Olivarez - National FORUM of Applied Educational Research Journal - , - William Allan Kritsonis, PhD - Editor-in-Chief (Founded 1`982)

7/28/2019 Olivarez - National FORUM of Applied Educational Research Journal - www.nationalforum.com, - William Allan Kritsonis, PhD - Editor-in-Chief (Founded 1`982)

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41 NATIONAL FORUM OF APPLIED EDUCATIONAL RESEARCH JOURNAL

of measures (e.g., Carvajal & Pauls, 1995; Eaves, Williams,Winchester, & Darch, 1994; Kaufman, 1973; Martel, McKelvie, &Standing, 1987; McGrew & Hessler, 1995; Wiese, Lamb, & Piersel,1988). In addition, most recognize that ability is not independent of the motivational factors that differ across individuals (Goff &Ackerman, 1992). These factors tend to mediate the influence thatability has on academic performance (Pajares & Graham, 1999;Pajares & Kranzler, 1995; Stevens, Olivárez, Lan, & Tallent-Runnels,2004). Therefore, most current empirical evidence supports thatintelligence and motivation factors provide significant contributions inthe prediction of academic success.

In contrast to the typically supported relationships betweenacademic performance and intelligence, as well as academicachievement and motivation, research investigating the role of

personality and academic achievement has provided consistentlymixed results (Farsides & Woodfield, 2003). For example, Farsidesand Woodfield (2003) used the Five Factor Model (FFM) of

personality, considered to be the most highly agreed upon personalitystructure among researchers (Perugini & Gallucci, 1997), and foundonly two traits, openness to experience and agreeableness, to be

positively associated with undergraduate students’ final grades after intelligence and an motivation were taken into account. Neither conscientiousness nor neuroticism were positively associated toacademic success. This is surprising since these two traits are oftenlinked to success in school.

In contrast to Farsides & Woodfield (2003) study, others havefound significant positive associations between conscientiousness andacademic outcomes. Recently, Heaven, Mak, Barry, and Ciarrochi(2002) reported that high school students possessing higher levels of conscientiousness tended to have better attitudes about school andhigher academic performance. Others have noted similar associations,also linkied higher levels of conscientiousness to college GPA. (Wolfe& Johnson, 1995) and to the overall final exam grades of universitystudents (Chamorro-Premuzic & Furnham, 2003). In addition, McIlroy



Arturo Olivárez, Jr., Tara Stevens, Helenrose Fives & Doug Hamman 42

and Bunting (2002) documented a relationship between academicconscientiousness and the test performance of undergraduate

psychology students; however, they noted that a general measure of conscientiousness was not related to either test performance or coursework. Because personality traits are often considered “insulated fromthe direct effects of the environment” (McCrae & Costa, 1999, p. 144),the appropriateness of limiting the measurement of conscientious

behavior to only the academic domain may not be relevant to thetraditional study of personality in education.

The question of why FFM traits do not consistently predictacademic achievement continues to be an issue. Educators are oftenleft uncertain of whether or not a better understanding of personality isimportant in facilitating academic success. Considering thatconscientiousness, the factor associated with task-oriented behavior (Peabody & Goldberg, 1989) and thought by some to be the factor most highly associated with learning (DeFruyt & Mervielde, 1996;Graziano & Ward, 1992; Digman, 1989), would theoretically relate tostudents’ achievement. However, it empirically does not always do so,a closer examination seems warranted. Of interest is De Raad andSchouwenburg’s (1996) conclusion that conscientiousness is typically

positively related to most cognitive and metacognitive study habits;however, Farsides and Woodfield’s (2003) results did not include asignificant relationship between conscientiousness and academicsuccess. Other researchers have also found no significant correlation

between these constructs (e.g., Goff & Ackerman, 1992; Rothstein,Paunonen, Rush, & King, 1994). Thus, the use of conscientiousness asa viable construct to inform expectations concerning student

performance and success is questionable.

