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Predicting academic success: General intelligence, "Big Five" personality traits, and work drive

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Intelligence, ‘‘Big 5’’ personality traits, and work drive as
predictors of course grade
John W. Lounsbury
a,
*, Eric Sundstrom
a
, James M. Loveland
a
, Lucy W. Gibson
b
a
Department of Psychology, University of Tennessee, Knoxville, TN 37996-0900, USA
b
Resource Associates, Inc., USA
Received 11 March 2002; received in revised form 3 September 2002; accepted 29 October 2002
Abstract
General intelligence, Big 5 personality constructs, and a measure of work drive were studied in relation
to course grade in an undergraduate psychology course taught by the same professor for 175 students over
a 5-year period. Using a hierarchical multiple regression analysis, general intelligence accounted sig-
nificantly for 16% of the variance in course grade; Big 5 personality measures accounted significantly for
an additional 7% of the variance; and work drive accounted significantly for an additional 4% of the
variance. However, when work drive was entered before the Big 5 variables, the Big 5 variables did not add
significantly (either as a set or individually) to the prediction of course grade. Results were discussed in
terms of the importance of personality constructs in uniquely predicting academic performance and the
need for additional study using more diverse predictors and aggregated criterion measures.
# 2002 Published by Elsevier Science Ltd.
The prediction of college grades from individual differences variables has been extensively
researched, with a recent shift in emphasis from studying cognitive predictors to examining the
role of personality constructs. A number of studies have examined the relationship between
grades and cognitive ability measures, with most finding a significant positive correlation (e.g.
Mathiasen, 1984; Mouw & Khanna, 1993; Passons, 1967; Schneider & Overton, 1983; Wolfe &
Johnson, 1995). As noted by Rothstein, Paunonen, Rush, and King (1994) there are logical and
empirical grounds for the prediction of academic performance from personality variables. For
example, students who are: more open to new learning, discovery, and exploration (see openness
as conceptualized by McCrae & Costa, 1997); higher on self-control, orderliness, and achieve-
ment striving (see conscientiousness as reviewed by Hogan & Ones, 1997) and lower on anxiety,
0191-8869/02/$ - see front matter # 2002 Published by Elsevier Science Ltd.
PII: S0191-8869(02)00330-6
Personality and Individual Differences & (&&&&) &&
www.elsevier.com/locate/paid
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* Corresponding author. Tel.: +1-865-974-2531; fax: +1-865-577-2764.
E-mail address: jlounsbury@aol.com (J. W. Lounsbury).
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impulsivity, hostility, and vulnerability (see neuroticism as discussed by Wiggins & Trapnell,
1997), would be more likely to perform well academically. Indeed, a number of studies have
examined the predictability of collegiate grades from personality variables (Boyer & Sedlacek,
1988; Brown, 1994; Dollinger & Orf, 1991; Dyer, 1987; Musgrave-Marquart, Bromley, & Dalley,
1997; Okun, & Finch, 1998; Omizo, Ward, & Michael, 1979; Pfeifer & Sedlacek, 1974; Rainey,
1985; Rothstein et al., 1994; Wolfe & Johnson, 1995).
Among the personality traits most frequently found to be significantly (and positively) related
to course grades and grade point average are the ‘‘Big 5’’ constructs of Conscientiousness (e.g.
Dollinger & Orf, 1991; Musgrave-Marquart et al., 1997; Paunonen & Ashton, 2001) and Open-
ness (e.g. Paunonen & Ashton, 2001), though Rothstein et al. (1994) found Agreeableness to be
significantly related to grade point average in a sample of business school graduate students. A
few studies have examined the unique effects of personality constructs in predicting college grades
(Brown, 1994; Wolfe & Johnson, 1995). For example, Wolfe and Johnson (ibid), found that SAT
scores and Conscientiousness both correlated 0.34 college GPA for a sample of 201 under-
graduates. After controlling for high school grades, Conscientiousness accounted for 9% unique
variance in college GPA whereas SAT contributed an additional 4% unique variance.
