Evaluación de modelo social cognitivo
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An assessment of a socialndashcognitive model of academic performance in mathematicsin Argentinean middle school students
Marcos Cupani a Mariacutea Cristina Richaud de Minzi b Edgardo Rauacutel Peacuterez a Ricardo Marcos Pautassi ac
a Laboratorio de Psicologiacutea de la Personalidad Universidad Nacional de Coacuterdoba Ciudad Universitaria Coacuterdoba 5000 Argentinab Centro Interdisciplinario de Investigaciones en Psicologiacutea Matemaacutetica y Experimental (CIIPME-CONICET) Buenos Aires Argentinac Instituto de Investigaciones Medicas M y M Ferreyra (INIMEC ndashCONICET) Friuli 2434 Coacuterdoba Coacuterdoba 5016 Argentina
a b s t r a c ta r t i c l e i n f o
Article historyReceived 20 February 2009
Received in revised form 18 March 2010
Accepted 20 March 2010
Keywords
Self-ef 1047297cacy
Outcome expectations
Performance goals
Academic performance
This study tested a set of hypotheses derived from the model of academic achievement in mathematics of theSocial Cognitive Career Theory in a sample of Argentinean middle school students To this aim 277 students
(male and female age 13ndash15 years) were assessed using the following instruments logicalndashmathematical
self-ef 1047297cacy scale mathematics outcome expectations mathematics performance goals and mathematics
ability test All of these instruments had been adapted for use in Argentinean students Academic
achievement in mathematics (ie grades obtained on regular school exams) was the variable to be modeled
through the path analysis technique The analysis allowed identi1047297cation of interrelations among the
variables and identi1047297cation of direct and indirect effects Academic achievement in mathematics was
partially explained by the model Overall the results support the theoretical postulates of Social Cognitive
Career Theory
copy 2010 Elsevier Inc All rights reserved
1 Introduction
Recent years have seen a growing trend toward applying Banduras
socialndashcognitivetheory (1986) to career behavior (Lent Brown amp Hackett
2002) A parallel line of research uses socialndashcognitive theory as a
framework for scrutinizing academic motivation and achievement These
two branches have focused on developmentally linked skill domains
produced complementary 1047297ndings on the correlates and effects of
cognitive-expectancy variables and been guided by similar conceptuali-
zations of educationalndashvocational functioning Noting such commonali-
ties a theory has been proposed to unify the socialndashcognitive framework
in order to conceptualize and study both career and academic behavior
(Lent Brown amp Hackett 1994)
The Social Cognitive Career Theory (SCCT) explains the devel-
opment of vocational interests career choice and academic
performance using different but interrelated theoretical models
Based on Bandurasgeneral socialcognitivetheory(1986)theSCCT
focuses on the triadic interaction among person environment and
behavior and howthis interaction shapes careerdevelopment Self-
ef 1047297cacy beliefs (ie a persons judgment about his or her ability to
properly execute a set of actions) outcome expectations (ie
imagined consequences of performing particular behaviors) and
goals (ie determination to engage in a particular activity or affect
a particular outcome) are central among these variables The SCCTis also focused on the causalpaths by which additional personal and
environmental inputs (eg raceethnicity ability and educational
experiences) in1047298uence career outcomes
The SCCTs performance model (Fig 1) hypothesizes that cognitive
ability in1047298uences student performance directly (through academic-
related skills) and indirectly (through self-ef 1047297cacy beliefs and outcome
expectations) College academic achievement therefore could relate to
abilities and knowledge acquired during the educational and social
trajectories of a given student These trajectories involve a sequence of
challenges and key events (such as performance accomplishments)
occurring in high school and college in which students are given the
opportunity to develop skills (eg studying and taking tests) academic
self-ef 1047297cacy beliefs and outcome expectations that contribute to
academic success Those who develop these expectations will be more
likely to approach (and less likely to avoid) challenging academic tasks
(Lent et al 1994)
The SCCT posits that self-ef 1047297cacy and outcome expectations affect
performance through the intervening in1047298uence of students performance
goals Thus students with stronger self-ef 1047297cacy beliefs and outcome
expectations will set and work toward more challenging academic goals
than those with weaker self-ef 1047297cacy beliefs or less positive outcome
expectations (Lent et al 1994)
Studies have examined subsets of this model Meta-analyses have
yielded correlations of 38and 50between self-ef 1047297cacy beliefs andcollege
academic performance(MultonBrown amp Lent 1991 Robbins et al 2004
respectively) Robbins et al (2004) reported a fully corrected correlation
Learning and Individual Differences 20 (2010) 659ndash663
This work was supported by Agencia Nacional de Promocion Cienti1047297ca y Tecnologica
(Argentina) PICT 07-255grant fromConsejo Nacional de Investigaciones Cientiacute1047297cas(MC)
and grant PRH-UNC (FONCyT-SPU) (Argentina) to RMP
Corresponding author Telfax +54 351 4334104
E-mail address mcupanipsycheunceduar (M Cupani)
1041-6080$ ndash see front matter copy 2010 Elsevier Inc All rights reserved
doi101016jlindif201003006
Contents lists available at ScienceDirect
Learning and Individual Differences
j o u r n a l h o m e p a g e w w w e l s ev i e r c o m l o c a t e l i n d i f
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of 39 between cognitive ability and academic performance This meta-
analysis found support via fully corrected bivariate correlations for each
hypothesized path (28 between self-ef 1047297cacy and cognitive ability 49
between academic self-ef 1047297cacy beliefs and academic goals 18 betweenacademic goals andperformanceall pb 05)Recently Brown et al(2008)
provided substantial support for SCCTs model of academic performance
but the correlation between goals and academic performance did not
achieve statistical signi1047297canceTo ourknowledge a large scale assessment
of the complete performance model has yet to be published
Mathematics self-ef 1047297cacy can be operationalized at different
speci1047297city levels (Betz amp Hackett 2006 Lent amp Brown 2006) The
present work de1047297ned this concept as the students belief in his or her
ability to perform math-related tasks Self-ef 1047297cacy beliefs also act in
concert with other common mechanisms of personal agency such as
self-concept beliefs (Pajares amp Graham 1999) Self-concept is usually
measured at a broader level of speci1047297city and includes the evaluation of
a given competence and the feelings of self-worth associated with that
skill Self-concept differs from self-ef 1047297cacy in that it is a context-speci1047297cassessment of thecompetence to perform a speci1047297ctask(Pajares 1996)
Self-ef 1047297cacy beliefs represent an important bridge between educa-
tional and vocational psychology (Betz amp Hackett 2006) The area of
mathematics hasbeen thefocus of substantial research (Pajaresamp Schunk
2001) Mathematics knowledge and scores are usually decisive for level
placement and admission to college and have been usually considered a
critical barrier for high school students aiming at scienti1047297c and technical
careers (Sells 1980) Most empirical research on the SCCT has focused on
the 1047297eld of science technology engineering and mathematics (STEM)
STEM-relatedself-ef 1047297cacy explains a substantial amountof thevariancein
STEM goals interests choices and performance (Ferry Fouad amp Smith
2000 OBrien Martinez-Pons amp Kopala 1999) Social cognitive research
has also mainly focused on high school (eg Lopez Lent Brown amp Gore
1997 OBrien et al 1999) or college students (eg Ferry et al 2000Lentet al 2001) Only a few studies assessed the utility of SCCT to measure
math and science goal intentions of an ethnically diverse group of middle
school students (eg Fouad amp Smith 1996 Navarro Flores amp Worthing-
ton 2007) Moreover US college students have been the subjects in the
vast majority of SCCT studies Still unknown however is how well the
SCCT generalizes to the educational and career development of younger
(or older) persons from diverse national contexts and across different
domains of academic and career activity (eg Lent Brown Nota amp Soresi
2003)
Lent et al (1994) focused their research on late adolescence and
early adulthood developmental periods likely to involve exploration
and implementation of career choices Previous research however
found that it is during middle school when students begin to acquire
academic abilitiesand take decisions that will have a strongimpact on
later academic outcomes (eg Fouad amp Smith 1996 Turner amp Lapan
2005) It is thus important to understand how social cognitive
mechanisms in1047298uence the development of performance in middle
school studentsThe present study executed a global comprehensive assessment of
the SCCT model in the domain of mathematics in a sample of
Argentinean middle school students According to the Argentine
Program for InternationalStudent Assessment academic mathematics
performance in this population has been very disappointing ( Organi-
zation for Economic Cooperation and Development 2001) Therefore
the present study also sought to provide information relevant to
increase academic success in this population
Consistent with the SCCTs basic academic performance hypotheses
(Lent et al 1994) we predicted that (i) mathematics abilities will be
signi1047297cantly and positively related to academic performance in
mathematics (hypothesis 1 H1) (ii) logicalndashmathematical self-ef 1047297cacy
beliefs will partially mediate the relationship between mathematics
abilities and academic performance in mathematics (H2) (iii) mathe-matics outcome expectations will fully mediate the relationship
between mathematics abilities and academic performance in mathe-
matics (H3) (iv) self-ef 1047297cacy beliefs will be signi1047297cantly and positively
related to academic performance in mathematics (H4) (v) performance
goals in mathematics will partially mediate the relationship between
logical and mathematical self-ef 1047297cacy beliefs and academic perfor-
mance in mathematics (H5) (vi) performance goalsin mathematicswill
fully mediate the relationship between math outcome expectations and
academic performance in mathematics (H6) and (vii) performance
goals in mathematics will be signi1047297cantly and positively related to
academic performance in mathematics (H7)
2 Methods
21 Participants
Two-hundred seventy-seven 8th (458) and 9th (534) graders
participated in the study (175 boys and 102 girls M age=1374plusmn
67 years) Students were enrolled in private educational institutions
in Cordoba Argentina thus representing a socioeconomic microcosm
of the larger society and belonging to families of skilled workers
large-production farmers professionals and local merchants
22 Instruments
221 Mathematics outcome expectations
The Mathematics Outcome Expectations Scale (MOES Cupani in
press) is a modi1047297ed version of the MathematicsScience Outcome
Fig 1 Social Cognitive Career Theory Performance Model Model of task performance highlighting the role of ability self-ef 1047297cacy outcomes expectations and performance goals
(adapted from Lent et al 1994)
660 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
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Expectations Scale (MSOES Fouad Smith amp Enochs 1997) The scale
consists of nine items assessing middle school students beliefs about
the potential consequences of mathematics-related courses activities
