Is Victor Better than Victoria at Maths?

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Is Victor Better than Victoria at Maths?Stelios N. Georgiou a , Panayiotis Stavrinides a & Theano Kalavanaa

a University of Cyprus , CyprusPublished online: 28 Nov 2007.

To cite this article: Stelios N. Georgiou , Panayiotis Stavrinides & Theano Kalavana (2007) Is VictorBetter than Victoria at Maths?, Educational Psychology in Practice: theory, research and practice ineducational psychology, 23:4, 329-342

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Educational Psychology in Practice,Vol. 23, No. 4, December 2007, pp. 329–342

ISSN 0266-7363 (print)/ISSN 1469-5839 (online)/07/040329–14© 2007 Association of Educational PsychologistsDOI: 10.1080/02667360701660951

Is Victor Better than Victoria at Maths?

Stelios N. Georgiou*, Panayiotis Stavrinides and Theano KalavanaUniversity of Cyprus, CyprusTaylor and Francis LtdCEPP_A_265936.sgm10.1080/02667360701660951Educational Psychology in Practice0266-7363 (print)/1469-5839 (online)Original Article2007Taylor & [email protected]

The aim of this study was to examine whether there are gender differences in actual maths achieve-ment, in attitudes towards maths, and in relevant achievement attributions among early adoles-cents. The participants were 255 eighth grade students (mean age 14.2) from 10 randomlyselected public junior high schools in Cyprus. They completed a questionnaire that measured theirattributions of their own maths achievement and their attitudes towards the subject (how attractiveand useful it is). Then they took a maths achievement test and immediately afterwards theyreported their affective reactions towards the test (how challenging or threatening they thought itwas). No significant differences were found between boys and girls in actual maths achievement.Significant differences were found, however, in the way the two genders explain their performance.Boys tend to believe more than girls do that their intellectual abilities are causing their high marksin maths. Also, it was found that high achievement could predict a positive attitude towards math-ematics, but not vice versa. These findings contradict the widespread beliefs that (a) girls are not asgood at maths as boys are; and (b) better attitudes towards maths lead to better performance.

Introduction

A widespread belief is that “girls are not good at maths”. Is this true? Many research-ers seem to think so. Kimball (1989), for example, cites many studies showing thatboys in high school achieve consistently higher scores than girls on standardisedmaths tests. More recent studies (Hedges & Nowell, 1995; Randhawa, 1994) confirmthese findings. Beller and Gafni (1996) report that the only differences in mathsperformance found among students from seven countries were in favour of boys. Ina longitudinal study (Campell & Beaudry, 1998) it was found that high achievingmales scored significantly higher in maths than high achieving females. Davies andBrember (1999) examined a large sample (N = 1488) of sixth grade students foreight consecutive years in terms of their maths attainment on a standardised test.Their results indicate that boys outperform girls in maths scores at a statistically

*Corresponding author. Department of Psychology, University of Cyprus, PO Box 20537, Nicosia,CY 1678, Cyprus. Email address: [email protected]

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330 S. N. Georgiou et al.

significant level. Interestingly, the same was true in terms of these students’ self-concept: that is, boys had not only better basic skills, but they had also a more positiveview of themselves than girls. Penner (2003) used data from the Third InternationalMathematics and Science Survey (TIMSS) of students from 10 countries to examinewhether there were gender differences. Such differences were found in favour of boysin all cases. They were minimal on easy questions and increased as questions grewmore difficult.

For many years, research on learning mathematics was cognitively oriented andemphasised intra-personal factors such as ability and talent. It was only during thelast two decades that affective and interpersonal factors were included in thisresearch. The currently accepted position (Leder, Pehkonen, & Torner, 2002) isthat achievement in mathematics is a function of many interrelated variables such asstudent ability, attitudes and perceptions, socioeconomic variables, parent and peerinfluences. Are there gender differences in all these variables? Research says that inmost of them there are: for example, males tend to exhibit a self-enhancing patternof attitudes and expectations about their own aptitudes and achievement whereasfemales tend to exhibit a self-derogating such pattern (Burgner & Hewstone, 1993;Furnham & Rawles, 1995; Stipek & Gralinski, 1991). The variables that are morerelevant to the present discussion are the explanations that students give for theirachievement in maths (i.e. their attributions) and their attitudes towards maths.Research findings regarding these variables will be reviewed below.

