academic achievement the unique contribution of self-efficacy beliefs in

ibe,

nopraisoci

d temeder,ale

y). Aed tpr

2012 Elsevier Inc. All rights reserved.

ent insychol99; Crlmela-Ain inv

Learning and Individual Differences xxx (2012) xxxxxx

LEAIND-00670; No of Pages 5

Contents lists available at SciVerse ScienceDirect

Learning and Indiv

.e lstudent characteristics that can be modied in school practice to pro-mote better academic performance. To this aim, social cognitive theo-rists have stressed the role of Self-Efcacy Beliefs in Self-RegulatedLearning (SESRL) as predictors of academic performance (e.g., Caprara,Vecchione, Alessandri, Gerbino, & Barbaranelli, 2011; Zimmerman &Schunk, 2004). The scope of the present study is to examine the uniquecontribution of SESRL on academic achievement over and beyond therole of other individual predictors such as intelligence, personalitytraits, and self-esteem.

1.1. Individual predictors of academic achievement

cordance to their purposes, to make the effort that is needed tolearn, and to demonstrate persistence. Likewise, adolescents opento experiences may be more apt to learn because they appreciateknowledge and discovery (Caprara et al., 2011). In comparison,agreeableness, emotional instability, and extraversion have notshown consistent signicant associations with academic successas do openness and conscientiousness (e.g., Duff, Boyle, Dunleavy,& Ferguson, 2004; Laidra et al., 2007; Poropat, 2009). Yet, in thepresent work, we prefer to include all of the Big-Five traits inorder to offer a compelling picture of the links between personalityand academic achievement.

In addition, self-esteem (i.e., how people judge themselves asIntelligence has consistently been demodemic achievement (Gagn & St Pre, 2002;2007), even after controlling for gender, prior

Corresponding author at: CIRMPA, Sapienza Univer00185 Roma, Italy. Tel.: +39 0649917665; fax: +39 06

E-mail address: [email protected] (A. Zu

1041-6080/$ see front matter 2012 Elsevier Inc. Alldoi:10.1016/j.lindif.2012.07.010

Please cite this article as: Zufan, A., et al.,beyond intelligence, personality traits, andestigating the early andsuccess at school is easilyfor educators to identify

academic achievement (Caprara et al., 2011; Poropat, 2009). It islikely that conscientious adolescents perform better at school be-cause of their ability to make plans, to regulate their behavior in ac-major psychological predictors of adolescent'sunderstandable. In particular, it is importantSelf-esteemSelf-efcacy beliefs in self-regulated learning

1. Introduction

Academic success exerts a prominlife students as a major indicator of pMartin, Peeke, Seroczynski, & Fier, 19source of rewards and satisfaction (SaAs a consequence, particular interestuence on adolescents'ogical adjustment (Cole,ystal et al., 1994) and aro & Tynkkynen, 2010).

and personality (Di Fabio & Busoni, 2007; Leeson, Ciarrochi, & Heaven,2008). Within the Big-Five Personality model (i.e., openness/intellect,conscientiousness, extraversion, agreeableness, and neuroticism/emotional instability), a comprehensive taxonomy of individualdifferences in personality (McCrae & Costa, 1999), conscientious-ness and openness has been shown to be strongly associated withPersonality traitsAcademic achievementIntelligenceShort Report (Original Research)

Academic achievement: The unique contrself-regulated learning beyond intelligenc

Antonio Zufan a,, Guido Alessandri b, Maria GerbiLaura Di Giunta a, Michela Milioni a, Gian Vittorio Caa Interuniversity Center for Research on the Genesis and Development of Prosocial and Antb Psychology Department, Sapienza University of Rome, Italy

a b s t r a c ta r t i c l e i n f o

Article history:Received 14 December 2011Received in revised form 16 June 2012Accepted 15 July 2012Available online xxxx

Keywords:

The present study examinepredicting academic achievacademic achievement, genipants included 170 (87 femsmall town near Rome (Italregression analysis supportschool year. Theoretical and

j ourna l homepage: wwwnstrated to predict aca-Laidra, Pullman, & Allik,academic achievement,

sity of Rome, Via dei Marsi 78,4469115.fan).

rights reserved.