and achievements Participants rated each item (eg ldquoIf I learn math I
will have more options when choosing my majorrdquo) on a 5-point scale
ranging from 1 (agreetotally)to 5 (disagreetotally) Item scoreswere
summed and divided by 9 MOES have adequate reliability and
construct validity (Cupani in press) The present study yielded a
Cronbachs alpha of 83 for MOES scores
222 Mathematics performance goals
The Mathematics Performance Goals Scale (MPGS Cupani in
press) isthemodi1047297ed version of the subscale for MathematicsScience
Intentions and Goals Scale (MSIGS Fouad et al 1997) It has 10 items
assessing middle school students intentions to pursue and persist in
mathematics-related courses in high school Participants rated each
item (eg ldquoThis year I propose to get good gradesin mathematicsrdquo) on
a 5-point scale ranging from 1 (agree totally) to 5 (disagree totally)
Scores were summed and divided by 10 MPGS have adequate
reliability and construct validity (Cupani in press) The present study
yielded a Cronbachs alpha of 87 for MPGS scores
223 Logicalndashmathematical self-ef 1047297cacy
The LogicalndashMathematical Self-ef 1047297cacy Scale (LMSS) has six items
and participants rated each item (eg ldquoSolve mathematics equationrdquo)
on a 10-point scale ranging from 1 (Cannot do at all) to 10 (Certain
can do) The scores were summed and divided by 6 The present study
yielded a Cronbachs alpha of 83 for LMSS scores Originally this scale
was included in the revised version of the Multiple Intelligences Self-
Ef 1047297cacy Inventory (MISEI-R) which has adequate reliability and
construct validity (Peacuterez amp Cupani 2008)
224 Mathematics abilities
The Numerical Reasoning subscale of the Differential Aptitude
Test Version 5 was used (Bennett Seashore amp Wesman 2000) The
Numerical Reasoning subscale measures the ability to use numbers ina logical and ef 1047297cient way In the present study a Kuder Richardson
(KR-20) coef 1047297cient of 81 was found for Numerical Reasoning scores
225 Academic Performance in Mathematic
Academic Performance in Mathematic (APM) was assessed by
accessing the students high school records for mathematics courses
In Argentina students are assessed at mid-term (June) and at the end
of the academic year (December) Grades are given on a 10-point
scale with 7 the cut-off for passing a course The two assessments
(which were highly correlated r =78 p b 001) were summed and
divided by 2 No signi1047297cant differences in APM were found between
grades (8th vs 9th t 275 647 pN 05) Therefore the groups were
pooled for subsequent analyses
23 Procedure
All measurements including consent forms were gathered within
a single class period during the 1047297rst class term Tests were taken
collectively during the course of a regular school day at four
educational institutions and in three different sessions Detailedinstructions on how to complete the survey were provided to the
students by the researcher The measures were taken following the
theoretical and causal links proposed by the SCCT The Numerical
Reasoning subtest was administered during the 1047297rst session (April)
one college per week followed 1 month later by the MOES and LMSS
(second session) The MPGS was applied about 3 weeks later (third
session) Mathematics grade scores for each student were collected
directly from school records at the end of the second school term
3 Results
31 Preliminary analyses
Univariate atypical cases (ie zN329 two-tailed test p b001)
were identi1047297ed by calculating standard scores for each variable
Atypical multivariate cases were identi1047297ed through the Mahalanobis
test (Tabachnick amp Fidell 2001 p b 001) As a result of these tests
four cases were removed from the dataset Multivariate normality
was evaluated by Mardia ratio (3202 p N 05) Across variables the
values for asymmetry and kurtosis were optimal for the proposed
parametric analysis (minus85 tominus08andminus48to 92 respectively George
amp Mallery 2001)
Table 1 presents zero-order correlation coef 1047297cients for the
measures All variables were signi1047297cantly correlated with math
performance mathematics performance goals (r =40) mathematics
abilities (r =47) and logicalndashmathematical self-ef 1047297cacy (r =54)
32 Path analysis
Model 1047297t should be assessed using several indices to ensure more
reliable and accurate decisions (Hu amp Bentler 1995) Therefore the
following indices were employed the χ 2 test of signi1047297cance the ratio
of the χ 2 statistic to degrees of freedom (χ 2 df ) the comparative 1047297t
index (CFI) the goodness-of-1047297t index (GFI) and the rootndashmeanndash
square error of approximation (RMSEA) When this ratio is less than
30 a good model 1047297t can be inferred (Kline 2005) CFI and GFI values
between ge90 and ge95 and RMSEA values between le05 and le08
indicate of good model 1047297t (Hu amp Bentler 1995)
Table 1
Descriptive data and interrelation between variables pertinent to the model
Descriptive Interrelation
Variables M SD AS KS MA LMS MOE MPG MP
Mathematics Ability (MA) 2008 647 minus08 minus48 100 40 02 05 47
Logic-Math Self-ef 1047297cacy (LMS) 694 167 minus85 55 100 25 38 54
Math Outcome Expectations (MOE) 360 73 minus49 24 100 39 24
Math Performance Goals (MPG) 343 74 minus68 92 100 40
Math Performance (MP) 603 183 minus22 minus35 100
pb 05 pb 01
Note The Mathematics abilities (MA) is from the Numerical Reasoning subscale of the Differential Aptitude Test Version 5 ( Bennett et al 2000) The LogicalndashMathematical Self-
ef 1047297cacy Scale (LMSS) is from the revised version of the Multiple Intelligences Self-Ef 1047297cacy Inventory (MISEI-R Peacuterez amp Cupani 2008) the Mathematics Outcome Expectations is
from the Mathematics Outcome Expectations Scale (MOES Cupani in press) modi1047297ed version of the subscale for MathematicsScience Intentions and Goals Scale (MSIGS Fouad
et al 1997) the Mathematics Performance Goals is from the Mathematics Performance Goals Scale (MPGS Cupani in press) modi1047297ed version of the subscale for Mathematics
Science Intentions and Goals Scale (MSIGS Fouad et al 1997) Academic Performance in Mathematic (APM) was assessed by accessing the students high school records for
mathematics courses Gradesare given on a 10-point scalewith7 thecut-offfor passing a course Allvalues representrawnonstandardized scores MmeanSD standard deviation
Ss skewness Ks kurtosis Interrelation zero-order correlations
661M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
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All indices revealed optimal model adjustment (CFI= 99
CFI=99 RMSEA=06 χ 2=4308 p =116 CMINDF=2154) The
residuals were also small (median= 000 range=minus37 to07)
Therefore the 1047297tness of the model appears strong enough to allow
the report and interpretation of the standardized path estimates
(Browne MacCallum Kim Anderson amp Glaser 2002) Fig 2 depicts
the path coef 1047297cients for the proposed relationships among the
variables in the theoretical model
The SCCT postulates indirect relationships among key variables To
assess these speci1047297c hypotheses we used Sobels test to examine
indirect effects in the recursive model under scrutiny (Kline 2005)
Table 2 presents of total direct and indirect effects of variables The
test strongly supported the theoretical proposal yielding a signi1047297cant
and positive relationship between mathematics performance and
mathematics abilities (H1 β =34 pb 01) logicalndashmathematical self-
ef 1047297cacy (H4 β =30 pb 01) and mathematics performance goals
(H7 β =27 p =01)
With regard to indirect effects an effect of academic abilities onmathematics performance was observed that was mediated by logicalndash
mathematical self-ef 1047297cacy beliefs (H234times 30= 10 z=524 pb 000)
The total effect of academic abilities was 44 (34+[34times30]) H3
however was not corroborated by our data The relationship between
abilities and expectations was negative and far from reaching
signi1047297cance (β=minus10 p=13)The analysis also allowed an estimation
of the predictive contribution of logicalndashmathematical self-ef 1047297cacy
beliefs (H530times 27=08 z =362 pb 000) and mathematics outcome
expectations (H6 31times27=09 z=332 pb 000) on mathematics
performance goals A positive and signi1047297cant ( β =29 pb 01) associ-
ation was also found between logicalndashmathematical self-ef 1047297cacy beliefs
and mathematics outcome expectations The total effect of self-ef 1047297cacy
on mathematics performance goals was 39 (30+[29times31] z =344
pb 000) Therefore the total contribution of self-ef 1047297cacy beliefs to
mathematics performance is 40 whereas the indirect contribution of
outcome expectation to mathematics performance mediated by
performance goals is 09
In summary the model generally explained 44 of the variance of academic achievement in mathematics Mathematics abilities
explained 16 of the variance of logicalndashmathematical self-ef 1047297cacy
beliefs With regard to H5 and H6 the results indicated that self-
ef 1047297cacy beliefs and outcome expectations explained 23 of the
variance of performance goals Self-ef 1047297cacy beliefs about outcome
expectations also provided a signi1047297cant contribution
4 Discussion
The present study conducted in a sample of Argentinean high-
school students strongly supported the theoretical model of academic
performance in mathematics of the SCCT Thecurrent1047297ndings suggest
that success in academic performance among Argentinean students is
associated with greater mathematics ability strong beliefs about this
ability and more optimistic and demanding performance targets
These successful students also have higher self-ef 1047297cacy beliefs
Moreover students who set more demanding performance targets
are those with higher self-ef 1047297cacy beliefs and higher expectations of
positive results The study replicates and extends early work
conducted in US students (eg Brown et al 2008)
An obvious yet important difference between the present and
previous studies is that students in this study belong to a Latin-
American population The cross-cultural validity of the SCCT has
recently become an increasingly popular focus of career inquiry (Lent
amp Sheu 2010) Most of this research however has been conducted
with Americans of foreign descent (eg MexicanndashAmericans Navarro
et al 2007) Lent et al (2001) argued for the need to examine the
validity of the SCCT in culturally diverse groups Research conducted
in Western contexts has identi1047297ed intrapersonal and contextualfactors relating to academic performance Country characteristics
such as average income socialinequality andcultural valuesmight be
associated with student achievement directly or indirectly via family
or motivation (Chiu amp Xihua 2008) Our study represents important
progress in this direction
One limitation of generalizing these 1047297ndings relates to the
representativeness of the sample Only students attending private
schools were included thus the results should not be generalized to
students from low socioeconomic status or attending state-based
Fig 2 Standardized path coef 1047297cients from the Social Cognitive Model of Academic Performance in Mathematics (Lent et al 1994) found in a sample of Argentinean middle school
students Standardized path coef 1047297cients and signi1047297cance level are depicted over each path ( pb
001)
Table 2
Decomposition of total direct and indirect effects of variables from the path analysis
Effect Direct effect Indirect effect Total effect
Logic-Mathematics Self-ef 1047297cacy
Mathematics Ability 40 00 40
Outcome expectations
Mathematics Ability minus10 11 02
Logic-Mathematics Self-ef 1047297cacy 29 00 29
Performance goals
Mathematics Ability 00 13 13
Logic-Mathematics Self-ef 1047297cacy 30 08 38
Outcome Expectations 31 00 31
Mathematics performance
Mathematics Ability 34 10 44