Considering that as a personality trait, conscientiousness isthought to be relatively stable and unchangeable across the lifespan(McCrae & Costa, 1996), some might not initially accept that such a

predictor is important in improving academic performance as its stablenature does not likely lend to manipulation. However, a similar argument can be made against the stable nature of ability, which




despite its consistent quality is often used to inform educators of student needs for enrichment, acceleration, and remediation.Therefore, it is plausible that conscientiousness, if truly associatedwith academic success, may assist educators in making decisionsconcerning who may require assistance with organization, deadlines,and structure, all of which will likely encourage better academicoutcomes.

The purpose of the present study was to further evaluate therole of conscientiousness, in conjunction with ability and motivation,in the prediction of academic achievement using two competing pathmodels to represent relevant theoretical underpinnings. Because it has

been suggested that personality may provide varying influencesdepending upon academic domain (Farsides & Woodfield, 2003),mathematics achievement was the academic area targeted as concernfor low performance scores. This academic performance domain has

been a consistent issue over the past two decades. Finally,conscientiousness was the focus of the present study due to its logicaltheoretical connection to student learning (DeFruyt & Mervielde,1996; Graziano & Ward, 1992; Digman, 1989). Without theacceptance of a theoretical framework for guiding the study of

personality in education (De Raad & Schouwenburg, 1996), we focusour attention to the possible relationship between personality andintelligence.

Personality and Intelligence

The difference between the constructs of personality andintelligence has been consistently investigated throughout the prior century (Goff & Ackerman, 1992), with most reviewers concludingthat the two are significantly independent (Saklofske & Zeidner,1995). Despite this distinction, some researchers have continued to

posit that a relationship does exist suggesting that personality traits,such as neuroticism and extraversion, do affect intelligence test scores(Furnham, Forde, & Cotter, 1998). Although not replicated by




subsequent investigations (Rawlings & Skok, 1993; Saklofske &Kostura, 1990), Robinson (1985) found that introverts outperformedtheir extraverted counterparts on tests of verbal ability, whereasextraverts outperformed introverts on tests of performance. Inaddition, evidence also supports that stable introverts may perform

better on timed intelligence tests (Furnham et al., 1998).

Such relationships may suggest either that ones’ personalityover time leads to the development of specific intellectual strengths or simply that personality is a factor that contributes to measurementerror. The aforementioned explanation indicates that a personalitytrait, such as introversion may lead to solitary engagement in tasks likereading and writing. As a result, individuals high in introversion may

be more likely to develop verbal skills and therefore score higher ontests of verbal ability. It follows from this explanation that possessinghigher levels of introversion simply mean that interaction in the testingsituation may be more greatly focused on the testing tasks rather thanon socialization with the test administrator or examiner, a factor thatcould adversely affect test scores. Since performance testing activitiesare often timed and involve little interaction with the examiner,individual differences may not have a great effect; however on verbaltesting tasks that typically involve greater interaction, introversionmay be a benefit as the individual may not be distracted by socialinformation.

However, the aforementioned scenarios could be viewed froma different direction. For example, introverted individuals who spendgreater time alone engaged in reading and writing activities may notenjoy the benefit of greater verbal ability. These individuals insteadsuffer from the lack of scaffolding and guidance provided frominteraction with adults and more advanced peers. When consideringtesting error, one could also speculate that the lack of social interestdisplayed by the introvert would adversely affect test scores as thereluctance to interact with the examiner could result in a failure tofully express responses. This interaction could potentially result in theomission of important information that would possibly reveal greater




ability. Similar questions arise when contemplating the role of conscientiousness. Would an individual’s preference for organizationand order encourage understanding and performance ability or wouldit be hindering due to restrictions and the failure to break out of a mindset or even think in newer ways that might potential affect final

performance results?

Because the multiple types of intelligence testing situations(e.g., group, individual, nonverbal, etc.) and the influence of continuous personality traits on the development of intelligencesuggest an endless number of ways in which personality may influenceintelligence test results, it seems that personality and intelligence may

be considerably intertwined resulting in both psychometric andtheoretical challenges. To address this issue, Cronbach’s (1949)

proposition of intelligence as maximal performance and personality astypical performance continues to reemerge (Hofstee, 2001). Themeasurement of intelligence is often approached in a manner thatreveals the testtaker’s maximal capabilities. The intentions of intelligence tests are to assess students’ best possible performances inorder to assess their general capabilities in cognitive domains. For example, on a timed coding task on a formal intelligence test,individuals are encouraged to accurately complete as many items inthe time allotted. However, this may not be the way these individualsapproach similar activities in typical, or everyday, situations. As aresult, maximal performance describes the best that one could do,whereas typical performance indicates what one tends to do in daily

practice.