Academic achievement: Theself-esteem, Learning and Indution of self-efcacy beliefs inpersonality traits, and self-esteemb, Bernadette Paula Luengo Kanacri a,ra b

al Motivations (CIRMPA), Sapienza University of Rome, Italy

he contribution of self-efcacy beliefs in self-regulated learning (SESRL) innt at the end of junior high school above and beyond the effects of previoussocioeconomic status, intelligence, personality traits, and self-esteem. Partic-s) eighth grade students (Mage=13.47) in a junior high school located in all measures were administered at the beginning of eighth grade. Hierarchicalhe unique contribution of SESRL on academic achievement at the end of theactical implications are discussed.

idual Differences

sev ie r .com/ locate / l ind i fworthy of value) has also been associated with academic achieve-ment (Baumeister, Campbell, Kruegger, & Vohs, 2003), mainly as amotivational factor (i.e., students try to excel at school in order tomaintain a general positive image of their self). Social cognitive the-orists have emphasized the pervasive role that SESRL exerts on ad-olescents' academic motivation and achievement (e.g., Bandura,Barbaranelli, Caprara, & Pastorelli, 1996, 2001; Caprara et al., 2008,

unique contribution of self-efcacy beliefs in self-regulated learningividual Differences (2012), doi:10.1016/j.lindif.2012.07.010

2 A. Zufan et al. / Learning and Individual Differences xxx (2012) xxxxxx2011; Zimmerman & Schunk, 2004). In managing their own learning,self-efcacious students are condent in their capacity to meetschool requirements, dutifully plan and organize their academic ac-tivities, perceive difculties as challenges, do not get discouragedby setbacks, persist in their efforts when needed to accomplishschool tasks, select peers who share their same interest in achieve-ment, and contribute to creating conditions that foster learning(Caprara et al., 2008).

Although some studies have considered the combined inuence ofintelligence and personality traits (Farsides & Woodeld, 2003; Laidraet al., 2007), of personality and SESRL (Caprara et al., 2011), and ofself-esteem and SESRL (Lane, Lane, & Kyprianou, 2004), to our knowl-edge, no study has simultaneously addressed the contribution of all ofthese variables on academic achievement. Drawing on the work of sev-eral authors (e.g., Ackerman & Heggestad, 1997; Chamorro-Premuzic &Furnham, 2004), we hypothesized that intelligence, personality traits,self-esteem, and SESRL operate in concert to predict academic perfor-mance by favoring intellectual curiosity, knowledge acquisition (espe-cially openness and intelligence), and motivational effort (especiallyconscientiousness, self-esteem, and SESRL). In conceiving humanpersonality as a system entailing different levels of functioning(e.g., Caprara et al., 2011; McAdams, 1995), one may view intelli-gence, personality traits, and self-esteem as individuals' basic po-tentials (Cattell, 1987; Kamakura, Jukoando, & Ono, 2001; Kendler,Gardner, & Prescott, 1998; Loehlin, McCrae, Costa, & John, 1998),and SESRL as the personal beliefs (mostly derived from experience)that enable people to turn their basic predispositions into proper be-haviors conducive to academic success (Caprara et al., 2008). Fol-lowing this reasoning, we conceptualized SESRL as operating at anintermediate level between basic predispositions and behavior(Caprara et al., 2011). Accordingly, we hypothesized that SESRL atthe beginning of eighth grade (the last year of junior high school inItaly) may exert a unique role in predicting academic achievementat the end of the same school year above and beyond the role of intelli-gence, personality traits, and self-esteem. In testing our hypotheses, wecontrolled previous academic achievement at the end of sixth grade(therst year of junior high school in Italy) and socio-demographic var-iables such as gender and socioeconomic status (SES)which are typical-ly associated with academic success (Lindberg, Hyde, Petersen, & Linn,2010; Nowell & Hedges, 1998; Sirin, 2005).

2. Materials and method

2.1. Participants

The participants were 170 young adolescents (87 females) whowere part of a longitudinal project that started in 2008 with the pri-mary goal of investigating the personal and social determinants of ad-olescents' adjustment. The participating students were drawn fromone public junior high school in Genzano, a community located nearRome. Participants were beginning the eighth grade (Mage=13.47)when data on traits, intelligence, self-esteem, and SESRL measureswere collected. The majority of students were from intact families(93.4%), and only 7.6% were from single-parent homes (separatedor divorced). Approximately 8% of parents held a professional ormanagerial rank; 26% were merchants or operators of other busi-nesses; 26% were skilled workers; 38% were unskilled workers; and2% were unemployed. The majority of parents had a high school de-gree (46.4%), whereas 23.7% had a university degree or beyond. Ap-proximately 20.5% nished middle school and only 9.4% achieved anelementary or less than elementary school education.