Logic-Mathematics Self-ef 1047297cacy 30 10 40
Outcome Expectations 00 09 09
Performance Goals 27 00 27
pb 01 pb 001
662 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
8192019 Evaluacioacuten de modelo social cognitivo
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institutions Future research should use a more heterogeneous sample
and explicitly assess the socioeconomic status of the students
Another limitation is that the measurement for academic achieve-
ment in mathematics canbe in1047298uenced by the idiosyncratic policies of
each institution or the educational orientation of each instructor Also
we acknowledge that our instrument measures math self-ef 1047297cacy
beliefs at a general rather than at a speci1047297c level The evidence shows
that the predictability of self-ef 1047297cacy measures depends on their
speci1047297
city and correspondence to actual math performance tasks(Bandura 1997) That is predictors and dependent variables must be
compatible in regards with content context temporal orientation and
speci1047297city level (Ajzen 1988) Future studies should aim at creating
new math self-ef 1047297cacy scales that measure this construct at a speci1047297c
level
Themain theoretical contributionof this study is the assessment of
theSCCT performancemodel in a novel cultural and linguistic context
namely middle school students in Argentina Interestingly the study
assessed all SCCT predictors jointly To our knowledge the literature
has yet to show a single large-scale test of the complete performance
model although numerous studies have examined subsets of the
model (eg Brown et al 2008) Thedevelopmental stage in which the
model is tested also deserves attention Early adolescence is a critical
stage for learning (Zimmerman Bonner amp Kovach 1996) character-
ized by a sharp decline in academic performance possibly caused by
the increasing challenges posed by middle school as well as the
inherent psychological and biological changes that occur during this
period
Beyond these theoretical implications the results suggest that the
SCCT could be used as a screening tool to identify students at-risk for
having for example diminished self-ef 1047297cacy in a given academic
domain Educational institutions could use this knowledge to design
experiences speci1047297cally aimed at improving these variables Notably
adolescents usually have limited knowledge about their capabilities
and career options a fact that results in stereotyped and unstable
vocational goals (Lent et al 2004) Therefore the development of
career goals can be halted early in life if the students are exposed to
educational environments that provide limited opportunities for
nurturing appropriate ef 1047297cacy or self-ef 1047297cacy skills and outcomeexpectations The results outlined in the present study could be used
to design interventions aimed at increasing the level of exposure to a
variety of career-relevant tasks and activities These interventions will
help develop task-speci1047297c concepts of self-ef 1047297cacy that in turn will
result in more realistic stable and useful vocational goals
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Pajares F amp Schunk D H (2001) Self-beliefs and school success Self-ef 1047297cacy self-concept and school achievement In R J Riding amp S Rayner (Eds) Self Perception(pp 239minus266) Westport CT Ablex Publishing
Peacuterez E amp Cupani M (2008) Multiple intelligences self-ef 1047297cacy inventory revised(MISEI-R) Preliminary validation Revista Latinoamericana de Psicologiacutea 40 47minus58
Robbins S B Lauver K Le H Davis D Langley R amp Carlstrom A (2004) Dopsychosocial and study skill factors predict college outcomes A meta-analysisPsychological Bulletin 130 261minus288
SellsL W(1980) Themathematical 1047297lter andthe educationof women andminorities
In L H Fox L Brodey amp D Tobin (Eds) Women and the mathematical mystique(pp 66minus75) Baltimore Johns Hopkins University
Tabachnick B Gamp Fidell L S (2001) Using multivariate statistics 4thEd Boston Allynand Bacon
Turner S L amp Lapan R T (2005) Evaluation of an intervention to increase non-traditional career interests and career-related self-ef 1047297cacy among middle-schooladolescents Journal of Vocational Behavior 66 516minus531
Zimmerman B J Bonner S amp Kovach R (1996) Developing self-regulated learnersBeyond achievement to self-ef 1047297cacy Washington DC American PsychologicalAssociation
663M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 25
of 39 between cognitive ability and academic performance This meta-
analysis found support via fully corrected bivariate correlations for each
hypothesized path (28 between self-ef 1047297cacy and cognitive ability 49
between academic self-ef 1047297cacy beliefs and academic goals 18 betweenacademic goals andperformanceall pb 05)Recently Brown et al(2008)
provided substantial support for SCCTs model of academic performance
but the correlation between goals and academic performance did not
achieve statistical signi1047297canceTo ourknowledge a large scale assessment
of the complete performance model has yet to be published
Mathematics self-ef 1047297cacy can be operationalized at different
speci1047297city levels (Betz amp Hackett 2006 Lent amp Brown 2006) The
present work de1047297ned this concept as the students belief in his or her
ability to perform math-related tasks Self-ef 1047297cacy beliefs also act in
concert with other common mechanisms of personal agency such as
self-concept beliefs (Pajares amp Graham 1999) Self-concept is usually
measured at a broader level of speci1047297city and includes the evaluation of
a given competence and the feelings of self-worth associated with that
skill Self-concept differs from self-ef 1047297cacy in that it is a context-speci1047297cassessment of thecompetence to perform a speci1047297ctask(Pajares 1996)
Self-ef 1047297cacy beliefs represent an important bridge between educa-
tional and vocational psychology (Betz amp Hackett 2006) The area of
mathematics hasbeen thefocus of substantial research (Pajaresamp Schunk
2001) Mathematics knowledge and scores are usually decisive for level
placement and admission to college and have been usually considered a
critical barrier for high school students aiming at scienti1047297c and technical
careers (Sells 1980) Most empirical research on the SCCT has focused on
the 1047297eld of science technology engineering and mathematics (STEM)
STEM-relatedself-ef 1047297cacy explains a substantial amountof thevariancein
STEM goals interests choices and performance (Ferry Fouad amp Smith
2000 OBrien Martinez-Pons amp Kopala 1999) Social cognitive research
has also mainly focused on high school (eg Lopez Lent Brown amp Gore
1997 OBrien et al 1999) or college students (eg Ferry et al 2000Lentet al 2001) Only a few studies assessed the utility of SCCT to measure
math and science goal intentions of an ethnically diverse group of middle
school students (eg Fouad amp Smith 1996 Navarro Flores amp Worthing-
ton 2007) Moreover US college students have been the subjects in the
vast majority of SCCT studies Still unknown however is how well the
SCCT generalizes to the educational and career development of younger
(or older) persons from diverse national contexts and across different
domains of academic and career activity (eg Lent Brown Nota amp Soresi
2003)
Lent et al (1994) focused their research on late adolescence and
early adulthood developmental periods likely to involve exploration
and implementation of career choices Previous research however
found that it is during middle school when students begin to acquire
academic abilitiesand take decisions that will have a strongimpact on
later academic outcomes (eg Fouad amp Smith 1996 Turner amp Lapan
2005) It is thus important to understand how social cognitive
mechanisms in1047298uence the development of performance in middle
school studentsThe present study executed a global comprehensive assessment of
the SCCT model in the domain of mathematics in a sample of
Argentinean middle school students According to the Argentine
Program for InternationalStudent Assessment academic mathematics
performance in this population has been very disappointing ( Organi-
zation for Economic Cooperation and Development 2001) Therefore
the present study also sought to provide information relevant to
increase academic success in this population
Consistent with the SCCTs basic academic performance hypotheses
(Lent et al 1994) we predicted that (i) mathematics abilities will be
signi1047297cantly and positively related to academic performance in
mathematics (hypothesis 1 H1) (ii) logicalndashmathematical self-ef 1047297cacy
beliefs will partially mediate the relationship between mathematics
abilities and academic performance in mathematics (H2) (iii) mathe-matics outcome expectations will fully mediate the relationship
between mathematics abilities and academic performance in mathe-
matics (H3) (iv) self-ef 1047297cacy beliefs will be signi1047297cantly and positively
related to academic performance in mathematics (H4) (v) performance
goals in mathematics will partially mediate the relationship between
logical and mathematical self-ef 1047297cacy beliefs and academic perfor-
mance in mathematics (H5) (vi) performance goalsin mathematicswill
fully mediate the relationship between math outcome expectations and
academic performance in mathematics (H6) and (vii) performance
goals in mathematics will be signi1047297cantly and positively related to
academic performance in mathematics (H7)
2 Methods
21 Participants
Two-hundred seventy-seven 8th (458) and 9th (534) graders
participated in the study (175 boys and 102 girls M age=1374plusmn
67 years) Students were enrolled in private educational institutions
in Cordoba Argentina thus representing a socioeconomic microcosm
of the larger society and belonging to families of skilled workers
large-production farmers professionals and local merchants
22 Instruments
221 Mathematics outcome expectations
The Mathematics Outcome Expectations Scale (MOES Cupani in
press) is a modi1047297ed version of the MathematicsScience Outcome
Fig 1 Social Cognitive Career Theory Performance Model Model of task performance highlighting the role of ability self-ef 1047297cacy outcomes expectations and performance goals
(adapted from Lent et al 1994)
660 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 35
Expectations Scale (MSOES Fouad Smith amp Enochs 1997) The scale
consists of nine items assessing middle school students beliefs about
the potential consequences of mathematics-related courses activities
and achievements Participants rated each item (eg ldquoIf I learn math I
will have more options when choosing my majorrdquo) on a 5-point scale
ranging from 1 (agreetotally)to 5 (disagreetotally) Item scoreswere
summed and divided by 9 MOES have adequate reliability and
construct validity (Cupani in press) The present study yielded a
Cronbachs alpha of 83 for MOES scores
222 Mathematics performance goals
The Mathematics Performance Goals Scale (MPGS Cupani in
press) isthemodi1047297ed version of the subscale for MathematicsScience
Intentions and Goals Scale (MSIGS Fouad et al 1997) It has 10 items
assessing middle school students intentions to pursue and persist in
mathematics-related courses in high school Participants rated each
item (eg ldquoThis year I propose to get good gradesin mathematicsrdquo) on
a 5-point scale ranging from 1 (agree totally) to 5 (disagree totally)
Scores were summed and divided by 10 MPGS have adequate
reliability and construct validity (Cupani in press) The present study
yielded a Cronbachs alpha of 87 for MPGS scores
223 Logicalndashmathematical self-ef 1047297cacy
The LogicalndashMathematical Self-ef 1047297cacy Scale (LMSS) has six items
and participants rated each item (eg ldquoSolve mathematics equationrdquo)
on a 10-point scale ranging from 1 (Cannot do at all) to 10 (Certain