One of the most interesting gender differences is the way boys and girls explaintheir successes and failures. Yee and Eccles (1988) report that boys tend to attributetheir success in mathematics to ability, while girls tend to attribute their own successin the same area to effort. Similarly, girls tend to attribute their failure to lack of abil-ity whereas boys attribute their failure to lack of effort (Dweck, Davidson, Nelson, &Enna, 1978). An immediate consequence of this attitude for girls is the decreasedmotivation and hopelessness on the task (Abramson, Seligman, & Teasdale, 1978).

Lightbody, Siann, Stocks and Walsh (1996) asked students to rate the importanceof factors contributing to academic success. They found that females rated hardwork and teachers’ liking for the student to be more important than males did. Incontrast, males rated cleverness, talent and luck to be more important. In a studyconducted by Powers and Wagner (1984), it was found that sixth grade boys attrib-uted school failure more to bad luck than girls did.

Attribution theory refers to the individuals’ effort to assign meaning to observedevents by suggesting causal explanations for them. In educational settings, studentswho fail an examination may attribute their failure to insufficient effort, while otherstudents may blame the teacher, their parents or bad luck for the poor examinationresults. Other students may conclude that they have no aptitude for the particularsubject after all, and change their whole approach accordingly as a result of thisperception.

The proponents of this theory maintain that actions are usually attributed to stableand enduring factors, such as the actor’s personality characteristics, rather than tran-sitory or variable factors such as moods. Weiner (1985) has proposed an influential

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Is Victor Better than Victoria at Maths? 331

taxonomy of causal attributions, using a three dimensional classification system. Thefirst dimension is the locus of the attribution (i.e. whether the assigned cause is inter-nal or external to the individual). The second dimension refers to the stability of theperceived causal factor over time and the third dimension is controllability (whetheran attributed cause is under the control of the individual or not). Thus, according tothis classification system, a student who believes that failure on a task was due to hisinadequate effort has assigned an internal, unstable, and controllable cause to theexperienced failure, because the locus of the perceived cause is internal to the actor,it can change (i.e. more effort can be exercised next time) and it is indeed under thecontrol of the individual. If low ability were thought to be the cause of the failure,then this would be an internal, stable and uncontrollable attribution.

In a particularly relevant study (Wong, 1993) it was found that the participantshad different perceptions of the cause of their performance in an actual examinationof mathematics. High achievers attributed their success to effort and intellectualability, while low achievers attributed their failure to ability and difficulty level of theexamination. Also, the former group had a more positive approach towards mathe-matics than the latter. Generally, girls had lower expected grades and lowertendency towards mathematics than boys. Girls were likely to attribute their successto external causes (e.g. help of their family, easy examination and easy subject).Also, in relation to boys, they attributed their failure to more stable and internalfactors such as low intelligence.

Using data from the Third International Mathematics and Science Study(TIMSS), House (2003) found that student self-beliefs were associated withachievement outcomes: that is, those who had high scores in maths were also morelikely to indicate that they enjoy learning mathematics and that mathematics isimportant to everyone’s life. Also, students who attributed their success to internaland controllable factors had higher scores than those who attributed it to externaland uncontrollable factors. Further, Ercikan, McCreith and Lapointe (2005) foundthat the strongest predictors of maths achievement and participation in advancedmathematics courses were students’ attitudes toward mathematics.

One of the unresolved questions in the literature is the direction of influencebetween attitudes towards mathematics and actual achievement in this subject. Someresearchers (Reynolds & Walberg, 1992) claim that attitudinal variables serve aspredictors of maths achievement. In contrast, others (see Ma & Xu, 2004) maintainthat the opposite is true: that is, poor achievement in mathematics results in negativeattitudes towards this subject, but not vice versa. Improving maths achievement canlead to better attitudes towards maths, but improving attitudes cannot improveachievement. What is established is the fact that motivation to study mathematics isa correlate of maths achievement (Skaalvik, 1994; Skaalvik & Rankin, 1995).