2.2. Procedure

We obtained approval for our longitudinal study from the school

council, composed of parent and teacher representatives. A signed

Please cite this article as: Zufan, A., et al., Academic achievement: Thebeyond intelligence, personality traits, and self-esteem, Learning and Indconsent form was subsequently obtained from parents for each stu-dent. All measures (except for academic achievement) were collectedin the classrooms by well-trained researchers who clearly articulatedthe purpose and response choices of the questionnaires to students.

2.3. Measures

Measures of intelligence, personality traits, self-esteem, SESRL,and SES were collected at the beginning of eighth grade during the20092010 school year. Academic achievement was obtained fromschool records at the end of sixth and eighth grades.

SESRL. The SESRL scale (Bandura et al., 1996) includes 9 items(=.85) scored on a 5-point Likert scale (from 1=cannot do at allto 5=highly certain can do). Participants rated their beliefs in theirperceived capability related to self-regulating learning activities,such as the capacity to plan and organize academic activities, the abilityto structure environments conducive to learning, and self-motivationfor academic work (e.g., How well can you study when there areother interesting things to do?).

2.3.1. IntelligenceWe utilized the Italian version of the Culture-Fair Intelligence Test, a

nonverbal measure aimed at measuring individuals' analytic and rea-soning ability (i.e., uid intelligence), for children from 8 to 13 yearsold (Cattel & Cattel, 1987). This instrument comprises two parallelforms (form A and B), each consists of four subtests: series, analogies,matrices, and classication. For our purposes, we considered the meanof forms A and B as a measure of intelligence. The SpearmanBrownsplit-half coefcient of reliability was .77.

2.3.2. Personality traitsParticipants rated their personality traits on 30 items (6 items for

each trait) in a reduced version of the Big-Five QuestionnaireChildren(BFQ-C; Barbaranelli, Caprara, Rabasca, & Pastorelli, 2003). The psycho-metric properties of the BFQ-C have been rmly established in severalsamples of Italian adolescents in junior high schools (Barbaranelli,Fida, Paciello, Di Giunta, & Caprara, 2008). Participants rated the fre-quency of the behavior noted in the item using a 5-point Likert scale(1=almost never to 5=almost always). The openness scale (=.83)included items related to self-reported intellectual attitudes, especiallyin the school domain (e.g., I easily learn what I study at school). Theconscientiousness scale (=.74) assessed the orderliness, precisionand the fullling of commitments (e.g., I only play when I'm nishedmy homework). The extraversion scale (=.72) assessed characteris-tics such as activity, enthusiasm, and self-condence (e.g., I like tojoke). The agreeableness scale (=.71) assessed concern and sensitiv-ity toward others (e.g., I trust in others). The emotional instabilityscale (=.84) included items assessing feelings of anxiety, depression,and anger (e.g., I easily get angry).

2.3.3. Self-esteemWe used the 10-item Rosenberg (1965) self-esteem scale (=.78),

whichmeasures the extent towhich participants feel they possess goodqualities and have achieved personal success (e.g., I feel that I have anumber of good qualities). Each item is scored on a 4-point scale rang-ing from 1=strongly disagree to 4=strongly agree.

2.3.4. Academic achievementChildren's achievement was collected at two time points: at the

end of sixth and eighth grades through the use of original school re-cords. In the Italian school system, teachers evaluate their studentsby using a ten-level gradation for each subject (from1=extremely insuf-cient to 10=excellent). We created a composite measure of academicachievement from grades obtained in the primary school subjects:Italian, math, science, foreign language (English and French), and so-

cial studies.


2.3.5. SESSES was dened using the information reported by the students

concerning their parents' occupation and education. We considerthis variable as the factor score from a conrmatory factorial analysisin which SES was a single dimension dened by parents' education

intelligence, openness, and extraversion remained signicant. In this

3A. Zufan et al. / Learning and Individual Differences xxx (2012) xxxxxxnal step, SESRL explained approximately 2% of the variance in academ-ic achievement at eighth grade; previous academic achievement about18%; intelligence, openness, and extraversion explained respectivelyabout 1%, 2%, and 2% of the variance.