Researchers such as Goff and Ackerman (1992) providedevidence that typical intelligence could be measured using itemsrelating to interest, specific aspects of personality, and engagement.They found that typical intelligence is more strongly related toCattell’s (1963) crystallized ability (G c) than to the fluid abilityconstruct (G f ). In other words, typical intelligence tends to be moregreatly associated with intelligence that involves the ability to applyverbal and conceptual knowledge than that which involves general




reasoning ability. This is logical as G c is considered to be developedvia formal educational experiences, which more greatly allow for thedaily influence of personality and interest variables over time ascompared to the case of G f which is often thought of as moreinherently based (Carroll, 1984).

Although Goff and Ackerman (1992) and Hofstee (2001) madeattempts to blend personality and intelligence through the creation of typical intelligence constructs that contained personality variables,such strategies have not been generally accepted (e.g., Rocklin, 1994).Goff and Ackerman (as cited in Rocklin, 1994) are criticized for failing to provide adequate psychometric evidence that their typicalintelligence construct actually differed from the construct of

personality. Furthermore, the employment of traditional intelligenceand personality tests continues to be the norm in educational settings.As a result, we would expect that FFM personality measures wouldnot significantly correlate with tests of maximal intelligence. Inaddition, achievement measures that focus on students’ best or maximal performance would likely be predicted by maximalintelligence, whereas achievement measures that reflect students’typical performance and academic activities over time would likely be

better predicted by personality.

Personality and Motivation

Although making distinctions between typical and maximalability may explain mixed findings related to the investigations of

personality and academic achievement, evaluating the role thatmotivation plays in this relationship is also important in understandingthe underlying processes. Because the FFM has been criticized for itsatheoretical nature (Cooper, 1998) that provides organization of

phenomena rather than explanation (Ozer & Reise, 1994), researchersmust investigate how the FFM works with other relevant variables,such as, intelligence and motivation. For example, the understandingthat intelligence predicts mathematics achievement does not provide




enough information to improve mathematics achievement. However,Pajares and Graham’s (1999) investigation into the mediating effectsof self-efficacy, or one’s beliefs in his or her ability to successfullyemploy his or her knowledge and skills (Bandura, 1986). Theseresearchers provided the explanation that intelligence is filteredthrough children’s beliefs before it affects mathematics performance.In other words, a child who may possess a high degree of intelligence,

but a low level of self-efficacy will likely not perform to the levelexpected on a test of mathematics and vice versa.

In the present case, one must also question whether or not asimilar mediating effect is possible concerning the relationship

between personality and mathematics achievement. Self-efficacy as amediator of personality and mathematics achievement has not yetspecifically been evaluated. However, Graziano, Jensen-Campbell,and Finch (1997) did find that self evaluations of competence wereable to mediate the links between FFM personality traits and teacher-rated adjustment in academic and social domains. In addition, in thefield of administrative sciences, evidence exists supporting that theeffects of conscientiousness on job performance are mediated throughmotivation variables, such as performance expectancy and goal choice(Gellatly, 1996) as well as striving for status and accomplishment(Barrick, Stewart, & Piotrowski, 2002).

The effects of personality on academic variables may bemediated by the beliefs that individuals possess about their ability touse their skills effectively. For example, students high inconscientiousness would be expected to display organization and order in the academic environment and would therefore likely havemetacognitive skills that encourage higher academic achievement over time. Again, this may be more apparent in students’ grade pointaverages (GPA) and end of course grades, which reflect typical

performance, than in specific testing situations designed to assessmaximal performance. However, a student high in conscientiousnesswho does not possess feelings of efficacy in his or her ability to usethose attributes in a specific domain may not experience higher levels




of academic achievement. In mathematics, an academic domain thattends to be greatly influenced by students’ motivational qualities(Brophy, 1998; McLeod, 1990; Carr, 1996), the role of self-efficacymay be particularly important.