Few published studies have examined the incremental validity of personality variables above
and beyond cognitive ability in predicting academic performance (exceptions include Brown,
1994; Roessler, 1978; Wolfe & Johnson, 1995). None of the above studies have examined general
intelligence as a predictor of college grades. Rather, most studies have focused on ACT and SAT
scores as cognitive predictors and, in some cases, as proxies for general intelligence, even though,
in the case of the SAT, the Educational Testing Service makes no claim that it measures general
intelligence but it measures verbal and mathematical reasoning abilities. With few exceptions (viz.
Dollinger & Orf, 1991; Paunonen & Ashton, 2001), most studies have examined as the criterion
variable collegiate grade-point-average (GPA) summated across courses. However, overall GPA
contains between-teacher and between-major variability, which represent uncontrolled sources of
variance. These sources of variance may have attenuated estimates of the validity for personality
and mental ability variables in predicting course performance.
The present study addressed the above concerns by using a recognized measure of general intel-
ligence as a predictor and the grade received in a single course as the criterion variable. In view of
the widespread recognition of the Big 5 personality model (Costa & McCrae, 1985; Digman, 1990;
Goldberg, 1992; John, 1990), we examined the ‘‘Big 5’’ traits of Neuroticism, Extraversion, Open-
ness, Agreeableness, and Conscientiousness in relation to course grade. We investigated the joint
and unique effects of predicting college course grade from intelligence and personality constructs.
More specifically, we examined: (1) the predictability of course grade from intelligence; and (2)
whether the Big 5 personality variables of Neuroticism, Extraversion, Openness, Agreeableness,
and Conscientiousness (Costa & McCrae, 1985; Goldberg, 1992) together added incremental var-
iance to the prediction of course grades above and beyond that attributable to general intelligence.
We also addressed one other personality trait in addition to the ‘‘Big 5’’: work drive. As defined
by Lounsbury, Loveland, Sundstrom, Gibson, Drost, and Hamrick (in press), work drive repre-
sents an enduring motivation to expend time and effort to finish projects, meet deadlines, be
productive, and achieve success. Work drive includes elements of similar constructs: work values
(Blood, 1969); protestant ethic (Mirels & Garrett, 1971); job involvement (Lawler & Hall, 1970;
Lodahl & Kejner, 1965); work involvement (Kanungo, 1982); and work centrality (Paullay et al.,
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1994). A recent study by Rau and Durand (2000) found that academic work ethic predicted col-
lege grades. Accordingly, a third question we addressed in the present study was: Does work drive
predict unique variance in college course grades beyond that predicted by intelligence and the
‘‘Big 5’’ personality traits?
1. Method
1.1. Research design
A field study of students in one course taught by one instructor over a period of 5 years mea-
sured course grades, general intelligence via the Otis–Lennon test, a measure of the ‘‘Big 5’’ per-
sonality traits tailored for college students, and a measure of work drive.
1.2. Participants
The sample for this study was comprised of a total of 175 students enrolled in a senior-level
course in psychological testing from 1997 to 2001 at a large southeastern state university. The same
professor taught this course each of the 5 years using standard testing and grading criteria. Sixty-
four percent of the students were female; 36% were male. The average age was 22.7 (S.D.=3.44).
1.3. Measures
1.3.1. Big 5 personality measures
To measure personality, we used the Personal Style Inventory (PSI), a general personality
inventory developed by Lounsbury and Gibson (1998), with construct validity evidence on a
college student sample provided by Lounsbury, Tatum, Chambers, Owens, and Gibson (1999)
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and on a sample of 5932 adults representing a wide range of occupational groups provided by
Lounsbury, et al., (in press). Each item in the PSI is placed on a five-step scale with bipolar verbal
anchors. For example, in the following conscientiousness item, participants are asked to choose
the point on the scale closest to the way they see themselves.
I don’t always try to perform every school &&&&&I always try to perform every school
assignment in a very thorough manner. 1 2 3 4 5 assignment in a very thorough manner.
The following Cronbach coefficient alphas were observed: Neuroticism—0.81, Extraversion—0.83,
Openness—0.84, Agreeableness—0.81, and Conscientiousness—0.78.