1 A conrmatory factorial analysis supported the separateness of the items of eachconstruct examined in the present study. The results are available upon request tothe rst author.

2 We also repeated the above analyses by considering each specic school subjectone at a time. The contribution of SESRL was found to be statistically signicant3.2. Regression analysis

Table 2 outlines the results of the hierarchical regression analysis. Atthe rst step, only academic achievement at sixth grade signicantlypredicted later academic achievement. The addition of intelligence, per-sonality traits, and self-esteem in the regression equation signicantlyimproved the variance explained. However, only intelligence, openness,and extraversion demonstrated signicant regression coefcients. Thesubsequent addition of SESRL signicantly contributed to the explainedvariance. Accordingly, SESRL predicted academic achievement at eighthgrade, controlling for the effects of all previous variables.2 The effects of3. Results

3.1. Preliminary analyses

Only one student was missing data on academic achievement,whereas some participants had missing values for the other variablesconsidered in this study. The data met the assumption for missingcompletely at random (MCAR): Little (1988) test was not signicant2(85)=88.548, p=.375, namely, the missingness on one variable isunrelated to the other measured or unmeasured variables. In order tonot reduce the number of subjects in the analyses, we computed themaximum-likelihood estimates of missing data via the expectationmaximization algorithm using SPSS 18 (Enders, 2010).

Table 1 presents the means, standard deviations, and zero-ordercorrelations among the variables. Prior and later academic achieve-ments were strongly correlated; self-esteem was uncorrelated withacademic achievement at both sixth and eighth grades. Gender, SES,conscientiousness, openness, and SESRL were all signicantly corre-lated with later academic achievement.and occupation (Caprara et al., 2011). We used the weighted leastsquare minimum variance function of Mplus 5.1 (Muthn & Muthn,2006), particularly recommended for non normal or categorical data(Flora & Curran, 2004), as the method of estimation.

2.4. Analytical approach

Initially, we examined the pattern of missing values of the variablesconsidered in our study. Then,we computed the zero-order correlationsamong all the variables.1 This was followed by a hierarchical regressionanalysis involving the role of intelligence, personality traits, self-esteem,and SESRL as predictors of academic achievement in the eighth grade. Inan effort to control for the impact of previous academic achievement,gender, and SES, these variables were entered in the rst step of the re-gression. The second step included intelligence, personality traits andself-esteem, while the third step included SESRL.(pb .05) in each instance.

Please cite this article as: Zufan, A., et al., Academic achievement: Thebeyond intelligence, personality traits, and self-esteem, Learning and Ind4. Discussion

The above ndings corroborate our hypothesis attesting to theunique contribution of SESRL to the prediction of later academicachievement above and beyond (1) previous academic achieve-ment, (2) gender, (3) SES, (4) intelligence, (5) personality traits,and (6) self-esteem. Gender and SES did not predict academicachievement at eighth grade in any step of our analysis. The beliefsstudents hold about their capacities to regulate their learning, in-stead, resulted one of the most important predictor of success atschool after previous academic achievement. This is in accordancewith social cognitive theory (Bandura, 1997) and highlights the im-portance of previous academic achievement in founding the basis formastery beliefs which, in turn, operate as feedback for the developmentof SESRL thereby further contributing to academic success. In addition,intelligence contributed to predicting academic achievement. This nd-ing is in line with the results of previous studies suggesting the inu-ence of intellectual abilities in fostering students' transitions acrossincreasingly difcult grades (e.g., Laidra et al., 2007).

Openness predicted later academic achievement in accordancewith recent results (Caprara et al., 2011) supporting the signicantimpact of openness on academic achievement in earlier (eighth) rath-er than later (thirteenth) grades. Openness in earlier grades accountsfor success at school above and beyond intelligence, as curiosity andinterest in learning should provide motivation to learn over andabove students' cognitive abilities. However, these same skills maybe less inuential as compared to the more focused discipline that isrequired for learning in subsequent grades. Extraversion negativelyand signicantly predicted academic achievement. This is consistentwith studies reporting a negative association between extraversionand academic performance (Rolfhus & Ackerman, 1999) usuallyexplained in terms of differences in time spent engaging in knowl-edge acquisition with extraverts spending more time socializing andintroverts spending more time studying (Poropat, 2009). Surprising-ly, conscientiousness did not account for later academic achievementas found in other research (Poropat, 2009). This result is likely relatedto the high stability of academic achievement in our study. Accordingto the literature (Poropat, 2009), agreeableness and emotional insta-bility did not predict academic achievement.