can do) The scores were summed and divided by 6 The present study
yielded a Cronbachs alpha of 83 for LMSS scores Originally this scale
was included in the revised version of the Multiple Intelligences Self-
Ef 1047297cacy Inventory (MISEI-R) which has adequate reliability and
construct validity (Peacuterez amp Cupani 2008)
224 Mathematics abilities
The Numerical Reasoning subscale of the Differential Aptitude
Test Version 5 was used (Bennett Seashore amp Wesman 2000) The
Numerical Reasoning subscale measures the ability to use numbers ina logical and ef 1047297cient way In the present study a Kuder Richardson
(KR-20) coef 1047297cient of 81 was found for Numerical Reasoning scores
225 Academic Performance in Mathematic
Academic Performance in Mathematic (APM) was assessed by
accessing the students high school records for mathematics courses
In Argentina students are assessed at mid-term (June) and at the end
of the academic year (December) Grades are given on a 10-point
scale with 7 the cut-off for passing a course The two assessments
(which were highly correlated r =78 p b 001) were summed and
divided by 2 No signi1047297cant differences in APM were found between
grades (8th vs 9th t 275 647 pN 05) Therefore the groups were
pooled for subsequent analyses
23 Procedure
All measurements including consent forms were gathered within
a single class period during the 1047297rst class term Tests were taken
collectively during the course of a regular school day at four
educational institutions and in three different sessions Detailedinstructions on how to complete the survey were provided to the
students by the researcher The measures were taken following the
theoretical and causal links proposed by the SCCT The Numerical
Reasoning subtest was administered during the 1047297rst session (April)
one college per week followed 1 month later by the MOES and LMSS
(second session) The MPGS was applied about 3 weeks later (third
session) Mathematics grade scores for each student were collected
directly from school records at the end of the second school term
3 Results
31 Preliminary analyses
Univariate atypical cases (ie zN329 two-tailed test p b001)
were identi1047297ed by calculating standard scores for each variable
Atypical multivariate cases were identi1047297ed through the Mahalanobis
test (Tabachnick amp Fidell 2001 p b 001) As a result of these tests
four cases were removed from the dataset Multivariate normality
was evaluated by Mardia ratio (3202 p N 05) Across variables the
values for asymmetry and kurtosis were optimal for the proposed
parametric analysis (minus85 tominus08andminus48to 92 respectively George
amp Mallery 2001)
Table 1 presents zero-order correlation coef 1047297cients for the
measures All variables were signi1047297cantly correlated with math
performance mathematics performance goals (r =40) mathematics
abilities (r =47) and logicalndashmathematical self-ef 1047297cacy (r =54)
32 Path analysis
Model 1047297t should be assessed using several indices to ensure more
reliable and accurate decisions (Hu amp Bentler 1995) Therefore the
following indices were employed the χ 2 test of signi1047297cance the ratio
of the χ 2 statistic to degrees of freedom (χ 2 df ) the comparative 1047297t
index (CFI) the goodness-of-1047297t index (GFI) and the rootndashmeanndash
square error of approximation (RMSEA) When this ratio is less than
30 a good model 1047297t can be inferred (Kline 2005) CFI and GFI values
between ge90 and ge95 and RMSEA values between le05 and le08
indicate of good model 1047297t (Hu amp Bentler 1995)
Table 1
Descriptive data and interrelation between variables pertinent to the model
Descriptive Interrelation
Variables M SD AS KS MA LMS MOE MPG MP
Mathematics Ability (MA) 2008 647 minus08 minus48 100 40 02 05 47
Logic-Math Self-ef 1047297cacy (LMS) 694 167 minus85 55 100 25 38 54
Math Outcome Expectations (MOE) 360 73 minus49 24 100 39 24
Math Performance Goals (MPG) 343 74 minus68 92 100 40
Math Performance (MP) 603 183 minus22 minus35 100
pb 05 pb 01
Note The Mathematics abilities (MA) is from the Numerical Reasoning subscale of the Differential Aptitude Test Version 5 ( Bennett et al 2000) The LogicalndashMathematical Self-
ef 1047297cacy Scale (LMSS) is from the revised version of the Multiple Intelligences Self-Ef 1047297cacy Inventory (MISEI-R Peacuterez amp Cupani 2008) the Mathematics Outcome Expectations is
from the Mathematics Outcome Expectations Scale (MOES Cupani in press) modi1047297ed version of the subscale for MathematicsScience Intentions and Goals Scale (MSIGS Fouad
et al 1997) the Mathematics Performance Goals is from the Mathematics Performance Goals Scale (MPGS Cupani in press) modi1047297ed version of the subscale for Mathematics
Science Intentions and Goals Scale (MSIGS Fouad et al 1997) Academic Performance in Mathematic (APM) was assessed by accessing the students high school records for
mathematics courses Gradesare given on a 10-point scalewith7 thecut-offfor passing a course Allvalues representrawnonstandardized scores MmeanSD standard deviation
Ss skewness Ks kurtosis Interrelation zero-order correlations
661M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 45
All indices revealed optimal model adjustment (CFI= 99
CFI=99 RMSEA=06 χ 2=4308 p =116 CMINDF=2154) The
residuals were also small (median= 000 range=minus37 to07)
Therefore the 1047297tness of the model appears strong enough to allow
the report and interpretation of the standardized path estimates
(Browne MacCallum Kim Anderson amp Glaser 2002) Fig 2 depicts
the path coef 1047297cients for the proposed relationships among the
variables in the theoretical model
The SCCT postulates indirect relationships among key variables To
assess these speci1047297c hypotheses we used Sobels test to examine
indirect effects in the recursive model under scrutiny (Kline 2005)
Table 2 presents of total direct and indirect effects of variables The
test strongly supported the theoretical proposal yielding a signi1047297cant
and positive relationship between mathematics performance and
mathematics abilities (H1 β =34 pb 01) logicalndashmathematical self-
ef 1047297cacy (H4 β =30 pb 01) and mathematics performance goals
(H7 β =27 p =01)
With regard to indirect effects an effect of academic abilities onmathematics performance was observed that was mediated by logicalndash
mathematical self-ef 1047297cacy beliefs (H234times 30= 10 z=524 pb 000)
The total effect of academic abilities was 44 (34+[34times30]) H3
however was not corroborated by our data The relationship between
abilities and expectations was negative and far from reaching
signi1047297cance (β=minus10 p=13)The analysis also allowed an estimation
of the predictive contribution of logicalndashmathematical self-ef 1047297cacy
beliefs (H530times 27=08 z =362 pb 000) and mathematics outcome
expectations (H6 31times27=09 z=332 pb 000) on mathematics
performance goals A positive and signi1047297cant ( β =29 pb 01) associ-
ation was also found between logicalndashmathematical self-ef 1047297cacy beliefs
and mathematics outcome expectations The total effect of self-ef 1047297cacy
on mathematics performance goals was 39 (30+[29times31] z =344
pb 000) Therefore the total contribution of self-ef 1047297cacy beliefs to
mathematics performance is 40 whereas the indirect contribution of
outcome expectation to mathematics performance mediated by
performance goals is 09
In summary the model generally explained 44 of the variance of academic achievement in mathematics Mathematics abilities
explained 16 of the variance of logicalndashmathematical self-ef 1047297cacy
beliefs With regard to H5 and H6 the results indicated that self-
ef 1047297cacy beliefs and outcome expectations explained 23 of the
variance of performance goals Self-ef 1047297cacy beliefs about outcome
expectations also provided a signi1047297cant contribution
4 Discussion
The present study conducted in a sample of Argentinean high-
school students strongly supported the theoretical model of academic
performance in mathematics of the SCCT Thecurrent1047297ndings suggest
that success in academic performance among Argentinean students is
associated with greater mathematics ability strong beliefs about this
ability and more optimistic and demanding performance targets
These successful students also have higher self-ef 1047297cacy beliefs
Moreover students who set more demanding performance targets
are those with higher self-ef 1047297cacy beliefs and higher expectations of
positive results The study replicates and extends early work
conducted in US students (eg Brown et al 2008)
An obvious yet important difference between the present and
previous studies is that students in this study belong to a Latin-
American population The cross-cultural validity of the SCCT has
recently become an increasingly popular focus of career inquiry (Lent
amp Sheu 2010) Most of this research however has been conducted
with Americans of foreign descent (eg MexicanndashAmericans Navarro
et al 2007) Lent et al (2001) argued for the need to examine the
validity of the SCCT in culturally diverse groups Research conducted
in Western contexts has identi1047297ed intrapersonal and contextualfactors relating to academic performance Country characteristics
such as average income socialinequality andcultural valuesmight be
associated with student achievement directly or indirectly via family
or motivation (Chiu amp Xihua 2008) Our study represents important
progress in this direction
One limitation of generalizing these 1047297ndings relates to the
representativeness of the sample Only students attending private
schools were included thus the results should not be generalized to
students from low socioeconomic status or attending state-based
Fig 2 Standardized path coef 1047297cients from the Social Cognitive Model of Academic Performance in Mathematics (Lent et al 1994) found in a sample of Argentinean middle school
students Standardized path coef 1047297cients and signi1047297cance level are depicted over each path ( pb
001)
Table 2
Decomposition of total direct and indirect effects of variables from the path analysis
Effect Direct effect Indirect effect Total effect
Logic-Mathematics Self-ef 1047297cacy
Mathematics Ability 40 00 40
Outcome expectations
Mathematics Ability minus10 11 02
Logic-Mathematics Self-ef 1047297cacy 29 00 29
Performance goals
Mathematics Ability 00 13 13
Logic-Mathematics Self-ef 1047297cacy 30 08 38
Outcome Expectations 31 00 31
Mathematics performance
Mathematics Ability 34 10 44
Logic-Mathematics Self-ef 1047297cacy 30 10 40
Outcome Expectations 00 09 09
Performance Goals 27 00 27
pb 01 pb 001
662 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 55
institutions Future research should use a more heterogeneous sample
and explicitly assess the socioeconomic status of the students
Another limitation is that the measurement for academic achieve-
ment in mathematics canbe in1047298uenced by the idiosyncratic policies of
each institution or the educational orientation of each instructor Also
we acknowledge that our instrument measures math self-ef 1047297cacy
beliefs at a general rather than at a speci1047297c level The evidence shows
that the predictability of self-ef 1047297cacy measures depends on their
speci1047297
city and correspondence to actual math performance tasks(Bandura 1997) That is predictors and dependent variables must be
compatible in regards with content context temporal orientation and
speci1047297city level (Ajzen 1988) Future studies should aim at creating
new math self-ef 1047297cacy scales that measure this construct at a speci1047297c
level
Themain theoretical contributionof this study is the assessment of
theSCCT performancemodel in a novel cultural and linguistic context
namely middle school students in Argentina Interestingly the study
assessed all SCCT predictors jointly To our knowledge the literature
has yet to show a single large-scale test of the complete performance