The Present Study

In the present study, we elected to use a standard measure of conscientiousness to evaluate typical intelligence. In addition, wechose a measure of Cattell’s G f to assess maximal intelligence. Weexpected that these two variables would not be significantly correlated.We also anticipated that maximal intelligence would act as asignificant predictor of mathematics performance. We decided tomeasure mathematics performance, using a test on which studentswere asked to perform their best. Typical intelligence was expected toserve as a significant predictor or students’ overall grade point average(GPA), a variable that should reflect typical performance over time.Finally, we hypothesized that mathematics self-efficacy would act as amediator between G f and mathematics performance as well asconscientiousness and GPA.

To evaluate our hypotheses we constructed two competing pathmodels, each evaluating the relationships between five variables: G f ,conscientiousness, mathematics self-efficacy, mathematics test

performance, and overall GPA. In the first model, G f andconscientiousness predicted mathematics performance and overallGPA, with the direct effects mediated by mathematics self-efficacy(see Figure 1). The purpose of the first model was to evaluate thetypical and maximal nature of conscientiousness and intelligence,while considering mathematics self-efficacy as a mediator. The secondmodel considered ability as a maximal measure of intelligence andconscientiousness as typical by allowing ability to only predictmathematics test performance and conscientiousness to only predictGPA; however these direct effects continued to be mediated bymathematics self-efficacy (see Figure 2).




Methodology

Participants

A sample of college students was conveniently selected from arequired college-wide computer literacy course offered at a large,

public university located in the Southwest, United States.Approximately 650 students enrolled and were given the opportunityto improve their course grade by volunteering to participate in variousresearch projects. Of the students, 368 volunteered to participate in the

present study, with 314 completing all of the measures required. Themajority of the students were classified as freshmen and sophomores(66.6%). Seventy-three percent identified themselves as female and80.7% as Anglo-Americans. A total of 49 different majors wererepresented.

Measures

General Mental Ability. The Cattell Culture Fair IntelligenceTest (1973) was utilized to measure the general ability (G f ) of

participants. The measure is based on Cattell’s (1971) theory of “fluid” abilities, which assumes that such abilities involve information

processing skills that reflect the individual’s ability to adapt and learnfrom the environment as time passes. The test is available in threelevels corresponding to the participant’s age. The short form of Cattell’s second scale, which is appropriate for young children andadults, was employed for the current study. The test was groupadministered and consists of four subtests that involve completingseries, classifying, solving matrices, and evaluating conditions. Itemswere hand scored yielding a total score. An internal consistencyestimate of .76 is reported in the test manual for the short form of Scale 2. The internal consistency estimate for the present sample was67.




Conscientiousness. Assessment of the FFM trait,conscientiousness, was accomplished using the participants’ self-reports on the revised version of Lanthier’s (1993) Big FivePersonality Questionnaire (BFPQ). The BFPQ was created to obtainself and other reports of the FFM dimensions across a wide age range.The 60 items on the questionnaire, with 12 items representing eachtrait, were formed by examining lists of adjectives developed byGoldberg (1990), Norman (1963), and McCrae and Costa (1987). Eachof the adjectives was embedded in a question which asks the

participant to rate how much he or she is like the specific target word.Each item is answered on a 5-point, Likert scale where a 1 representshardly at all like me and a 5 represents extremely much like me.Scores are formed by taking the mean of the 12 items included in eachscale, with higher scores indicating higher levels of a particular trait.For the present study, participants were asked to complete only the 12-item conscientiousness scale. Items addressed the participants’ self-report of levels of organization, dependability, responsibility, neatness,forgetfulness, and rebelliousness. The internal consistency estimate for the current sample was .78.