General self-esteemdid not exert any signicant inuence on later ac-ademic achievement. This result is not new (Baumeister et al., 2003), andmay mostly depend on the specic conceptualization of self-esteem(Valentine, DuBois, & Cooper, 2004). Indeed, there aremore specicman-ifestations of self-esteem, such as academic self-esteem (i.e., individuals'personal attribution of their own worth in the academic domain), thatmay be more effective predictors of academic performance (Pullmann& Allik, 2008; Valentine et al., 2004). Future studies should consider thepredictive power of academic self-esteem jointly with SESRL.

We believe that SESRL, in comparison to intelligence, personalitytraits, and self-esteem, may have more practical value in academic set-tings. Indeed, social cognitive theorists (Bandura, 1997) have shownhow self-efcacy beliefs can be fostered and changed, principallythrough the mechanisms of mastery experiences and modeling. In thissense, several programs have already reported encouraging resultsabout how self-regulation training for students can improve their aca-demic performance (Randi & Corno, 2000; Zimmerman & Schunk,2004). Conversely, less is known about the possibility of modifying in-telligence and personality traits. Moreover, previous programs thathave tried to improve academic performance through a change inself-esteem have demonstrated null or even counterproductive out-comes (Baumeister et al., 2003).

5. Conclusion

Early learning on how to deal with increasingly challenging school

demands on a daily basis may enable students to avoid experiencing


s, se

.223 .012 .135 .065 .114 .545 .747 1

4 A. Zufan et al. / Learning and Individual Differences xxx (2012) xxxxxxTable 1Descriptive statistics and correlations among gender, SES, intelligence, personality trait

Variables Mean SD 1 2 3 4

1. Gender 12. SES .007 13. Intelligence 30.19 4.44 .079 .043 14. Openness 3.51 0.68 .148 .149 .204 15. Conscientiousness 3.41 0.73 .147 .025 .161 .4206. Extraversion 4.26 0.56 .111 .018 .032 .0377. Agreeableness 3.39 0.62 .163 .075 .023 .2818. Emotional instability 2.69 0.81 .041 .024 .026 .1149. Self-esteem 3.09 0.46 .033 .037 .050 .23710. SESRL 3.69 0.75 .267 .079 .100 .65811. Academic achievement6th

7.53 1.22 .164 .331 .267 .442

12. Academic achievement8th

7.09 0.96 .158 .272 .326 .594

Note. Gender was code 0 = male; 1 = female. SD = standard deviation. pb .10. pb .05.

pb .01. pb .001.school failures which, ultimately, may negatively affect life choices.This is very important in the Italian context, where the transitionfrom junior (sixth to eighth) to senior high school (ninth to thir-teenth) represents a delicate phase in which students, for the rsttime, individually choose the academic path they will follow. Inthis process, the role played by teachers and parents as primary ed-ucational agents capable of helping adolescents in setting their goalsand offering feedback when necessary is irreplaceable (Pajares,2002). Building strong SESRL as early as possible allows studentsto use their self-regulated skills more automatically over subse-quent school years and to take more control of their academiclives. In continuing efforts to increase our knowledge base in thisimportant domain, it is important that future studies (1) replicateour results with non-western students, (2) consider the impact ofSESRL at different school levels, (3) examine the unique role thatSESRL plays when other important predictors of academic achieve-ment, such as prosocial behavior (Caprara, Barbaranelli, Pastorelli,Bandura, & Zimbardo, 2000), parental support (Cutrona, Cole,Colangelo, Assouline, & Russell, 1994), and teacherstudent rela-tionship (Battistich, Schaps, & Wilson, 2004) are taken into account,and (4) integrate the analysis with more subject-specic SESRLmeasures in order to increase the predictive power of SESRL and tospecify its role among different school-subjects.

Table 2Hierarchical regression with academic achievement at eighth grade as dependent variable.