model although numerous studies have examined subsets of the
model (eg Brown et al 2008) Thedevelopmental stage in which the
model is tested also deserves attention Early adolescence is a critical
stage for learning (Zimmerman Bonner amp Kovach 1996) character-
ized by a sharp decline in academic performance possibly caused by
the increasing challenges posed by middle school as well as the
inherent psychological and biological changes that occur during this
period
Beyond these theoretical implications the results suggest that the
SCCT could be used as a screening tool to identify students at-risk for
having for example diminished self-ef 1047297cacy in a given academic
domain Educational institutions could use this knowledge to design
experiences speci1047297cally aimed at improving these variables Notably
adolescents usually have limited knowledge about their capabilities
and career options a fact that results in stereotyped and unstable
vocational goals (Lent et al 2004) Therefore the development of
career goals can be halted early in life if the students are exposed to
educational environments that provide limited opportunities for
nurturing appropriate ef 1047297cacy or self-ef 1047297cacy skills and outcomeexpectations The results outlined in the present study could be used
to design interventions aimed at increasing the level of exposure to a
variety of career-relevant tasks and activities These interventions will
help develop task-speci1047297c concepts of self-ef 1047297cacy that in turn will
result in more realistic stable and useful vocational goals
References
Ajzen I (1988) Attitudes personality and behavior Stony Stratford UK OpenUniversity Press
Bandura A (1986) Social foundations of thought and action A social cognitive theoryEnglewood Cliffs NJ Prentice Hall
Bandura A (1997) Self-ef 1047297cacy The exercise of control New York FreemanBetz N Eamp Hackett G (2006) Careerself-ef 1047297cacy theory Back tothe future Journal of
Career Assessment 14(1) 3minus11
Bennett GK Seashore HG amp Wesman AG (2000) Differential Aptitude Test(DAT-5)Madrid TEA Ediciones
Brown S D Tramayne S Hoxha D Telander K Fan X amp Lent R W (2008) Socialcognitive predictors of college students academic performance and persistence Ameta-analytic path analysis Journal of Vocational Behavior 72 298minus308
Browne M WMacCallum R CKim C TAnderson B Lamp Glaser R (2002) When 1047297tindices and residuals are incompatible Psychological Methods 7 403minus421
Chiu M M amp Xihua Z (2008) Family and motivation effects on mathematicsachievement Analyses of students in 41 countries Learning and Instruction 18(4)321minus336
Cupani M (in press) Validity evidence for the new scales for mathematics outcomeexpectancies and performance goals Interdiciplinaria 27 (1)
Ferry T R Fouad N A amp Smith P L (2000) The role of family context in a socialcognitive model for career-related choice behavior A math and scienceperspective Journal of Vocational Behavior 57 348minus364
Fouad N A amp Smith P L (1996) A test of a social cognitive model for middle schoolstudents Math and science Journal of Counseling Psychology 43 338minus346
Fouad N A Smith P L amp Enochs L (1997) Reliability and validity evidence for theMiddle School Self-Ef 1047297cacy Scale Measurement and Evaluation in Counseling andDevelopment 30 17minus31
George D amp MalleryM (2001) Using SPSS for Windows step by step a simple guide andreference Boston MA Allyn amp Bacon
Hu L amp Bentler P (1995) Evaluating model 1047297t In R Hoyle (Ed) Structural equation
modelling Concepts issues and applications (pp 76minus99) Thousand Oaks CA SagePublicationsKline R B (2005) Principles and practice of structural equation modeling 2nd ed New
York GuilfordLent R WBrown S Damp Hackett G (1994) Toward a unifying socialcognitive theory
of career and academic interest choice and performance Journal of VocationalBehavior 45 79minus122
Lent R WBrown S DBrenner BChopra S BDavis TTalleyrandR amp SuthakaranV (2001) The role of contextual supports and barriers in the choice of mathscience educational options A test of social cognitive hypotheses Journal of Counseling Psychology 48 474minus483
Lent R W Brown S D amp Hackett G (2002) Social cognitive career theory In DBrown (Ed) Career choice and development (pp 255minus311) 4th ed San Francisco
Jossey-BassLent R W Brown S D Nota L amp Soresi S (2003) Testing social cognitive interest
and choice hypotheses across Holland types in Italian high school students Journalof Vocational Behavior 62 101minus118
Lent R W Hackett G amp y Brown S D (2004) Una perspectiva Social Cognitiva de latransicioacuten entre la escuela y el trabajo (A Social Cognitive Perspective of the
transition between school and work) Evaluar 4 1minus22Lent R W amp Brown S D (2006) On conceptualizing and assessing social cognitive
constructs in career research A measurement guide Journal of Career Assessment 14 12minus35
Lent R W amp Sheu H (2010) Applying social cognitive career theory across culturesEmpirical status In J G Ponterotto J M Casas L A Suzuki amp C M Alexander(Eds) Handbook of multicultural counseling (pp 691minus701) Thousand Oaks CASage
Lopez F G Lent R W Brown S D amp Gore P A (1997) Role of social ndashcognitiveexpectations in high school students mathematics-related interest and perfor-mance Journal of Counseling Psychology 44 44minus52
Multon K D Brown S D amp Lent R W (1991) Relation of self-ef 1047297cacy beliefs toacademicoutcomesA meta-analyticinvestigation Journal of Counseling Psychology
38 30minus38Navarro R L Flores L Y amp Worthington R L (2007) Mexican American middle
school students goal intentions in mathematics and science A test of socialcognitive career theory Journal of Counseling Psychology 54 320minus335
OBrien V Martinez-Pons M amp Kopala M (1999) Mathematics self-ef 1047297cacy ethnicidentity gender and career interests related to mathematics and science Journal of Educational Research 92 231minus235
Organization for Economic Cooperation and Development (2001) Knowledge and skills for life First results from the OECD Programme for International Student Assessment (PISA) 2000 Paris OECD Publications
Pajares F (1996) Self-ef 1047297cacy beliefs in academic settings Review of EducationalResearch 66 543minus578
Pajares F amp Graham L (1999) Self-Ef 1047297cacy motivation constructs and mathematicsperformance of entering middle school students Contemporary EducationalPsychology 139 124minus139
Pajares F amp Schunk D H (2001) Self-beliefs and school success Self-ef 1047297cacy self-concept and school achievement In R J Riding amp S Rayner (Eds) Self Perception(pp 239minus266) Westport CT Ablex Publishing
Peacuterez E amp Cupani M (2008) Multiple intelligences self-ef 1047297cacy inventory revised(MISEI-R) Preliminary validation Revista Latinoamericana de Psicologiacutea 40 47minus58
Robbins S B Lauver K Le H Davis D Langley R amp Carlstrom A (2004) Dopsychosocial and study skill factors predict college outcomes A meta-analysisPsychological Bulletin 130 261minus288
SellsL W(1980) Themathematical 1047297lter andthe educationof women andminorities
In L H Fox L Brodey amp D Tobin (Eds) Women and the mathematical mystique(pp 66minus75) Baltimore Johns Hopkins University
Tabachnick B Gamp Fidell L S (2001) Using multivariate statistics 4thEd Boston Allynand Bacon
Turner S L amp Lapan R T (2005) Evaluation of an intervention to increase non-traditional career interests and career-related self-ef 1047297cacy among middle-schooladolescents Journal of Vocational Behavior 66 516minus531
Zimmerman B J Bonner S amp Kovach R (1996) Developing self-regulated learnersBeyond achievement to self-ef 1047297cacy Washington DC American PsychologicalAssociation
663M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 35
Expectations Scale (MSOES Fouad Smith amp Enochs 1997) The scale
consists of nine items assessing middle school students beliefs about
the potential consequences of mathematics-related courses activities
and achievements Participants rated each item (eg ldquoIf I learn math I
will have more options when choosing my majorrdquo) on a 5-point scale
ranging from 1 (agreetotally)to 5 (disagreetotally) Item scoreswere
summed and divided by 9 MOES have adequate reliability and
construct validity (Cupani in press) The present study yielded a
Cronbachs alpha of 83 for MOES scores
222 Mathematics performance goals
The Mathematics Performance Goals Scale (MPGS Cupani in
press) isthemodi1047297ed version of the subscale for MathematicsScience
Intentions and Goals Scale (MSIGS Fouad et al 1997) It has 10 items
assessing middle school students intentions to pursue and persist in
mathematics-related courses in high school Participants rated each
item (eg ldquoThis year I propose to get good gradesin mathematicsrdquo) on
a 5-point scale ranging from 1 (agree totally) to 5 (disagree totally)
Scores were summed and divided by 10 MPGS have adequate
reliability and construct validity (Cupani in press) The present study
yielded a Cronbachs alpha of 87 for MPGS scores
223 Logicalndashmathematical self-ef 1047297cacy
The LogicalndashMathematical Self-ef 1047297cacy Scale (LMSS) has six items
and participants rated each item (eg ldquoSolve mathematics equationrdquo)
on a 10-point scale ranging from 1 (Cannot do at all) to 10 (Certain
can do) The scores were summed and divided by 6 The present study
yielded a Cronbachs alpha of 83 for LMSS scores Originally this scale
was included in the revised version of the Multiple Intelligences Self-
Ef 1047297cacy Inventory (MISEI-R) which has adequate reliability and
construct validity (Peacuterez amp Cupani 2008)
224 Mathematics abilities
The Numerical Reasoning subscale of the Differential Aptitude
Test Version 5 was used (Bennett Seashore amp Wesman 2000) The
Numerical Reasoning subscale measures the ability to use numbers ina logical and ef 1047297cient way In the present study a Kuder Richardson
(KR-20) coef 1047297cient of 81 was found for Numerical Reasoning scores
225 Academic Performance in Mathematic
Academic Performance in Mathematic (APM) was assessed by
accessing the students high school records for mathematics courses
In Argentina students are assessed at mid-term (June) and at the end
of the academic year (December) Grades are given on a 10-point
scale with 7 the cut-off for passing a course The two assessments
(which were highly correlated r =78 p b 001) were summed and
divided by 2 No signi1047297cant differences in APM were found between
grades (8th vs 9th t 275 647 pN 05) Therefore the groups were
pooled for subsequent analyses
23 Procedure
All measurements including consent forms were gathered within
a single class period during the 1047297rst class term Tests were taken
collectively during the course of a regular school day at four
educational institutions and in three different sessions Detailedinstructions on how to complete the survey were provided to the
students by the researcher The measures were taken following the
theoretical and causal links proposed by the SCCT The Numerical
Reasoning subtest was administered during the 1047297rst session (April)
one college per week followed 1 month later by the MOES and LMSS
(second session) The MPGS was applied about 3 weeks later (third
session) Mathematics grade scores for each student were collected
directly from school records at the end of the second school term
3 Results
31 Preliminary analyses
Univariate atypical cases (ie zN329 two-tailed test p b001)
were identi1047297ed by calculating standard scores for each variable
Atypical multivariate cases were identi1047297ed through the Mahalanobis
test (Tabachnick amp Fidell 2001 p b 001) As a result of these tests
four cases were removed from the dataset Multivariate normality
was evaluated by Mardia ratio (3202 p N 05) Across variables the
values for asymmetry and kurtosis were optimal for the proposed
parametric analysis (minus85 tominus08andminus48to 92 respectively George