1.3.1.1. Work drive. Drawing on the constructs of Protestant Ethic (Blood, 1969; Mirels & Gar-
rett, 1971), job involvement (Lawler & Hall, 1970; Lodahl & Kejner, 1965), work involvement
1
For example, Lounsbury et al. (1999) reported correlations between common Big 5 constructs from the PSI and
the NEO-FFI short form (Costa & McCrae, 1985) as: Extraversion: 0.72; Neuroticism: 0.70; Openness: 0.60; Agree-
ableness: 0.67; and Conscientiousness: 0.60.
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(Kanungo, 1982), and work centrality (Paullay, Alliger, & Stone-Romero, 1994), Lounsbury and
Gibson (1998) developed a scale to measure what they term work drive which reflects a person’s
disposition to work hard, put in long hours and extend oneself to finish projects, meet deadlines,
be productive, and achieve success. This scale has been extensively validated in a variety of work
and academic settings (Lounsbury & Gibson, 1998; Lounsbury et al., in press). In the present
study, work drive was measured on an 11-item scale tailored for students with responses placed
on a 5-point Likert scale ranging from 1 ‘‘Strongly Disagree’’ to 5 ‘‘Strongly Agree’’ Here are
four sample items: (1) I always try to do more than I have to in my classes. (2) I don’t mind
staying up late to finish a school assignment. (3) Doing well in school is the most important thing
in my life. (4) My friends say I study too much.
Cronbach alpha for the work drive scale=0.81. The average score was 3.33 with a standard
deviation of 0.74.
1.3.1.2. General intelligence. We used the Otis–Lennon Test of Mental Maturity—an 80-item
group-administered test of general intelligence which has been extensively normed and researched
(Anastasi & Urbina, 1997; Otis & Lennon, 1969).
1.3.1.3. Course grade. The final grade in the course served as the criterion variable in this study.
Grades were made on a 4-point scale ranging from 0=F to 4=A., with half-point intermediate
scale values. The median course grade was 3.0. Grading was based primarily on performance on
standardized tests (multiple choice and matching) scored by the graduate teaching assistant for
the course using preset cutoffs for grades. The graduate student did not have access to personality
scores or results, which helped maintain independence of grades and personality scores.
2. Results
Table 1 displays the descriptive statistics and the correlation matrix for the study variables. As
can be seen from this table, the following constructs were significantly related to course grade:
Table 1
Descriptive statistics and intercorrelations for study variables
a
(1) (2) (3) (4) (5) (6) (7) (8)
Neuroticism (1) 0.38** 0.40** 0.57** 0.45** 30** 0.03 0.11
Extraversion (2) 0.24** 0.40** 0.14 0.28** 0.10 0.01
Openness (3) 0.29** 0.17* 0.40** 0.12 0.16*
Agreeableness (4) 0.50** 0.30** 0.01 0.01
Conscientiousness (5) 0.53** 0.01 0.18*
Work drive (6) 0.02 0.28**
General intelligence (7) 0.40**
Course grade (8)
M 2.55 3.64 3.83 3.67 3.37 3.32 59.53 3.08
S.D. 0.64 0.64 0.58 0.57 0.72 0.74 10.26 0.75
a
Sample sizes for correlations range between 143 and 175. *P< 0.05. **P< 0.01.
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Openness (r=0.16, P< 0.05), Conscientiousness (r=0.18, P< 0.05), Work Drive (r=0.28,
P< 0.01), and general intelligence (r=0.40, P< 0.01).
To examine the incremental validity of the Big 5 and work drive constructs above and beyond
general intelligence, we conducted a hierarchical multiple regression analysis of course grades
with the following order of entry: (1) Step 1-general intelligence; (2) Step 2-the Big 5 variables;
and (3) Step 3-work drive. The results are shown in part one of Table 2. The amount of unique
Table 2
Hierarchical multiple regression results for general intelligence, work drive, and Big 5 variables entered as a set
a
Step Variable Dependent variable: course grade
Multiple RR
2
R
2
Change
Part 1: Results of hierarchical multiple regression analysis with work drive entered last
1 General intelligence 0.401** 0.161** 0.161**
2 Big 5 personality measures 0.477** 0.227** 0.067**
3 Work drive 0.551** 0.268** 0.041**
Part 2: Results of hierarchical multiple regression analysis with Big 5 variables entered last
1 General intelligence 0.401** 0.161** 0.161**
2 Work Drive 0.489** 0.239** 0.078**
3 Big 5 personality measures 0.517** 0.268** 0.028 (n.s.)
a
n=144. *P< 0.05. **P< 0.01.