Variables Step 1 Step 2

B p B

Ac. achiev. 6th (.576) .731 .000 (.446)Gender (.071) .037 .477 (.027)SES (.094) .029 .537 (.103)Intelligence (.027)Openness (.409)Conscientiousness (.107)Extraversion ( .243)Agreeableness (.023)Em. instability (.018)Self-esteem ( .072)SESRL

F(3, 166)=70.429, p=.000 F(7, 159)=R2 .56

Note. Unstandardized (reported in parentheses) and standardized regression coefcients with

Please cite this article as: Zufan, A., et al., Academic achievement: Thebeyond intelligence, personality traits, and self-esteem, Learning and Indlf-esteem, SESRL, and academic achievement.

5 6 7 8 9 10 11 12

1.217 1.390 .334 1

.250 .143 .085 1.250 .159 .039 .319 1.661 .162 .356 .224 .191 1.132 .126 .098 .106 .139 .421 1Acknowledgments

This study has been funded by the Italian Ministry of Health as partof a National Strategic Research Program (grant RFPS-2007-5-641730)on child and adolescent mental health.

The authors thank Dr. Beatrice Bridglall, Dr. Richard Fabes, andDr. Carol Martin for their helpful comments on an earlier draft of thisarticle.

References

Ackerman, P. L., & Heggestad, E. D. (1997). Intelligence, personality, and interests: evidencefor overlapping traits. Psychological Bulletin, 121, 219245, http://dx.doi.org/10.1037/0033-2909.121.2.219.

Bandura, A. (1997). Self-efcacy: The exercise of control. New York: Freeman.Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (1996). Multifaceted impact

of self efcacy beliefs on academic functioning. Child Development, 67, 12061222,http://dx.doi.org/10.1111/j.1467-8624.1996.tb01791.x.

Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (2001). Self-efcacy beliefsas shapers of children's aspirations and career trajectories. Child Development, 72,187206, http://dx.doi.org/10.1111/1467-8624.00273.

Barbaranelli, C., Caprara, G. V., Rabasca, A., & Pastorelli, C. (2003). A questionnaire formeasuring the Big Five in late childhood. Personality and Individual Differences,34, 645664, http://dx.doi.org/10.1016/S0191-8869(02)00051-X.

Barbaranelli, C., Fida, R., Paciello, M., Di Giunta, L., & Caprara, G. V. (2008). Assessing per-sonality in early adolescence through self-report and other-ratings: A multitrait

Step 3

p B p

.566 .000 (.414) .526 .000

.014 .767 ( .019) .010 .834

.032 .504 (.139) .043 .359

.124 .012 (.024) .113 .020

.288 .000 (.297) .209 .001

.081 .152 ( .024) .019 .777 .142 .004 ( .254) .148 .002.015 .772 (.013) .008 .871.015 .757 (.036) .030 .526 .035 .485 ( .041) .020 .685

(.278) .218 .0058.368, p=.000 F(1, 158)=8.215, p=.005

.68 .70

their relative p-value.


multimethod analysis of the BFQ-C. Personality and Individual Differences, 44, 876886,http://dx.doi.org/10.1016/j.paid.2007.10.014.

Battistich, V., Schaps, E., &Wilson, N. (2004). Effects of an elementary school interventionon students' connectedness to school and social adjustment during middle school.The Journal of Primary Prevention, 24, 243262, http://dx.doi.org/10.1023/B:JOPP.0000018048.38517.cd.

Baumeister, R. F., Campbell, J. D., Kruegger, J. I., & Vohs, K. D. (2003). Does highself-esteem cause better performance, interpersonal success, happiness, or healthierlifestyles? Psychological Science in the Public Interest, 4, 144, http://dx.doi.org/10.1111/1529-1006.01431.

Caprara, G. V., Barbaranelli, C., Pastorelli, C., Bandura, A., & Zimbardo, P. (2000).Prosocial foundations of children's academic achievement. Psychological Science,11, 302306, http://dx.doi.org/10.1111/1467-9280.00260.

Caprara, G. V., Fida, R., Vecchione, M., Del Bove, G., Vecchio, G. M., Barbaranelli, C., et al.(2008). Longitudinal analysis of the role of perceived self-efcacy for self-regulatedlearning in academic continuance and achievement. Journal of Educational Psycholo-gy, 100, 525534, http://dx.doi.org/10.1037/0022-0663.100.3.525.

Caprara, G. V., Vecchione, M., Alessandri, G., Gerbino, M., & Barbaranelli, C. (2011). Thecontribution of personality traits and self-efcacy beliefs to academic achievement:A longitudinal study. British Journal of Educational Psychology, 81, 7896,http://dx.doi.org/10.1348/2044-8279.002004.