A number of researchers support the notion that attitudes toward mathematicsare shaped by social influences (Singh, Granville, & Dika, 2002): for example, atti-tudes of parents and teachers toward mathematics and, moreover, their attitudestoward children as learners of mathematics, affect the children’s own perceptions oftheir ability and interest. A child’s school performance can be influenced directly or

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indirectly by the way his or her parents explain it. As Stevenson and Lee (1990)comment:

… when parents believe that success in school depends on ability in contrast to effort,they are less likely to foster participation in activities related to academic achievementthat would elicit strong effort toward learning on the part of their children. (Stevenson& Lee, 1990, p. 66)

Vanden and Peterson (1991) examined the relationship between the explanatorystyle of parents for events involving their school-aged children and the children’sactual classroom performance. Their findings provide support to the claim that theattributional beliefs of parents can affect the behaviour of their children. Attributionsto external and stable characteristics over which the child has no control (such asluck or family circumstances) have been linked to underachievement (O’Sullivan &Howe, 1996; Powers & Wagner 1984). In contrast, attributions of achievement toeffort have been associated positively to better school grades (Christenson, Rounds,& Gorney, 1992). By means of a structural equation model and a path analysisprocedure, Georgiou (1999) was able to show that a line of influence exists betweenparental attribution style, the type and degree of parental involvement and thechild’s actual academic achievement. Parental belief systems affect their children inmany different ways. McGillicuddy-Delisi (1992), for example, has reported “moth-ers who believed that the course of development is different for boys and for girlshad children who were rated more poorly in every academic area polled” (p. 131).

Teachers’ attributions of student achievement seem to have an effect on studentmotivation. One of the “bad things good teachers sometimes do” in class accordingto Graham (1990) is to show sympathy to certain low achieving students by assign-ing easier tasks and by not expecting the same quality of work as with the rest ofthe class. Teachers do this when they attribute failure to low ability (Georgiou,Christou, Stavrinides, & Panaoura 2002). Girls are often the victims of this. IfVictoria, for example, does poorly on a maths test and the stereotype “girls are notgood in maths” is used in order to explain this event, then a series of consequencescan be expected. The first is a consensus expressed by her environment that herlow performance is not her fault; it is due to something chronic, unchangeable anduncontrollable: that is, Victoria has no aptitude for maths.

Forming this judgment about the girl will likely elicit sympathy and some assistance.However, she may eventually be neglected and denied opportunities relevant to maths ifher inability is deemed inalterable. If the girl were exposed to the stereotype, she wouldsuffer feelings of shame and lowered self-esteem in that domain. Over time, this couldcause her to withdraw from mathematical tasks. (Reyna, 2000, p. 91)

Gender stereotypes create beliefs: for example, students who believe that boys knowmore things about maths will ask their male peers for help in maths exercises. Also,this stereotype can affect teachers’ reactions, such as giving more chances to boys toanswer difficult or challenging questions (Lundeberg, 1997; Sadker, 1999).

To summarise, a vicious circle may be in action. Gender differences in favour ofboys have been systematically observed in maths achievement for many years. This

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has created the stereotype that girls are not good at maths. Helwig, Anderson, andTindal (2001) point out that since boys tend to outperform girls in a wide variety ofmaths achievement measures, and since the media exaggerate and sensationalisethese differences, “the possibility exists that teachers may acquire erroneous negativeperceptions of the mathematics abilities of their female students” (p. 93).

This, in turn, affects girls’ motivation and attitudes towards maths. It also influ-ences the attitudes and behaviour of important others such as teachers and parents.Stereotypical thinking of all these people, including girls themselves, contributes tolower maths achievement, and the cycle repeats itself. The fact that gender differ-ences in maths achievement are non-existent in the early years and appear later inhigh school is an argument in favour of the use of literature on stereotyping toexplain these differences.