Table 3
Hierarchical multiple regression results for general intelligence, work drive, and individual Big 5 variables
a
Step Variable Dependent variable: course grade
Multiple RR
2
R
2
Change
Part 1: Results of hierarchical multiple regression analysis with general intelligence and work drive included and with
forced entry of individual Big 5 variables based on order of importance
1 General intelligence 0.401** 0.161** 0.161**
2 Work drive 0.489** 0.239** 0.078**
3 Agreeableness 0.500** 0.250** 0.011 (n.s.)
4 Emotional stability 0.513** 0.264** 0.011 (n.s.)
5 Conscientiousness 0.517** 0.267** 0.004 (n.s.)
6 Extraversion 0.517** 0.268** 0.000 (n.s.)
7 Openness 0.517** 0.268** 0.000 (n.s.)
Part 2: Results of hierarchical multiple regression analysis with work drive included and with forced entry of individual
Big 5 variables based on order of importance
1 Work drive 0.288** 0.083** 0.161**
2 Agreeableness 0.307** 0.094** 0.011 (n.s.)
3 Emotional stability 0.322** 0.103** 0.009 (n.s.)
4 Extraversion 0.327** 0.107** 0.004 (n.s.)
5 Openness 0.331** 0.109** 0.002 (n.s.)
6 Conscientiousness 0.337** 0.113** 0.002 (n.s.)
a
n=144. *P< 0.05. **P< 0.01.
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variance contributed at each step is represented by the incremental variance or the squared semi-
partial correlation coefficient (Cohen & Cohen, 1983). A total of 27% of the variability in course
grade was accounted for, with general intelligence accounting for 16% of the variance in course
grade (P< 0.01) with the set of Big 5 personality variables adding an additional 7% (P< 0.01),
and work drive an additional 4% (P< 0.01) of the unique variance in course grade.
Given the relative importance of work drive in accounting for variance in course grade, we
decided to examine whether the Big 5 variables contribute any significant variance in course grade
above and beyond that accounted for by work drive. Thus, we reversed Steps 2 and 3 above, with
results shown in part two of Table 2. In this case, work drive accounted for 8% (P < 0.01) of the
unique variance in course grade after general intelligence, but the Big 5 variables accounted for a
non-significant 3% of the unique variance in course grade.
To further examine whether any of the individual Big 5 variables contributed uniquely to the
course grade variance, we performed two additional sets of hierarchical multiple regression ana-
lyses. In the first analysis, we included both general intelligence and work drive—in that order—
followed by forced entry of each of the Big 5 variables in order of magnitude of semi-partial
correlations. In the second analysis, we included just the work drive variable followed by forced
entry of each of the Big 5 variables in order of magnitude of semi-partial correlations. As can be
seen from the results of these two analyses displayed in parts one and two of Table 3, none of the
Big 5 variables added significant variance to the prediction of course grade beyond general intel-
ligence and work drive as predictors or work drive alone as a predictor.
3. Discussion
Our results confirmed the significant, positive relationship between general intelligence and
course grade. This result is consistent with results of other studies that found a significant positive
relationship between SAT/ACT scores and course grades (Dollinger & Orf, 1991; Paunonen &
Ashton, 2001). Since SAT correlates about 0.70 with the Otis Lennon Mental Ability Test (Otis &
Lennon, 1969), it is an open question whether SAT or ACT scores uniquely related to course
grades after controlling for general intelligence. This represents an interesting topic for future
research.
The present results also affirm the predictive validity of Big 5 personality traits in relation to
course grade. In fact, our results mirrored those of Paunonen and Ashton (1977) who found
Conscientiousness and Openness significantly, positively related to the final grade in a psychology
course. The present findings also demonstrate the incremental validity of Big 5 personality mea-
sures above and beyond general intelligence in predicting course grade. This pattern is consistent
with the above-mentioned studies of personality predictors of grade-point-average after control-
ling for SAT/ACT scores. Our results are also consistent with research in personnel psychology
that shows personality variables, particularly conscientiousness, adding incremental validity
beyond general mental ability in predicting job performance (e.g. Barrick & Mount, 1991; Hogan,
1996; Tett, Jackson, & Rothstein, 1991).