amp Mallery 2001)
Table 1 presents zero-order correlation coef 1047297cients for the
measures All variables were signi1047297cantly correlated with math
performance mathematics performance goals (r =40) mathematics
abilities (r =47) and logicalndashmathematical self-ef 1047297cacy (r =54)
32 Path analysis
Model 1047297t should be assessed using several indices to ensure more
reliable and accurate decisions (Hu amp Bentler 1995) Therefore the
following indices were employed the χ 2 test of signi1047297cance the ratio
of the χ 2 statistic to degrees of freedom (χ 2 df ) the comparative 1047297t
index (CFI) the goodness-of-1047297t index (GFI) and the rootndashmeanndash
square error of approximation (RMSEA) When this ratio is less than
30 a good model 1047297t can be inferred (Kline 2005) CFI and GFI values
between ge90 and ge95 and RMSEA values between le05 and le08
indicate of good model 1047297t (Hu amp Bentler 1995)
Table 1
Descriptive data and interrelation between variables pertinent to the model
Descriptive Interrelation
Variables M SD AS KS MA LMS MOE MPG MP
Mathematics Ability (MA) 2008 647 minus08 minus48 100 40 02 05 47
Logic-Math Self-ef 1047297cacy (LMS) 694 167 minus85 55 100 25 38 54
Math Outcome Expectations (MOE) 360 73 minus49 24 100 39 24
Math Performance Goals (MPG) 343 74 minus68 92 100 40
Math Performance (MP) 603 183 minus22 minus35 100
pb 05 pb 01
Note The Mathematics abilities (MA) is from the Numerical Reasoning subscale of the Differential Aptitude Test Version 5 ( Bennett et al 2000) The LogicalndashMathematical Self-
ef 1047297cacy Scale (LMSS) is from the revised version of the Multiple Intelligences Self-Ef 1047297cacy Inventory (MISEI-R Peacuterez amp Cupani 2008) the Mathematics Outcome Expectations is
from the Mathematics Outcome Expectations Scale (MOES Cupani in press) modi1047297ed version of the subscale for MathematicsScience Intentions and Goals Scale (MSIGS Fouad
et al 1997) the Mathematics Performance Goals is from the Mathematics Performance Goals Scale (MPGS Cupani in press) modi1047297ed version of the subscale for Mathematics
Science Intentions and Goals Scale (MSIGS Fouad et al 1997) Academic Performance in Mathematic (APM) was assessed by accessing the students high school records for
mathematics courses Gradesare given on a 10-point scalewith7 thecut-offfor passing a course Allvalues representrawnonstandardized scores MmeanSD standard deviation
Ss skewness Ks kurtosis Interrelation zero-order correlations
661M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 45
All indices revealed optimal model adjustment (CFI= 99
CFI=99 RMSEA=06 χ 2=4308 p =116 CMINDF=2154) The
residuals were also small (median= 000 range=minus37 to07)
Therefore the 1047297tness of the model appears strong enough to allow
the report and interpretation of the standardized path estimates
(Browne MacCallum Kim Anderson amp Glaser 2002) Fig 2 depicts
the path coef 1047297cients for the proposed relationships among the
variables in the theoretical model
The SCCT postulates indirect relationships among key variables To
assess these speci1047297c hypotheses we used Sobels test to examine
indirect effects in the recursive model under scrutiny (Kline 2005)
Table 2 presents of total direct and indirect effects of variables The
test strongly supported the theoretical proposal yielding a signi1047297cant
and positive relationship between mathematics performance and
mathematics abilities (H1 β =34 pb 01) logicalndashmathematical self-
ef 1047297cacy (H4 β =30 pb 01) and mathematics performance goals
(H7 β =27 p =01)
With regard to indirect effects an effect of academic abilities onmathematics performance was observed that was mediated by logicalndash
mathematical self-ef 1047297cacy beliefs (H234times 30= 10 z=524 pb 000)
The total effect of academic abilities was 44 (34+[34times30]) H3
however was not corroborated by our data The relationship between
abilities and expectations was negative and far from reaching
signi1047297cance (β=minus10 p=13)The analysis also allowed an estimation
of the predictive contribution of logicalndashmathematical self-ef 1047297cacy
beliefs (H530times 27=08 z =362 pb 000) and mathematics outcome
expectations (H6 31times27=09 z=332 pb 000) on mathematics
performance goals A positive and signi1047297cant ( β =29 pb 01) associ-
ation was also found between logicalndashmathematical self-ef 1047297cacy beliefs
and mathematics outcome expectations The total effect of self-ef 1047297cacy
on mathematics performance goals was 39 (30+[29times31] z =344
pb 000) Therefore the total contribution of self-ef 1047297cacy beliefs to
mathematics performance is 40 whereas the indirect contribution of
outcome expectation to mathematics performance mediated by
performance goals is 09
In summary the model generally explained 44 of the variance of academic achievement in mathematics Mathematics abilities
explained 16 of the variance of logicalndashmathematical self-ef 1047297cacy
beliefs With regard to H5 and H6 the results indicated that self-
ef 1047297cacy beliefs and outcome expectations explained 23 of the
variance of performance goals Self-ef 1047297cacy beliefs about outcome
expectations also provided a signi1047297cant contribution
4 Discussion
The present study conducted in a sample of Argentinean high-
school students strongly supported the theoretical model of academic
performance in mathematics of the SCCT Thecurrent1047297ndings suggest
that success in academic performance among Argentinean students is
associated with greater mathematics ability strong beliefs about this
ability and more optimistic and demanding performance targets
These successful students also have higher self-ef 1047297cacy beliefs
Moreover students who set more demanding performance targets
are those with higher self-ef 1047297cacy beliefs and higher expectations of
positive results The study replicates and extends early work
conducted in US students (eg Brown et al 2008)
An obvious yet important difference between the present and
previous studies is that students in this study belong to a Latin-
American population The cross-cultural validity of the SCCT has
recently become an increasingly popular focus of career inquiry (Lent
amp Sheu 2010) Most of this research however has been conducted
with Americans of foreign descent (eg MexicanndashAmericans Navarro
et al 2007) Lent et al (2001) argued for the need to examine the
validity of the SCCT in culturally diverse groups Research conducted
in Western contexts has identi1047297ed intrapersonal and contextualfactors relating to academic performance Country characteristics
such as average income socialinequality andcultural valuesmight be
associated with student achievement directly or indirectly via family
or motivation (Chiu amp Xihua 2008) Our study represents important
progress in this direction
One limitation of generalizing these 1047297ndings relates to the
representativeness of the sample Only students attending private
schools were included thus the results should not be generalized to
students from low socioeconomic status or attending state-based
Fig 2 Standardized path coef 1047297cients from the Social Cognitive Model of Academic Performance in Mathematics (Lent et al 1994) found in a sample of Argentinean middle school
students Standardized path coef 1047297cients and signi1047297cance level are depicted over each path ( pb
001)
Table 2
Decomposition of total direct and indirect effects of variables from the path analysis
Effect Direct effect Indirect effect Total effect
Logic-Mathematics Self-ef 1047297cacy
Mathematics Ability 40 00 40
Outcome expectations
Mathematics Ability minus10 11 02
Logic-Mathematics Self-ef 1047297cacy 29 00 29
Performance goals
Mathematics Ability 00 13 13
Logic-Mathematics Self-ef 1047297cacy 30 08 38
Outcome Expectations 31 00 31
Mathematics performance
Mathematics Ability 34 10 44
Logic-Mathematics Self-ef 1047297cacy 30 10 40
Outcome Expectations 00 09 09
Performance Goals 27 00 27
pb 01 pb 001
662 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 55
institutions Future research should use a more heterogeneous sample
and explicitly assess the socioeconomic status of the students
Another limitation is that the measurement for academic achieve-
ment in mathematics canbe in1047298uenced by the idiosyncratic policies of
each institution or the educational orientation of each instructor Also
we acknowledge that our instrument measures math self-ef 1047297cacy
beliefs at a general rather than at a speci1047297c level The evidence shows
that the predictability of self-ef 1047297cacy measures depends on their
speci1047297
city and correspondence to actual math performance tasks(Bandura 1997) That is predictors and dependent variables must be
compatible in regards with content context temporal orientation and
speci1047297city level (Ajzen 1988) Future studies should aim at creating
new math self-ef 1047297cacy scales that measure this construct at a speci1047297c
level
Themain theoretical contributionof this study is the assessment of
theSCCT performancemodel in a novel cultural and linguistic context
namely middle school students in Argentina Interestingly the study
assessed all SCCT predictors jointly To our knowledge the literature
has yet to show a single large-scale test of the complete performance
model although numerous studies have examined subsets of the
model (eg Brown et al 2008) Thedevelopmental stage in which the
model is tested also deserves attention Early adolescence is a critical
stage for learning (Zimmerman Bonner amp Kovach 1996) character-
ized by a sharp decline in academic performance possibly caused by
the increasing challenges posed by middle school as well as the
inherent psychological and biological changes that occur during this
period
Beyond these theoretical implications the results suggest that the
SCCT could be used as a screening tool to identify students at-risk for
having for example diminished self-ef 1047297cacy in a given academic
domain Educational institutions could use this knowledge to design
experiences speci1047297cally aimed at improving these variables Notably
adolescents usually have limited knowledge about their capabilities
and career options a fact that results in stereotyped and unstable
vocational goals (Lent et al 2004) Therefore the development of
career goals can be halted early in life if the students are exposed to
educational environments that provide limited opportunities for
nurturing appropriate ef 1047297cacy or self-ef 1047297cacy skills and outcomeexpectations The results outlined in the present study could be used
to design interventions aimed at increasing the level of exposure to a
variety of career-relevant tasks and activities These interventions will
help develop task-speci1047297c concepts of self-ef 1047297cacy that in turn will
result in more realistic stable and useful vocational goals
References
Ajzen I (1988) Attitudes personality and behavior Stony Stratford UK OpenUniversity Press
Bandura A (1986) Social foundations of thought and action A social cognitive theoryEnglewood Cliffs NJ Prentice Hall
Bandura A (1997) Self-ef 1047297cacy The exercise of control New York FreemanBetz N Eamp Hackett G (2006) Careerself-ef 1047297cacy theory Back tothe future Journal of
Career Assessment 14(1) 3minus11
Bennett GK Seashore HG amp Wesman AG (2000) Differential Aptitude Test(DAT-5)Madrid TEA Ediciones
Brown S D Tramayne S Hoxha D Telander K Fan X amp Lent R W (2008) Socialcognitive predictors of college students academic performance and persistence Ameta-analytic path analysis Journal of Vocational Behavior 72 298minus308
Browne M WMacCallum R CKim C TAnderson B Lamp Glaser R (2002) When 1047297tindices and residuals are incompatible Psychological Methods 7 403minus421
Chiu M M amp Xihua Z (2008) Family and motivation effects on mathematicsachievement Analyses of students in 41 countries Learning and Instruction 18(4)321minus336