The aim of this study was to examine whether there are gender differences inmaths achievement among early adolescents. Also, the study tried to identify possi-ble differences between boys and girls in a series of attitudinal and affective variables(i.e. attitudes towards maths, maths achievement attributions and affective reactionsafter taking a maths test).

Hypotheses

The following directional hypotheses were stated, based on earlier research:

1. The mean maths achievement score of boys will be significantly higher than thecorresponding score of girls.

2. High achieving boys will have a significantly higher mean score in attributingachievement to ability than high achieving girls, while high achieving girls willhave a significantly higher mean score in attributing achievement to effort thanhigh achieving boys.

3. There will be a statistically significant difference in favour of boys in the meanscores of attraction towards mathematics between boys and girls.

4. High achieving students will have a significantly higher mean score in findingthe test challenging than low achieving students, while low achieving studentswill have a significantly higher mean score in finding the test threatening thanhigh achieving students.

5. Positive attitudes (attraction) towards maths will be able to predict high mathsachievement of both genders.

Method

Participants

A sample of 255 eighth grade students (mean age 14.2) participated in this study.They were Greek Cypriot students attending public high schools, and about half ofthem (54%) were female. The sampling procedure was as follows: 10 junior highschools (six situated in urban and four in rural areas) were randomly selected from

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the major Nicosia District. One of each school’s eighth grade classes was alsorandomly selected and all its students were included in the sample. The only crite-rion that was applied in the selection of schools was the socio-economic status of thecommunity they serve. The careful sampling procedure followed suggests that theoutcome is a non-biased, representative sample of 14-year-old Greek Cypriot earlyadolescents in terms of gender and family background. It should be noted that chil-dren in Cyprus enter elementary school at age six and then they enter junior highschool at age 12-years-old. Therefore, the eighth grade students (second grade ofhigh school after six years of elementary school) are about 14-years-old.

Tasks and Procedures

The data for this study were collected by means of the following self-report scales:Attitudes Towards Mathematics Scale, Maths Achievement Attributions Scale, amaths achievement test (TIMSS) and the Affective Reactions Scale.

Attitudes Towards Mathematics Scale

This scale was developed on the basis of earlier research (House, 2003; Leder et al.,2002) and measures two dimensions of attitudes towards maths: attraction (forexample items such as “Mathematics is an attractive subject”; “I like learning math-ematics”) and usefulness (for example items such as “Mathematics is important inour lives”; “Mathematics is useful in developing thinking abilities”). The scaleconsists of a total of 16 items, four of which have negative meaning (for example,“I hate maths”).

Maths Achievement Attributions Scale

This is an adaptation of the O’Sullivan and Howe (1996) scale but it refers to mathsachievement rather than reading as the original scale does. It follows Weiner’s(1985) typology and it was used in an earlier study (Georgiou, 1999b). Some exam-ples of the items included (20 in total) are the following: “My performance in mathsdepends on the effort I put in at home in order to learn”; “My performance in mathsdepends on the talent I have for this subject”; “My performance in maths dependson my level of intelligence”; “My performance in maths depends on my parents’expectations”.

As soon as all students in the classroom completed the attitudes and attributionspart of the questionnaire, a test of mathematics achievement was administered tothem. It included 10 exercises of increasing difficulty. The test was constructed onthe basis of the released items of the original TIMSS assessment of mathematics ineighth grade children. This test was developed as part of an international project thatcompares mathematics achievement of students from many different countries,including the UK. The TIMSS data have been used by numerous researchers (seeHouse, 2003; Penner, 2003). Cyprus is one of the participating countries and has a

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national representative in planning the testing procedure. Thus, the test’s content isconsistent with the local taught curriculum. The students were allowed 15 minutesto complete the test and when the time was up they were instructed to stop workingon the exercises. Exercises that remained unsolved were treated as wrong. Possiblescores ranged between 0 and 10.

Affective Reactions Scale

The final part of the assessment included a 16-item questionnaire measuring thestudents’ affective reaction to the mathematics examination. Examples of items thatmake up this scale are the following: “The exercises I have just completed motivatedme to prove what I know”; “I feel upset after taking the maths test”; “I worry thatothers may have performed better than me”; “The exercises made me experiencenegative feelings like discomfort, shame, sadness, and anger”.