Cattel, R. B., & Cattel, A. K. S. (1987). Culture Fair. Firenze: Organizzazioni Speciali.

Laidra, K., Pullman, H., & Allik, J. (2007). Personality and intelligence as predictors of ac-ademic achievement: A cross-sectional study from elementary to secondary school.Personality and Individual Differences, 42, 441451, http://dx.doi.org/10.1016/j.paid.2006.08.001.

Lane, J., Lane, A. M., & Kyprianou, A. (2004). Self-efcacy, self-esteem and their impacton academic performance. Social Behavior and Personality: An International Journal,32, 247256 [Retrieved from , http://www.sbp-journal.com/index.php/sbp]

Leeson, P., Ciarrochi, J., & Heaven, P. C. L. (2008). Cognitive ability, personality, and ac-ademic performance in adolescence. Personality and Individual Differences, 45,630635, http://dx.doi.org/10.1016/j.paid.2008.07.006.

Lindberg, S. M., Hyde, J. S., Petersen, J. L., & Linn, M. C. (2010). New trends in gender andmathematics performance: A meta-analysis. Psychological Bulletin, 136, 11231135,http://dx.doi.org/10.1037/a0021276.

Little, R. J. A. (1988). A test of missing completely at random for multivariate datawith missing values. Journal of the American Statistical Association, 83, 11981202,http://dx.doi.org/10.2307/2290157.

Loehlin, J. C., McCrae, R. R., Costa, P. T. J., & John, O. P. (1998). Heritabilities of commonand measure-specic components of the Big Five personality factors. Journal of Re-search in Personality, 32, 431453, http://dx.doi.org/10.1006/jrpe.1998.2225.

McAdams, D. P. (1995). What do we know when we know a person? Journal of Person-ality, 63, 365396, http://dx.doi.org/10.1111/j.1467-6494.1995.tb00500.x.

McCrae, R. R., & Costa, P. T., Jr. (1999). A ve-factor theory of personality. In L. Pervin, &O. P. John (Eds.), Handbook of personality: Theory and research (pp. 139153). (2nded.). New York: Guilford Press.

Muthn, L. K., & Muthn, B. O. (2006). Mplus: User's guide. Los Angeles, CA: Muthn &

5A. Zufan et al. / Learning and Individual Differences xxx (2012) xxxxxxScience.Chamorro-Premuzic, T., & Furnham, A. (2004). A possible model to understand the

personalityintelligence interface. British Journal of Psychology, 95, 249264,http://dx.doi.org/10.1348/000712604773952458.

Cole, D. A., Martin, J. M., Peeke, L. A., Seroczynski, A. D., & Fier, J. (1999). Children's over-and underestimation of academic competence: A longitudinal study of gender differ-ences, depression and anxiety. Child Development, 70, 459473, http://dx.doi.org/10.1111/1467-8624.00033.

Crystal, D. S., Chen, C., Fuligni, A. J., Stevenson, H. W., Hau, C. C., Ko, H. J., et al. (1994).Psychological maladjustment and academic achievement: A cross-cultural study ofJapanese, Chinese, and American high school students. Child Development, 65,738753, http://dx.doi.org/10.1111/j.1467-8624.1994.tb00780.x.

Cutrona, C. E., Cole, V., Colangelo, N., Assouline, S. G., & Russell, D. W. (1994). Perceivedparental social support and academic achievement: An attachment theory perspec-tive. Journal of Personality and Social Psychology, 66, 369378, http://dx.doi.org/10.1037/0022-3514.66.2.369.

Di Fabio, A., & Busoni, L. (2007). Fluid intelligence, personality traits and scholastic suc-cess: Empirical evidence in a sample of Italian high school students. Personality andIndividual Differences, 43, 20952104, http://dx.doi.org/10.1016/j.paid.2007.06.025.

Duff, A., Boyle, E., Dunleavy, K., & Ferguson, J. (2004). The relationship between person-ality, approach to learning and academic achievement. Personality and IndividualDifferences, 36, 19071920, http://dx.doi.org/10.1016/j.paid.2003.08.020.

