendently associated with college GPA. To this end, a hierarchical regression
analysis was conducted on participants� measures of GPA. As the more general measure of GPA, we first examined cumulative GPA up to the fall semester during
which we collected the participants� responses to the questionnaire. In the first step of the regression, the average study time per week based on the questionnaire re- sponses was entered into the equation to determine the impact of study time in the
absence of the other potential predictors. Next, high-school GPA and SAT scores
were entered into the regression as indicators of prior knowledge and skills. For
the third step, other variables that were anticipated to influence academic perfor-
mance (i.e., taking advantage of instruction and study quality) were entered. These
variables included class attendance, planning, study environment, and hours of
work per week. For the final step of the regression, high-school GPA and SAT
scores were removed from the equation. This step allowed us to identify both the variance independently accounted for by prior knowledge and skills and the
effect of the other predictors when the variance due to these variables was not re-
moved from cumulative GPA.
The findings from the analyses can be found in Table 2. The results from the first
step of the regression indicated that study time alone was not a significant predictor
of cumulative GPA, F(1,81) = 1.01, p = .32 (b = .11). When high-school GPA and
Table 2
Hierarchical regression analyses across measures of GPA
Cumulative
GPA