The following format was used in all the scales, with the exception of the achieve-ment test: each statement was phrased as a categorical proposition and the partici-pants were asked to indicate their agreement based on a five-point Likert type of scale(“Absolutely agree”, “Agree”, “Undecided”, “Disagree”, “Absolutely disagree”).The scoring was from 4–0 in a descending order. The scoring was reversed for someitems depending on their meaning.

The three self-report scales were factor analysed separately in order to create moremeaningful constructs. The varimax rotation method was used for this analysis. Theexploratory factor analysis (EFA) of the attitudes scale produced only one reliablefactor, titled “attraction”, and not two as reported by previous studies. Its Cronbachalpha index was .63 and it was able to explain 42% of the variance. Examples ofitems for this factor are “maths is an important subject for people’s lives”; “mathscontributes to our cognitive development”; “I usually enjoy learning mathematicalconcepts” and “maths is a boring subject” (reversed scoring).

The attributions scale produced three factors, namely “ability”, “effort” and“family”. The alpha values were .67, .63 and .61 respectively. Some examples ofitems loading on the corresponding factors are the following: “My maths achieve-ment is due to my ability”; “… my effort at home”; “… my parents’ expectations”.Together, these factors explained 62% of the variance. Finally, the affective reac-tions scale produced two factors: in response to the question “I found this maths test…” the factors extracted were: “challenging” (.60) and “threatening” (.62)—alphavalues appear in parenthesis. Together, these factors explained 67.8% of the vari-ance. The loadings of the items in the three scales (i.e. attitudes, attributions, affec-tive reactions) were all above .75. The six factors extracted from the three scaleswere saved as variables and were used for further analysis.

Results

Research Hypothesis 1 was not supported by the results. The mean scores of boysand girls in maths achievement were not significantly different (boys’ mean score =

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4.07, sd = 2.1 and girls’ mean score = 3.82, sd = 1.8, t = .78, p > .05): that is, nogender differences in maths achievement were found among these 14-year-oldstudents.

In order to test for possible differences in the attitude, attribution and affectivereactions factors, four groups were created as follows: boys with high achievement,boys with low achievement, girls with high achievement and girls with low achieve-ment. The criterion used was the following: high achievement was operationallydefined as any score that was higher than one standard deviation above the mean ofthe total distribution of scores, while low achievement was operationally defined asany score lower than one standard deviation below the mean of the total distributionof scores. One-way analysis of variance was computed for testing the difference inmean scores of these four groups. The most notable finding was that high achievingboys had a significantly higher mean score in ability attributions than all the othergroups (X = 3.42). Table 1 shows all the details of the ANOVA and the multiplecomparisons test applied. However, high achieving girls did not have significantlyhigher mean score in effort attributions than high achieving boys. Thus, ResearchHypothesis 2 was only partially supported.

Research Hypothesis 3 was not supported by the results. High achieving boys hadsignificantly higher attitude (attraction) towards maths only in comparison to lowachieving boys and girls, but not in comparison to high achieving girls. That is, highachieving boys and girls do not differ significantly in their attitudes towards maths.

Research Hypothesis 4 was only partially supported by the data analysis. Highachieving boys and girls expressed positive affective reactions after taking the mathstest (i.e. they found it to be challenging), while low achieving boys and girlsexpressed negative affective reactions after taking the maths test (i.e. they found it tobe threatening). However, only the challenging affective reactions were significantlydifferent between the two genders. Interestingly, both affective reactions after takingthe maths test (challenging and threatening) were good predictors of the test’sresults (i.e. maths achievement).

Table 1. Mean differences in attitudes, attributions and affective reactions based on gender by achievement analysis of variance

Gender by achievement

Dependent measures Boys/high (a) Boys/low (b) Girls/high (c) Girls/low (d)

Attraction 3.57bd 2.80 3.44 3.10Family 2.15 2.38c 1.71 1.94Effort 2.92 2.70 3.03 2.82Ability 3.42bcd 2.65 2.85 2.50Challenging 2.92bd 2.00 2.47d 1.72Threatening 1.42 1.76 1.67 1.95

Note: Mean scores with subscripts indicate significant difference (p < .05) between the particular score and that of the group that the subscript indicates.