Enders, C. K. (2010). Applied missing data analysis. New York: Guilford Press.Farsides, T., & Woodeld, R. (2003). Individual differences and undergraduate academ-

ic success: The roles of personality, intelligence and application. Personality and In-dividual Differences, 34, 12251243, http://dx.doi.org/10.1016/S0191-8869(02)00111-3.

Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of es-timation for conrmatory factor analysis with ordinal data. Psychological Methods,9, 466491, http://dx.doi.org/10.1037/1082-989x.9.4.466.

Gagn, F., & St Pre, F. (2002). When IQ is controlled, does motivation still predictachievement? Intelligence, 30, 71100, http://dx.doi.org/10.1016/S0160-2896(01)00068-X.

Kamakura, T., Jukoando, & Ono, Y. (2001). Genetic and environmental inuences onself-esteem in a Japanese twin sample. Twin Research, 4, 439442, http://dx.doi.org/10.1375/1369052012768.

Kendler, K. S., Gardner, C. O., & Prescott, C. A. (1998). A population-based twin study ofself-esteem and gender. Psychological Medicine, 28, 14031409, http://dx.doi.org/10.1017/S0033291798007508.Please cite this article as: Zufan, A., et al., Academic achievement: Thebeyond intelligence, personality traits, and self-esteem, Learning and IndMuthn.Nowell, A., & Hedges, L. V. (1998). Trends in gender differences in academic achieve-

ment from 1960 to 1994: An analysis of differences in mean, variance, and extremescores. Sex Roles, 39, 2143 (Retrieved from , http://www.eric.ed.gov/)

Pajares, F. (2002). Gender and perceived self-efcacy in self-regulated learning. Theoryinto Practice, 41, 116125 [(Retrieved from , http://www.eric.ed.gov/)]

Poropat, A. E. (2009). A meta-analysis of the ve-factor model of personality and academ-ic performance. Psychological Bulletin, 135, 322338, http://dx.doi.org/10.1037/a0014996.

Pullmann, H., & Allik, J. (2008). Relations of academic and general self-esteem to schoolachievement. Personality and Individual Differences, 45, 559564, http://dx.doi.org/10.1016/j.paid.2008.06.017.

Randi, J., & Corno, L. (2000). Teacher innovations in the self-regulated learning. In M.Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation(pp. 651685). San Diego, CA: Academic Press.

Rolfhus, E., & Ackerman, P. (1999). Assessing individual differences in knowledge:Knowledge, intelligence, and related traits. Journal of Educational Psychology, 91,511526, http://dx.doi.org/10.1037/0022-0663.91.3.511.

Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: PrincetonUniversity Press.

Salmela-Aro, K., & Tynkkynen, L. (2010). Trajectories of life satisfaction across the tran-sition to post-compulsory education: Do adolescents follow different pathways?Journal of Youth and Adolescence, 39, 870881, http://dx.doi.org/10.1007/s10964-009-9464-2.

Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic re-view of research. Review of Educational Research, 75, 417453, http://dx.doi.org/10.3102/00346543075003417.

Valentine, J. C., DuBois, D., & Cooper, H. (2004). The relation between self-beliefs andacademic achievement: A meta-analytic review. Educational Psychologist, 39,111133, http://dx.doi.org/10.1207/s15326985ep3902_3.

Zimmerman, B. J., & Schunk, D. H. (2004). Self-regulating intellectual processes andoutcomes: A social cognitive perspective. In D. Y. Dai, & R. J. Sternberg (Eds.), Mo-tivation, emotion, and cognition: Integrative perspectives on intellectual functioningand development (pp. 143174). Mahwah, NJ: Lawrence Erlbaum.Cattell, R. B. (1987). Intelligence: Its structure, growth, and action. New York: Elsevierunique contribution of self-efcacy beliefs in self-regulated learningividual Differences (2012), doi:10.1016/j.lindif.2012.07.010

Academic achievement: The unique contribution of self-efficacy beliefs in self-regulated learning beyond intelligence, personality traits, and self-esteem1. Introduction1.1. Individual predictors of academic achievement

2. Materials and method2.1. Participants2.2. Procedure2.3. Measures2.3.1. Intelligence2.3.2. Personality traits2.3.3. Self-esteem2.3.4. Academic achievement2.3.5. SES

2.4. Analytical approach

3. Results3.1. Preliminary analyses3.2. Regression analysis

4. Discussion5. ConclusionAcknowledgmentsReferences

academic achievement the unique contribution of self-efficacy beliefs in

Documents