Mathematics Self-Efficacy. To assess students’ mathematicsself-efficacy, a task-specific mathematics self-efficacy instrument wascreated based on one developed by Pajares and Graham (1999) andguidelines discussed by Marsh, Roche, Pajares, and Miller (1997).Students were asked to endorse their level of confidence in correctlysolving 20 algebraic problems based on an 8-point Likert scale rangingfrom “not confident at all” to “completely confident”. Directions onthe instrument stated, “Suppose that you were asked the followingmath questions in a multiple choice test tomorrow. Please indicatehow confident you are that you will give the correct answer to eachquestion.” For example, one item presented the following: In oneschool, 65% of the graduates went on to college. If there were 1500graduates, how many went on to college? Students were instructed notto work the problems, and scores were derived by summing the items,with higher scores indicating a greater amount of confidence thanlower scores. Pajares and Graham (1999) reported consistent estimates




of reliability across samples with Cronbach’s alpha coefficients at or near .94 and noted their similarities to coefficients obtained fromsimilar instruments in previous investigations. For the present sample,Cronbach’s alpha reached .93.

Mathematics Performance. Students were asked to complete20 problems that were similar to those they previously rated their confidence in solving on the mathematics self-efficacy instrument.Similar rather than identical items were utilized to measuremathematics performance to address the possible artificial inflation of the correlation between mathematics self-efficacy and performance asa result of correlated specifics (Marsh, Roche, Pajares, & Miller,1997). Participants were asked to solve algebraic problems and selectthe correct answer from four choices. The items were scoreddichotomously, correct or incorrect using dummy coding, and totaledto derive a raw score. A Kuder-Richardson Formula 20 estimate of reliability calculated for the present total sample reached .78.

Overall Grade Point Average. Students were asked to reporttheir overall grade point average, using the traditional 4.00 scale. Wewere interested in these students’ overall or typical schoolachievement and believed that GPA would serve as a more accurateassessment of students’ typical or daily achievement.

Procedures

An announcement soliciting participants for the study wasmade in all sections of the selected course. Interested students were

provided with a consent letter describing the procedure and were askedto anonymously complete the test booklets in groups at the end of oneclass session.

Statistical Analyses

The LISREL 8.52 program (du Toit & du Toit, 2001) using theSIMPLIS programming language was utilized to evaluate the




adequacy of the two presented models. Alternative goodness of fitindices were selected based on the recommendations of Hu andBentler (1999), with a cutoff value close to .95 for the Tucker LewisIndex (TLI) in combination with a cutoff value close to .09 for thestandardized root mean squared residual (SRMR). The assessment of fit through the evaluation of chi square was not utilized in the currentstudy due to the extensive amount of criticism this method hasreceived; however the statistic has been reported here to inform thereader. The chi-square value as an assessment of fit has been criticizedfor its sensitivity to sample size and lack of robustness to the violationof basic underlying assumptions (Bentler, 1990; Tabachnick & Fidell,1996).

The difference in chi-square estimates between the twocompeting models was also evaluated, as the second model was nestedin the first. Nonsignificant chi-square difference tests suggest that thenested model does not provide a significant improvement over the firstmodel, whereas significant chi-square tests suggest that the nestedmodel provides a significant improvement. This strategy providessupport for the selection of one model over another.

Results

Skewness and kurtosis for the total sample were analyzed andsupported the presence of multivariate normality. Screening of scatterplots between the subscales revealed linear relationships.Finally, tests of Mahalanobis distance were used to identifymultivariate outliers. Table 1 displays the means and standarddeviations for all variables as well as the correlation matrix, which

provided support for the expected relationships. For both path models,maximum likelihood estimation was utilized, and parameter estimationmatrices were positive definite, with no parameter estimates outsidetheir permissible range.




Table 1

Means, Standard Deviations, and Correlation Matrix for the

Five Measures

Measures Means SD 1 2 3 4 51. Fluid Ability (G f ) 35.03 4.24 1.002. Conscientiousness 45.34 5.78 -.13* 1.003. Math Self-Efficacy 135.0

0

19.9

3

0.24*

*

.01 1.00

4. Math Performance 14.90 3.63 0.45*

*

-.06 .

53**

1.00

5. Overall GPA 302.0

0

50.4

4

.09 .

23**

.

19**

.

20**

1.0

0* p < .05. ** p < .01.