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A stepwise regression test was applied in order to identify the best model thatcould predict maths achievement. It was found that three factors, namely attributionto ability, finding the maths test as challenging and finding it threatening (with anegative beta index) could best predict maths achievement scores (see Table 3).Thus, even though attraction to maths and maths achievement were significantlycorrelated (r = .24, p < .01) (see Table 2), the predictive ability of these two factorswas unidirectional: that is, high achievement could predict a positive attitudetowards mathematics, but not vice versa (see Tables 3 and 4). Consequently,Research Hypothesis 5 was not supported by the results.

To summarise, this study has produced the following results.

1. No statistically significant gender differences in maths achievement seem to existamong these 14-year-old students.

2. As predicted, high achieving boys had a significantly higher mean score in abilityattributions than all the other groups (i.e. they believed that their grades weredue to their intelligence).

3. High achieving boys and girls do not differ significantly in their attitudestowards maths (i.e. they both find it to be an attractive subject). This was nottrue for low achieving boys and girls.

Table 2. Correlation coefficients between maths achievement, attitude, causal attributions, and affective reactions

1 2 3 4 5 6 7

1. Achievement – .24** .13 .02 .24** .32** −.142. Attraction – .26** .22** .23** .16* −.043. Family – .09 .05 .07 −.014. Effort – .19* .08 .065. Ability – .14 .066. Challenging – .037. Threatening –

Notes: *p < .05, ** p < .01.

Table 3. Regression analysis predicting maths achievement

Predictors B SE Beta

Attraction .37 .22 .13Family .13 .16 .06Effort −.18 .19 −.07Ability .37 .16 .17*Challenging .43 .13 .24**Threatening −.32 .15 −.16*

Note: R2 = .21; * p < .05, ** p < .01.

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4. Students who do well in maths find the topic challenging, while those who donot do well find it threatening.

5. High achievement could predict a positive attitude towards mathematics, butsuch an attitude could not predict good achievement.

Discussion

The main aim of this study was to identify possible gender differences in mathsachievement among early adolescents (14-year-olds). Such differences, however,were not found. Similarly, no significant gender differences were found in attitudestowards maths. Thus, the results of this study support that Victor is not necessarilybetter than Victoria in maths achievement. Their only difference lies in the explana-tion of their respective performance. Boys tend to believe more than girls do thattheir intellectual abilities are causing their high marks in maths. This is in line withearlier studies (Lightbody et al., 1996; Yee & Eccles, 1988) that have compared theexplanatory schemes used by boys and girls. Even in the absence of any difference inactual achievement, girls refuse to emphasise their abilities, whereas boys do not missthe chance to do so. This result is in line with earlier findings: for example, Daviesand Brember (1999) report that in their study boys showed higher self-concept thangirls and Furnham and Rawles (1995) report that girls exhibited a self-derogatingattribution pattern.

As for the causal relationship between attitude and achievement, the data do notsupport the idea that a student (boy or girl) who has more positive attitudes towardsthe subject does better at the maths test. The reverse seems to be true. If mathsachievement could be improved by, for example, better teaching methods, moremotivated teachers or better textbooks, then attitudes towards maths would improvetoo. Generally, the results of this study are in line with those reported by Ma and Xu(2004) and they particularly support their argument that “the causal relationshipbetween attitude and achievement is gender invariant” (p. 276).

Manning (1998) summarises findings of many studies showing that there are littledifferences between boys and girls in maths ability, effort or interest until the adoles-cent years. “Then, as social pressures increase, girls tend to exert less effort in studying

Table 4. Regression analysis with maths achievement predicting attitudes, attributions and affective reactions

Predicted measures B SE Beta R2

Attraction .08 .02 .24** .06Family .05 .03 .13 .01Effort .01 .03 .02 .00Ability .11 .03 .24** .06Challenging .18 .04 .32** .10Threatening −.07 .03 −.14 .02

Notes: * p < .05, ** p < .01.