Cupani M (in press) Validity evidence for the new scales for mathematics outcomeexpectancies and performance goals Interdiciplinaria 27 (1)
Ferry T R Fouad N A amp Smith P L (2000) The role of family context in a socialcognitive model for career-related choice behavior A math and scienceperspective Journal of Vocational Behavior 57 348minus364
Fouad N A amp Smith P L (1996) A test of a social cognitive model for middle schoolstudents Math and science Journal of Counseling Psychology 43 338minus346
Fouad N A Smith P L amp Enochs L (1997) Reliability and validity evidence for theMiddle School Self-Ef 1047297cacy Scale Measurement and Evaluation in Counseling andDevelopment 30 17minus31
George D amp MalleryM (2001) Using SPSS for Windows step by step a simple guide andreference Boston MA Allyn amp Bacon
Hu L amp Bentler P (1995) Evaluating model 1047297t In R Hoyle (Ed) Structural equation
modelling Concepts issues and applications (pp 76minus99) Thousand Oaks CA SagePublicationsKline R B (2005) Principles and practice of structural equation modeling 2nd ed New
York GuilfordLent R WBrown S Damp Hackett G (1994) Toward a unifying socialcognitive theory
of career and academic interest choice and performance Journal of VocationalBehavior 45 79minus122
Lent R WBrown S DBrenner BChopra S BDavis TTalleyrandR amp SuthakaranV (2001) The role of contextual supports and barriers in the choice of mathscience educational options A test of social cognitive hypotheses Journal of Counseling Psychology 48 474minus483
Lent R W Brown S D amp Hackett G (2002) Social cognitive career theory In DBrown (Ed) Career choice and development (pp 255minus311) 4th ed San Francisco
Jossey-BassLent R W Brown S D Nota L amp Soresi S (2003) Testing social cognitive interest
and choice hypotheses across Holland types in Italian high school students Journalof Vocational Behavior 62 101minus118
Lent R W Hackett G amp y Brown S D (2004) Una perspectiva Social Cognitiva de latransicioacuten entre la escuela y el trabajo (A Social Cognitive Perspective of the
transition between school and work) Evaluar 4 1minus22Lent R W amp Brown S D (2006) On conceptualizing and assessing social cognitive
constructs in career research A measurement guide Journal of Career Assessment 14 12minus35
Lent R W amp Sheu H (2010) Applying social cognitive career theory across culturesEmpirical status In J G Ponterotto J M Casas L A Suzuki amp C M Alexander(Eds) Handbook of multicultural counseling (pp 691minus701) Thousand Oaks CASage
Lopez F G Lent R W Brown S D amp Gore P A (1997) Role of social ndashcognitiveexpectations in high school students mathematics-related interest and perfor-mance Journal of Counseling Psychology 44 44minus52
Multon K D Brown S D amp Lent R W (1991) Relation of self-ef 1047297cacy beliefs toacademicoutcomesA meta-analyticinvestigation Journal of Counseling Psychology
38 30minus38Navarro R L Flores L Y amp Worthington R L (2007) Mexican American middle
school students goal intentions in mathematics and science A test of socialcognitive career theory Journal of Counseling Psychology 54 320minus335
OBrien V Martinez-Pons M amp Kopala M (1999) Mathematics self-ef 1047297cacy ethnicidentity gender and career interests related to mathematics and science Journal of Educational Research 92 231minus235
Organization for Economic Cooperation and Development (2001) Knowledge and skills for life First results from the OECD Programme for International Student Assessment (PISA) 2000 Paris OECD Publications
Pajares F (1996) Self-ef 1047297cacy beliefs in academic settings Review of EducationalResearch 66 543minus578
Pajares F amp Graham L (1999) Self-Ef 1047297cacy motivation constructs and mathematicsperformance of entering middle school students Contemporary EducationalPsychology 139 124minus139
Pajares F amp Schunk D H (2001) Self-beliefs and school success Self-ef 1047297cacy self-concept and school achievement In R J Riding amp S Rayner (Eds) Self Perception(pp 239minus266) Westport CT Ablex Publishing
Peacuterez E amp Cupani M (2008) Multiple intelligences self-ef 1047297cacy inventory revised(MISEI-R) Preliminary validation Revista Latinoamericana de Psicologiacutea 40 47minus58
Robbins S B Lauver K Le H Davis D Langley R amp Carlstrom A (2004) Dopsychosocial and study skill factors predict college outcomes A meta-analysisPsychological Bulletin 130 261minus288
SellsL W(1980) Themathematical 1047297lter andthe educationof women andminorities
In L H Fox L Brodey amp D Tobin (Eds) Women and the mathematical mystique(pp 66minus75) Baltimore Johns Hopkins University
Tabachnick B Gamp Fidell L S (2001) Using multivariate statistics 4thEd Boston Allynand Bacon
Turner S L amp Lapan R T (2005) Evaluation of an intervention to increase non-traditional career interests and career-related self-ef 1047297cacy among middle-schooladolescents Journal of Vocational Behavior 66 516minus531
Zimmerman B J Bonner S amp Kovach R (1996) Developing self-regulated learnersBeyond achievement to self-ef 1047297cacy Washington DC American PsychologicalAssociation
663M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 45
All indices revealed optimal model adjustment (CFI= 99
CFI=99 RMSEA=06 χ 2=4308 p =116 CMINDF=2154) The
residuals were also small (median= 000 range=minus37 to07)
Therefore the 1047297tness of the model appears strong enough to allow
the report and interpretation of the standardized path estimates
(Browne MacCallum Kim Anderson amp Glaser 2002) Fig 2 depicts
the path coef 1047297cients for the proposed relationships among the
variables in the theoretical model
The SCCT postulates indirect relationships among key variables To
assess these speci1047297c hypotheses we used Sobels test to examine
indirect effects in the recursive model under scrutiny (Kline 2005)
Table 2 presents of total direct and indirect effects of variables The
test strongly supported the theoretical proposal yielding a signi1047297cant
and positive relationship between mathematics performance and
mathematics abilities (H1 β =34 pb 01) logicalndashmathematical self-
ef 1047297cacy (H4 β =30 pb 01) and mathematics performance goals
(H7 β =27 p =01)
With regard to indirect effects an effect of academic abilities onmathematics performance was observed that was mediated by logicalndash
mathematical self-ef 1047297cacy beliefs (H234times 30= 10 z=524 pb 000)
The total effect of academic abilities was 44 (34+[34times30]) H3
however was not corroborated by our data The relationship between
abilities and expectations was negative and far from reaching
signi1047297cance (β=minus10 p=13)The analysis also allowed an estimation
of the predictive contribution of logicalndashmathematical self-ef 1047297cacy
beliefs (H530times 27=08 z =362 pb 000) and mathematics outcome
expectations (H6 31times27=09 z=332 pb 000) on mathematics
performance goals A positive and signi1047297cant ( β =29 pb 01) associ-
ation was also found between logicalndashmathematical self-ef 1047297cacy beliefs
and mathematics outcome expectations The total effect of self-ef 1047297cacy
on mathematics performance goals was 39 (30+[29times31] z =344
pb 000) Therefore the total contribution of self-ef 1047297cacy beliefs to
mathematics performance is 40 whereas the indirect contribution of
outcome expectation to mathematics performance mediated by
performance goals is 09
In summary the model generally explained 44 of the variance of academic achievement in mathematics Mathematics abilities
explained 16 of the variance of logicalndashmathematical self-ef 1047297cacy
beliefs With regard to H5 and H6 the results indicated that self-
ef 1047297cacy beliefs and outcome expectations explained 23 of the
variance of performance goals Self-ef 1047297cacy beliefs about outcome
expectations also provided a signi1047297cant contribution
4 Discussion
The present study conducted in a sample of Argentinean high-
school students strongly supported the theoretical model of academic
performance in mathematics of the SCCT Thecurrent1047297ndings suggest
that success in academic performance among Argentinean students is
associated with greater mathematics ability strong beliefs about this
ability and more optimistic and demanding performance targets
These successful students also have higher self-ef 1047297cacy beliefs
Moreover students who set more demanding performance targets
are those with higher self-ef 1047297cacy beliefs and higher expectations of
positive results The study replicates and extends early work
conducted in US students (eg Brown et al 2008)
An obvious yet important difference between the present and
previous studies is that students in this study belong to a Latin-
American population The cross-cultural validity of the SCCT has
recently become an increasingly popular focus of career inquiry (Lent
amp Sheu 2010) Most of this research however has been conducted
with Americans of foreign descent (eg MexicanndashAmericans Navarro
et al 2007) Lent et al (2001) argued for the need to examine the
validity of the SCCT in culturally diverse groups Research conducted
in Western contexts has identi1047297ed intrapersonal and contextualfactors relating to academic performance Country characteristics
such as average income socialinequality andcultural valuesmight be
associated with student achievement directly or indirectly via family
or motivation (Chiu amp Xihua 2008) Our study represents important
progress in this direction
One limitation of generalizing these 1047297ndings relates to the
representativeness of the sample Only students attending private
schools were included thus the results should not be generalized to
students from low socioeconomic status or attending state-based
Fig 2 Standardized path coef 1047297cients from the Social Cognitive Model of Academic Performance in Mathematics (Lent et al 1994) found in a sample of Argentinean middle school
students Standardized path coef 1047297cients and signi1047297cance level are depicted over each path ( pb
001)
Table 2
Decomposition of total direct and indirect effects of variables from the path analysis
Effect Direct effect Indirect effect Total effect
Logic-Mathematics Self-ef 1047297cacy
Mathematics Ability 40 00 40
Outcome expectations
Mathematics Ability minus10 11 02
Logic-Mathematics Self-ef 1047297cacy 29 00 29
Performance goals
Mathematics Ability 00 13 13
Logic-Mathematics Self-ef 1047297cacy 30 08 38
Outcome Expectations 31 00 31
Mathematics performance
Mathematics Ability 34 10 44
Logic-Mathematics Self-ef 1047297cacy 30 10 40
Outcome Expectations 00 09 09
Performance Goals 27 00 27
pb 01 pb 001
662 M Cupani et al Learning and Individual Differences 20 (2010) 659ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 55
institutions Future research should use a more heterogeneous sample
and explicitly assess the socioeconomic status of the students
Another limitation is that the measurement for academic achieve-
ment in mathematics canbe in1047298uenced by the idiosyncratic policies of
each institution or the educational orientation of each instructor Also
we acknowledge that our instrument measures math self-ef 1047297cacy
beliefs at a general rather than at a speci1047297c level The evidence shows
that the predictability of self-ef 1047297cacy measures depends on their
speci1047297
city and correspondence to actual math performance tasks(Bandura 1997) That is predictors and dependent variables must be
compatible in regards with content context temporal orientation and
speci1047297city level (Ajzen 1988) Future studies should aim at creating
new math self-ef 1047297cacy scales that measure this construct at a speci1047297c
level
Themain theoretical contributionof this study is the assessment of
theSCCT performancemodel in a novel cultural and linguistic context
namely middle school students in Argentina Interestingly the study
assessed all SCCT predictors jointly To our knowledge the literature