Goodness of fit estimates for the first model, for which both G f

and conscientiousness predicted both mathematics performance andoverall GPA, with the direct effects mediated by mathematics self-efficacy, were not adequate when considered in combination ( TLI = .84; SRMR = .02). The chi-square estimate for the first model wassignificant (χ 2 = 3.92, df = 1, p < .05), which also indicated a poor fitto the data. Evaluation of individual parameters (see Figure 3)revealed three nonsignificant relationships, which were also close tozero. The path coefficient for G f and overall GPA and the pathcoefficient for conscientiousness and mathematics self-efficacy as wellas conscientiousness and mathematics performance were .07, .04, and-.02, respectively. Variance accounted for in mathematics self-efficacy

by G f and conscientiousness only reached 6%. Forty percent of thevariance in mathematics performance was accounted for by thevariables G f , mathematics self-efficacy, and conscientiousness. G f ,mathematics self-efficacy, and conscientiousness accounted for 9% of the variance in overall GPA.




Goodness of fit estimates for the second model, whichconsidered G f as a maximal measure of intelligence andconscientiousness as typical by allowing G f to only predictmathematics performance and conscientiousness to only predictoverall GPA with direct effects mediated by mathematics self-efficacy, showed an improvement over the first model ( TLI = .95;SRMR = .03) and indicated an adequate model to data fit. The chi-square estimate for the second model was nonsignificant (χ 2 = 5.76, df = 3, p = .06). Only one path coefficient, the relationship betweenconscientiousness and mathematics self-efficacy, was nonsignificant(see Figure 4). G f and conscientiousness accounted for 6% of thevariance in mathematics self-efficacy, G f and mathematics self-efficacy accounted for 40% of the variance in mathematics

performance, and conscientiousness and mathematics self-efficacyaccounted for 9% of the variance in overall GPA.

To further compare the two models, the difference in chi-square values ( ∆ χ 2 = 1.84, ∆ df = 2, p > .05) was evaluated. Thisnonsignificant value suggested that the second model did not providesignificant improvement over the first. Even so, the second model

provided an adequate fit to the data, whereas the first model did not. Inaddition, only one parameter estimate was found to be nonsignificantin the second model in comparison to three in the first. Therefore, thesecond model, with its theoretical basis that maximal and typicalintelligence are represented by G f and conscientiousness, respectively,seems to have the most support for its acceptance.

Discussion

As expected, we found support that G f and mathematics self-efficacy are important predictors of mathematics performance, withmathematics self-efficacy performing a mediating role. Asdocumented by Pajares and Graham (1999), students’ beliefs abouttheir ability to use their knowledge and skills effectively to solve math

problems deserves more attention in the mathematical domain, as




these beliefs and inherent ability work together to influence performance outcomes. However, this type of fluid ability as tapped by the Cattell’s measure appears to provide little direct effect onacademic outcomes that reflect one’s typical performance, such asoverall GPA.

These findings appear consistent with Goff and Ackerman’s(1992) distinction between typical and maximal intelligence. Becausea test of mathematics performance demands that students demonstratetheir maximal ability. Therefore, it is logical that fluid ability, ameasure of maximal intelligence, provided the strongest relationship,whereas conscientiousness offered little, if any, prediction. Instead,,conscientiousness, which likely reflects typical intelligence, was asignificant predictor of overall GPA, a construct that provides ameasure of daily or typical work. Conscientiousness may be a positiveasset when considering the organization required completing andsubmitting assigned work. In addition, an individual high inconscientiousness would likely arrive to class on time, accomplishassignments in a neat and methodical manner that reduces thelikelihood of error, and express less rebelliousness toward educators.As a result, educators may be more likely to assign higher grades tosuch students, raising their overall GPAs.

The presence of a relationship between conscientiousness andoverall GPA , but the lack of any relationship between G f and overallGPA, may also be a result of other issues. For example, whenstudents’ grades are artificially inflated, then Gf would be of littleinfluence. The effects of mathematics self-efficacy on overall GPAeffect of mathematics self-efficacy on overall GPA would also besuspect in this particular circumstance. We can not be certain how thislevel of confidence affects overall GPA through the students’

persistence and effort. It could be due to pressures felt by faculty toconform to students’ high expectations, a concern identified byLandrum (1999). Although problems associated with grade inflationshould be considered, researchers in this area others have foundevidence to support that grade inflation is not an issue across all




college campuses: Some institutions actually experience gradedeflation, where consistently greater effort is rewarded by higher grades (Kuh & Hu, 1999). This further implies the importance of theconscientiousness construct and of mathematics self-efficacy, whiledownplaying the influence of G f .