A unique contribution of the present results to the research literature is the finding that work
drive accounted for significant variance in predicting course grade beyond both general intelli-
gence and ‘‘Big 5’’ measures. Moreover, if work drive is entered prior to the Big 5 variables, with
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general intelligence included or excluded in the analysis, in the regression analyses for predicting
course grade, it is a significant predictor, but the Big 5 variables, either individually or as a set, do
not add significantly to the prediction of course grade. It may be that work drive represents a
more parsimonious model for predicting academic performance than the Big 5 constructs.
The present results provide one answer to prior calls for more specific or narrow-band person-
ality constructs than the Big 5 in predicting college grades (McIntire & Levine, 1984; Paunonen &
Ashton, 2001). The result for work drive reinforces the importance of a disposition to work hard,
or what has been variously termed work ethic, Protestant work ethic, and work value (e.g.
Cherrington, 1980; Hill & Rojewski, 1999; Mirels & Garrett, 1971; Waters, Batlis, & Waters,
1975) or, in the college context, ‘‘academic ethic’’ (Rau & Durand, 2000). Further research could
compare the present measure of work drive with comparable operationalizations of academic
ethic and work ethic.
One limitation of the present study is that it dealt with a single course. This deliberate feature of
our research design leaves open the question of the generalizability of the present findings to the
more global criterion of academic performance—grade point average (GPA). Because GPA
represents an aggregated score across many courses, it contains unmeasured differences in grad-
ing tendencies between professors. While GPA represents a robust criterion for validation, esti-
mates of the validity of various predictors may be attenuated by grading differences. It would be
interesting to see what validity estimates would be observed if grader difference effects could be
minimized; for example, by converting all course grades to an equivalent metric such as z scores
or by examining aggregated grades within majors, to control for inter-major differences in grades.
Either of these approaches would overcome the other problem with using a single course grade—
low variance in the criterion. Examining aggregated grades across multiple courses would
increase criterion variance and could lead to higher validities. Validity estimates generated here
are probably attenuated by relatively low criterion variance and may be under-estimates of the
validities that could be observed using multiple courses.
In conclusion, the present study found that measures of ‘‘Big 5’’ personality traits con-
scientiousness and openness, and a new measure of work drive, predicted unique variance in course
grades beyond that predicted by general intelligence. However, the results indicated that the Big 5
variables did not add significantly to the prediction of course grade above and beyond work drive.
These results provide additional support for the importance of non-cognitive variables in predict-
ing collegiate academic performance and for studying both broad personality constructs as well as
more specific, contextualized constructs in relation to academic attainment. Hopefully, future
research can confirm and extend these results using more diverse predictor and criterion measures.
References
Anastasi, A., & Urbina, S. (1997). Psychological testing. Upper Saddle River, NJ: Prentice Hall.
Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: a meta-analysis.
Personnel Psychology, 44, 1–26.
Blood, M. (1969). Work values and job satisfaction. Journal of Applied Psychology, 53(6), 456–459.
Boyer, S. P., & Sedlacek, W. E. (1988). Noncognitive predictors of academic success for international students: a
longitudinal study. Journal of College Student Development, 29(3), 218–223.
J.W. Lounsbury et al. / Personality and Individual Differences & (&&&&) && 7
1
2
3
4
5
6
7
8
9
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11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
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Version 7.51e
ARTICLE IN PRESS
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Brown, N. W. (1994). Cognitive, interest, and personality variables predicting first—semester GPA. Psychological
Reports, 74(2), 605–606.
Cherrington, D. (1980). The work ethic: working values and values that work. New York: Amacom.
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ:
Erlbaum.
Costa, P., & McCrae, R. (1985). The NEO Personality Inventory (NEO-PI-R) and the NEO Five-Factor Inventory
(NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources.
Digman, J. (1990). Personality structure: emergence of the five-factor model. Annual Review of Psychology, 41, 417–440.
Dollinger, S. J., & Orf, L. A. (1991). Personality and performance in ‘‘personality’’: conscientiousness and openness.