has yet to show a single large-scale test of the complete performance
model although numerous studies have examined subsets of the
model (eg Brown et al 2008) Thedevelopmental stage in which the
model is tested also deserves attention Early adolescence is a critical
stage for learning (Zimmerman Bonner amp Kovach 1996) character-
ized by a sharp decline in academic performance possibly caused by
the increasing challenges posed by middle school as well as the
inherent psychological and biological changes that occur during this
period
Beyond these theoretical implications the results suggest that the
SCCT could be used as a screening tool to identify students at-risk for
having for example diminished self-ef 1047297cacy in a given academic
domain Educational institutions could use this knowledge to design
experiences speci1047297cally aimed at improving these variables Notably
adolescents usually have limited knowledge about their capabilities
and career options a fact that results in stereotyped and unstable
vocational goals (Lent et al 2004) Therefore the development of
career goals can be halted early in life if the students are exposed to
educational environments that provide limited opportunities for
nurturing appropriate ef 1047297cacy or self-ef 1047297cacy skills and outcomeexpectations The results outlined in the present study could be used
to design interventions aimed at increasing the level of exposure to a
variety of career-relevant tasks and activities These interventions will
help develop task-speci1047297c concepts of self-ef 1047297cacy that in turn will
result in more realistic stable and useful vocational goals
References
Ajzen I (1988) Attitudes personality and behavior Stony Stratford UK OpenUniversity Press
Bandura A (1986) Social foundations of thought and action A social cognitive theoryEnglewood Cliffs NJ Prentice Hall
Bandura A (1997) Self-ef 1047297cacy The exercise of control New York FreemanBetz N Eamp Hackett G (2006) Careerself-ef 1047297cacy theory Back tothe future Journal of
Career Assessment 14(1) 3minus11
Bennett GK Seashore HG amp Wesman AG (2000) Differential Aptitude Test(DAT-5)Madrid TEA Ediciones
Brown S D Tramayne S Hoxha D Telander K Fan X amp Lent R W (2008) Socialcognitive predictors of college students academic performance and persistence Ameta-analytic path analysis Journal of Vocational Behavior 72 298minus308
Browne M WMacCallum R CKim C TAnderson B Lamp Glaser R (2002) When 1047297tindices and residuals are incompatible Psychological Methods 7 403minus421
Chiu M M amp Xihua Z (2008) Family and motivation effects on mathematicsachievement Analyses of students in 41 countries Learning and Instruction 18(4)321minus336
Cupani M (in press) Validity evidence for the new scales for mathematics outcomeexpectancies and performance goals Interdiciplinaria 27 (1)
Ferry T R Fouad N A amp Smith P L (2000) The role of family context in a socialcognitive model for career-related choice behavior A math and scienceperspective Journal of Vocational Behavior 57 348minus364
Fouad N A amp Smith P L (1996) A test of a social cognitive model for middle schoolstudents Math and science Journal of Counseling Psychology 43 338minus346
Fouad N A Smith P L amp Enochs L (1997) Reliability and validity evidence for theMiddle School Self-Ef 1047297cacy Scale Measurement and Evaluation in Counseling andDevelopment 30 17minus31
George D amp MalleryM (2001) Using SPSS for Windows step by step a simple guide andreference Boston MA Allyn amp Bacon
Hu L amp Bentler P (1995) Evaluating model 1047297t In R Hoyle (Ed) Structural equation
modelling Concepts issues and applications (pp 76minus99) Thousand Oaks CA SagePublicationsKline R B (2005) Principles and practice of structural equation modeling 2nd ed New
York GuilfordLent R WBrown S Damp Hackett G (1994) Toward a unifying socialcognitive theory
of career and academic interest choice and performance Journal of VocationalBehavior 45 79minus122
Lent R WBrown S DBrenner BChopra S BDavis TTalleyrandR amp SuthakaranV (2001) The role of contextual supports and barriers in the choice of mathscience educational options A test of social cognitive hypotheses Journal of Counseling Psychology 48 474minus483
Lent R W Brown S D amp Hackett G (2002) Social cognitive career theory In DBrown (Ed) Career choice and development (pp 255minus311) 4th ed San Francisco
Jossey-BassLent R W Brown S D Nota L amp Soresi S (2003) Testing social cognitive interest
and choice hypotheses across Holland types in Italian high school students Journalof Vocational Behavior 62 101minus118
Lent R W Hackett G amp y Brown S D (2004) Una perspectiva Social Cognitiva de latransicioacuten entre la escuela y el trabajo (A Social Cognitive Perspective of the
transition between school and work) Evaluar 4 1minus22Lent R W amp Brown S D (2006) On conceptualizing and assessing social cognitive
constructs in career research A measurement guide Journal of Career Assessment 14 12minus35
Lent R W amp Sheu H (2010) Applying social cognitive career theory across culturesEmpirical status In J G Ponterotto J M Casas L A Suzuki amp C M Alexander(Eds) Handbook of multicultural counseling (pp 691minus701) Thousand Oaks CASage
Lopez F G Lent R W Brown S D amp Gore P A (1997) Role of social ndashcognitiveexpectations in high school students mathematics-related interest and perfor-mance Journal of Counseling Psychology 44 44minus52
Multon K D Brown S D amp Lent R W (1991) Relation of self-ef 1047297cacy beliefs toacademicoutcomesA meta-analyticinvestigation Journal of Counseling Psychology
38 30minus38Navarro R L Flores L Y amp Worthington R L (2007) Mexican American middle
school students goal intentions in mathematics and science A test of socialcognitive career theory Journal of Counseling Psychology 54 320minus335
OBrien V Martinez-Pons M amp Kopala M (1999) Mathematics self-ef 1047297cacy ethnicidentity gender and career interests related to mathematics and science Journal of Educational Research 92 231minus235
Organization for Economic Cooperation and Development (2001) Knowledge and skills for life First results from the OECD Programme for International Student Assessment (PISA) 2000 Paris OECD Publications
Pajares F (1996) Self-ef 1047297cacy beliefs in academic settings Review of EducationalResearch 66 543minus578
Pajares F amp Graham L (1999) Self-Ef 1047297cacy motivation constructs and mathematicsperformance of entering middle school students Contemporary EducationalPsychology 139 124minus139
Pajares F amp Schunk D H (2001) Self-beliefs and school success Self-ef 1047297cacy self-concept and school achievement In R J Riding amp S Rayner (Eds) Self Perception(pp 239minus266) Westport CT Ablex Publishing
Peacuterez E amp Cupani M (2008) Multiple intelligences self-ef 1047297cacy inventory revised(MISEI-R) Preliminary validation Revista Latinoamericana de Psicologiacutea 40 47minus58
Robbins S B Lauver K Le H Davis D Langley R amp Carlstrom A (2004) Dopsychosocial and study skill factors predict college outcomes A meta-analysisPsychological Bulletin 130 261minus288
SellsL W(1980) Themathematical 1047297lter andthe educationof women andminorities
In L H Fox L Brodey amp D Tobin (Eds) Women and the mathematical mystique(pp 66minus75) Baltimore Johns Hopkins University
Tabachnick B Gamp Fidell L S (2001) Using multivariate statistics 4thEd Boston Allynand Bacon
Turner S L amp Lapan R T (2005) Evaluation of an intervention to increase non-traditional career interests and career-related self-ef 1047297cacy among middle-schooladolescents Journal of Vocational Behavior 66 516minus531
Zimmerman B J Bonner S amp Kovach R (1996) Developing self-regulated learnersBeyond achievement to self-ef 1047297cacy Washington DC American PsychologicalAssociation
663M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663
8192019 Evaluacioacuten de modelo social cognitivo
httpslidepdfcomreaderfullevaluacion-de-modelo-social-cognitivo 55
institutions Future research should use a more heterogeneous sample
and explicitly assess the socioeconomic status of the students
Another limitation is that the measurement for academic achieve-
ment in mathematics canbe in1047298uenced by the idiosyncratic policies of
each institution or the educational orientation of each instructor Also
we acknowledge that our instrument measures math self-ef 1047297cacy
beliefs at a general rather than at a speci1047297c level The evidence shows
that the predictability of self-ef 1047297cacy measures depends on their
speci1047297
city and correspondence to actual math performance tasks(Bandura 1997) That is predictors and dependent variables must be
compatible in regards with content context temporal orientation and
speci1047297city level (Ajzen 1988) Future studies should aim at creating
new math self-ef 1047297cacy scales that measure this construct at a speci1047297c
level
Themain theoretical contributionof this study is the assessment of
theSCCT performancemodel in a novel cultural and linguistic context
namely middle school students in Argentina Interestingly the study
assessed all SCCT predictors jointly To our knowledge the literature
has yet to show a single large-scale test of the complete performance
model although numerous studies have examined subsets of the
model (eg Brown et al 2008) Thedevelopmental stage in which the
model is tested also deserves attention Early adolescence is a critical
stage for learning (Zimmerman Bonner amp Kovach 1996) character-
ized by a sharp decline in academic performance possibly caused by
the increasing challenges posed by middle school as well as the
inherent psychological and biological changes that occur during this
period
Beyond these theoretical implications the results suggest that the
SCCT could be used as a screening tool to identify students at-risk for
having for example diminished self-ef 1047297cacy in a given academic
domain Educational institutions could use this knowledge to design
experiences speci1047297cally aimed at improving these variables Notably
adolescents usually have limited knowledge about their capabilities
and career options a fact that results in stereotyped and unstable
vocational goals (Lent et al 2004) Therefore the development of
career goals can be halted early in life if the students are exposed to
educational environments that provide limited opportunities for
nurturing appropriate ef 1047297cacy or self-ef 1047297cacy skills and outcomeexpectations The results outlined in the present study could be used
to design interventions aimed at increasing the level of exposure to a
variety of career-relevant tasks and activities These interventions will
help develop task-speci1047297c concepts of self-ef 1047297cacy that in turn will
result in more realistic stable and useful vocational goals
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Peacuterez E amp Cupani M (2008) Multiple intelligences self-ef 1047297cacy inventory revised(MISEI-R) Preliminary validation Revista Latinoamericana de Psicologiacutea 40 47minus58
Robbins S B Lauver K Le H Davis D Langley R amp Carlstrom A (2004) Dopsychosocial and study skill factors predict college outcomes A meta-analysisPsychological Bulletin 130 261minus288
SellsL W(1980) Themathematical 1047297lter andthe educationof women andminorities
In L H Fox L Brodey amp D Tobin (Eds) Women and the mathematical mystique(pp 66minus75) Baltimore Johns Hopkins University
Tabachnick B Gamp Fidell L S (2001) Using multivariate statistics 4thEd Boston Allynand Bacon
Turner S L amp Lapan R T (2005) Evaluation of an intervention to increase non-traditional career interests and career-related self-ef 1047297cacy among middle-schooladolescents Journal of Vocational Behavior 66 516minus531
Zimmerman B J Bonner S amp Kovach R (1996) Developing self-regulated learnersBeyond achievement to self-ef 1047297cacy Washington DC American PsychologicalAssociation
663M Cupani et al Learning and Individual Differences 20 (2010) 659 ndash663