In contrast to its role in the relationship between G f andmathematics performance, mathematics self-efficacy did not appear tomediate the effects of conscientiousness on overall GPA, even thoughthe later model in the study provided the best fit to the data of the twomodels considered here. Thus, students who were higher inconscientiousness tended to have higher grades, regardless of theamount of confidence they possessed in their ability to utilize their knowledge and skills successfully to solve mathematics problems.Despite its inability to mediate conscientiousness in this study,mathematics self-efficacy did independently predict students’ overallGPA.

The lack of association between conscientiousness andmathematics self-efficacy seems to contradict the results of others whofound that conscientiousness and motivational variables worked inconjunction to predict academic outcomes (Graziano et al., 1997). Thisdiscrepancy may be related to the measurement of motivationalvariables. In the present study, mathematics self-efficacy wasmeasured in a specific manner that asked by asking students to ratewhat they believed was the best and optimal way they could performon a variety of mathematics problems. Graziano et al. (1997) utilized ameasure of self-competence, a construct that theoretically differs frommathematics self-efficacy as it is more global, affectively based, andrelated to one’s frame of reference. “In self-efficacy judgments thefocus of assessment is on the individual’s capabilities in relation to thespecific criterion items and so the influence of frame of referenceeffects is minimized” (Marsh, Roche, Pajares, & Miller, 1997, p. 364).In other words, when rating self-efficacy, individuals are not likely to

be thinking about how others will perform on the task, but only abouttheir own ability to succeed in the task. Therefore, mathematics self-




efficacy can be directly related to mathematics problems students believe they can successfully solve, without consideration of theaccomplishments of others. This suggests that a larger relationshipexist between, suggesting a greater relationship to students’ abilitiesrather than to their personality, such as their conscientiousness.

The present findings suggest that educators should continue toencourage mathematics self-efficacy, which develops through specific

praise and feedback, mastery experiences, physiological feedback, andvicarious experiences (Bandura, 1986), in order to improve students’mathematics performance. Results indicate that improvements inmathematics self-efficacy will most benefit testing situations or thoseacademic activities that demand maximal performance. In educationalenvironments where standardized testing is increasingly used to makeeducational decisions, the consideration of mathematics self-efficacyseems quite important. However, this apparent strength does notsuggest that mathematics self-efficacy is a great or sole poor predictor of students’ overall GPA. In the current study the relationship wassomewhat small, but significant. In addition, mathematics self-efficacy, a domain-specific measure, was utilized to predict overallGPA, which is a much more global measure. Thus, students’ level of confidence in their ability to use their mathematics skills andknowledge effectively appears related to overall academic concerns.This is not surprising with a sample of university students who wererequired to meet specific criteria related to mathematical skill uponadmission to the institution. Therefore, the generalizability of the

present findings to public school children is cautioned. Even so, theimplementation of strategies to promote higher levels of organizationand on-task behavior or conscientiousness, as suggested by the findingthat conscientiousness is an important predictor of overall GPA, wouldseem to benefit students of all ages. Although personality is sometimesviewed as a relatively unchangeable construct, some Five Factor Model traits may vary across the lifespan. Srivastava, Oliver, Gosling,and Potter (2003) found that conscientiousness tended to increase atdifferent rates throughout early and middle adulthood. Future research






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Figure 1. Model 1. Full model

Fluid AbilityG

f

Mathematics Self-Efficacy

Conscientiousness

Overall GradePoint Average

MathematicsTestPerformance




Figure 2. Model 2. Reduced model

Fluid AbilityG

f


Conscientiousness

Overall Grade PointAverage

Mathematics Test

Performance




Figure 3. Model 1 with parameter estimates.

Fluid AbilityG

f


Conscientiousness

Overall Grade PointAverage

Mathematics Test

Performance

.34

.08 a

.24

.45

.17

.04 a-.02 a

.23

-.13




Figure 4. Model 2 with parameter estimates.

Fluid AbilityG

f


Conscientiousness

Overall GradePoint Average

Mathematics TestPerformance

.35

.24

.45

.19

.04 a

.22

-.13

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