Journal of Research in Personality, 25(3), 276–284.
Dyer, E. D. (1987). Can university success and first-year job performance be predicted from academic achievement,
vocational interest, personality and biographical measures? Psychological Reports, 61(2), 655–671.
Goldberg, L. R. (1992). The development of marker variables for the Big-Five factor structure. Psychological Assess-
ment, 4, 26–42.
Hill, R., & Rojewski, J. W. (1999). Double jeopardy: work ethic differences in youth at risk of school failure. Career
Development Quarterly, 47(3), 267–279.
Hogan, R. (1996). Personality assessment. In R. S. Barrett (Ed.), Fair employment strategies in human resources man-
agement (pp. 144–152). Westport, Connecticut: Quorum.
Hogan, J., & Ones, D. S. (1997). Conscientiousness and integrity at work. In R. Hogan, J. Johnson, & S. Briggs (Eds.),
Handbook of personality psychology (pp. 849–870). San Diego, CA: Academic.
John, O. (1990). The ‘‘big five’’ factor taxonomy: dimensions of personality in the natural language and in ques-
tionnaires. In L. A. Pervin (Ed.), Handbook of personality theory and research (pp. 66–100). New York: Guilford.
Kanungo, R. (1982). Measurement of job and work involvement. Journal of Applied Psychology, 67(3), 341–349.
Lawler, E., & Hall, D. (1970). Relationship of job characteristics to job involvement, satisfaction, and intrinsic moti-
vation. Journal of Applied Psychology, 54(4), 305–312.
Lodahl, T., & Kejner, M. (1965). The definition and measurement of job involvement. Journal of Applied Psychology,
50(1), 24–33.
Lounsbury, J. W., & Gibson, L. W. (1998). Personal Style Inventory: a work-based personality measurement system.
Knoxville, TN: Resource Associates.
Lounsbury, J. W., Loveland, J. M., Sundstrom, E., Gibson, L. W., Drost, A. W., Hamrick, F. (in press). An investi-
gation of personality traits in relation to career satisfaction. Journal of Career Assessment.
Lounsbury, J. W., Tatum, H. E., Chambers, W., Owens, K., & Gibson, L. W. (1999). An investigation of career
decidedness in relation to ‘‘Big Five’’ personality constructs and life satisfaction. College Student Journal, 33(4), 646–
652.
Mathiasen, R. E. (1984). Predicting college academic achievement. College Student Journal, 18, 380–386.
McCrae, R. R., & Costa, P. T. (1997). Conceptions and correlates of openness to experience. In R. Hogan, J. Johnson,
& S. Briggs (Eds.), Handbook of personality psychology (pp. 826–847). San Diego, CA: Academic.
McIntire, S. A., & Levine, E. (1984). An empirical investigation of self-esteem as a composite construct. Journal of
Vocational Behavior, 25, 290–303.
Mirels, H., & Garrett, J. (1971). The protestant ethic as a personality variable. Journal of Consulting and Clinical Psy-
chology, 36(1), 40–44.
Mouw, J. T., & Khanna, R. K. (1993). Prediction of academic success: a review of the literature and some recom-
mendations. College Student Journal, 27(3), 328–336.
Musgrave-Marquart, D., Bromley, S. P., & Dalley, M. B. (1997). Personality, academic attrition, and substance abuse
as predictors of academic achievement in college students. Journal of Social Behavior & Personality, 12(2), 501–511.
Okun, M. A., & Finch, J. F. (1998). The Big Five personality dimensions and the process of institutional departure.
Contemporary Educational Psychology, 23(3), 233–256.
Omizo, M. M., Ward, G. R., & Michael, W. B. (1979). Personality measures as predictors of success in a counselor
education Master’s program. Educational and Psychological Measurement, 39(4), 947–953.
Otis, A. S., & Lennon, R. T. (1969). Otis-Lennon Mental Ability Test Technical Handbook. New York: Harcourt,
Brace.
8 J.W. Lounsbury et al. / Personality and Individual Differences & (&&&&) &&
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2
3
4
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42
43
44
PAID 2389 Disk used No. pages 9, DTD=4.3.1
Version 7.51e
ARTICLE IN PRESS
UNCORRECTED PROOF
Passons, W. R. (1967). Predictive validities of ACT, SAT, and high school grades for first semester GPA and freshmen
courses. Educational and Psychological Measurement, 27, 1143–1144.
Paullay, I., Alliger, G., & Stone-Romero, E. (1994). Construct validation of two instruments designed to measure job
involvement and work centrality. Journal of Applied Psychology, 79(2), 224–228.
Paunonen, S. V., & Ashton, M. C. (2001). Big five predictors of academic achievement. Journal of Research in Per-
sonality, 35, 78–90.
Pfeifer, C. M., & Sedlacek, W. E. (1974). Predicting black student grades with non- intellectual measures. Journal of
Negro Education, 43(1), 67–76.
Rainey, D. W. (1985). The JAS-T and Type A in students: a replication note. Journal of Personality Assessment, 49(5),
528–529.
Rau, W., & Durand, A. (2000). The academic ethic and college grades: does hard work help students ‘‘to make the
grade’’? Sociology of Education, 73(1), 19–38.
Roessler, R. (1978). Cognitive and noncognitive variables in the prediction of preclinical performance. Journal of
Medical Education, 53(8), 678–680.
Rothstein, M. G., Paunonem, S. V., Rush, J. C., & King, G. A. (1994). Personality and cognitive ability predictors of
performance in graduate business school. Journal of Educational Psychology, 86(4), 516–530.
Schneider, L. F., & Overton, T. D. (1983). Holland personality types and academic achievement. Journal of Counseling
Psychology, 30(2), 287–289.
Tett, R. P., Jackson, D. N., & Rothstein, M. (1991). Personality measures as predictors of job performance: a meta-
analytic review. Personnel Psychology, 44, 703–742.
Waters, L., Batlis, N., & Waters, C. (1975). Protestant ethic attitudes among college students. Educational and Psycho-
logical Measurement, 35, 447–450.
Wiggins, J. S., & Trapnell, P. D. (1997). Personality structure: the return of the Big Five. In R. Hogan, J. Johnson, &
S. Briggs (Eds.), Handbook of personality psychology (pp. 737–765). San Diego, CA: Academic.
Wolfe, R. N., & Johnson, S. D. (1995). Personality as a predictor of college performance. Educational and Psycho-
logical Measurement, 55, 177–185.
J.W. Lounsbury et al. / Personality and Individual Differences & (&&&&) && 9
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... This is in contrast with studies conducted by Komaraju, Karau and Schmeck (2009), reported that there is positive connection between neuroticism and academic achievement. To sum up, Ridgell and Lounsbury (2004) state that, the model of relationships among personality domains is inconsistent even though Big-five personality traits are evidently associated to academic achievement. This seems that academic achievement not only related to personality traits but also partially depends on others factors, for example, academic year at college and standards used to assess performance (Ridgell and Lounsbury, 2004). ...
... To sum up, Ridgell and Lounsbury (2004) state that, the model of relationships among personality domains is inconsistent even though Big-five personality traits are evidently associated to academic achievement. This seems that academic achievement not only related to personality traits but also partially depends on others factors, for example, academic year at college and standards used to assess performance (Ridgell and Lounsbury, 2004). ...
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Publisher Summary This chapter discusses the openness which cannot be understood as the culture that is acquired through education or good breeding, not as intellect or any other cognitive ability. Openness must be viewed in both structural and motivational terms. Openness is seen in the breadth, depth, and permeability of consciousness and in the recurrent need to enlarge and examine experience. Openness also suggests a passive or uncritical receptivity, which is clearly inappropriate. Open people actively seek out experience and are apt to be particularly reflective and thoughtful about the ideas they encounter. A structural account of openness may be necessary, but it does not seem to be sufficient. Open people are not the passive recipients of a barrage of experiences they are unable to screen out; they actively seek out new and varied experiences. Openness involves motivation, needs for variety cognition sentience, and understanding. The heritability of openness might be explained by the heritability of intelligence. Psychologists have spent more time and effort studying intelligence, than any other trait by adopting the term “Intellect.” Personality psychologists could claim this vast literature as their own. Openness could be construed as intelligence itself or as the reflection of intelligence in the personality sphere.
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