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mathematics, which progressively limits their future education and, eventually, theircareer choices” (p.168). If age is a factor in the gender differences found in mathsachievement, then one way to explain the phenomenon is by using our knowledge onstereotypes. Stereotypes are both descriptive and explanatory tools in that they explain(in a biased and generalised manner) what a group is and does, but also why groupmembers are the way they are. When a stereotype is activated, it tends to portraypeople within that social category as possessing the characteristics associated with thestereotyped group. Stereotypes have two fundamental functions: (a) they give indi-viduals a basis for immediate action in uncertain circumstances; and (b) they allowindividuals to simplify complex social environments (Dijker & Koomen, 1996; Fiske,1998). For many years, girls have been excluded from well paying and professionallysatisfying jobs that require maths skills, not necessarily because they lacked the ability,but because they couldn’t break the vicious circle created by the existing gender stereo-type. As Reyna (2000) points out, gender stereotypes:

… can impede people’s goals through catalyzing and justifying negative evaluationsand punitive or rejecting behaviours toward the stereotyped. Stereotypes also createinternal barriers to success by propagating self-doubt, dashed hopes for future, or lostconfidence in an environment that does not let the stereotyped succeed. (Reyna, 2000,p. 106)

A stereotype ceases to exist only when reality proves it wrong. For this to happen,certain elements in the equation (to use a maths term) need to change. Some ofthem may have already changed. As many authors point out (Feingold, 1988; Frost,Hyde, & Fennema, 1994), in recent years gender differences both in the cognitiveand the affective domain have gone through a great deal of change. Therefore, itmight be necessary to reconsider and re-examine the role of gender in achievementsettings. It is possible that changes in child rearing practices have caused the disap-pearance of the differences between the two sexes in maths achievement, or haveeven brought about the reversal of the phenomenon: for example, Alkhateeb (2001),studying twelfth grade students in an Arab culture, found that females achievedbetter in mathematics compared to boys. Similarly, Abayomi and Mji (2004) failedto find gender differences in maths achievement among young adults in an Africanculture.

To conclude, the findings of the current research are in conflict with the positionexpressed by many researchers about (a) the existing gender differences in mathsachievement among early adolescents (Beller & Gafni, 1996; Campell & Beaudry,1998; Davies & Brember, 1999; Hedges & Nowell, 1995; Randhawa, 1994); and (b)the direction of influence between attitude and achievement (Reynolds & Walberg,1992; Skaalvik, 1994; Skaalvik & Rankin, 1995). This study contributes to the liter-ature by challenging a widespread conviction. The results show that girls are as goodin maths as boys, even in early adolescence, when other studies report gender differ-ences much earlier (Davies & Brember, 1999; Penner, 2003). At least this seems tobe the case among Greek Cypriot 14-year-old students. Further research is neededto find out if this is also true for members of other cultural and age groups.

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These results might be particularly useful for applied educational psychologistsworking with young people with low self-esteem or low self-efficacy. It is possiblethat students may underestimate or doubt their own abilities in different areas, notonly mathematics, because they happen to belong to certain groups who are affectedby social bias and discrimination and not because they indeed lack these abilities atan individual level. Using such understanding may help youngsters, their parents orcarers and teachers to break the vicious circle created by existing stereotypes. In thisway, all youngsters may be encouraged to fulfil their potential.

References

Abayomi, A., & Mji, A. (2004). Is gender a factor in mathematics performance among Nigerianpre-service teachers? Sex Roles, 51, 749–752.

Abramson, L. Y., Seligman, M. E. P., & Teasdale, J. D. (1978). Learned helplessness in humans:Critique and reformulation. Journal of Abnormal Psychology, 87, 49–74.

Alkhateeb, H. M. (2001). Gender differences in mathematics achievement among high schoolstudents in the United Arab Emirates, 1991–2000. School Science and Mathematics, 101(1), 5–9.

Beller, M., & Gafni, N. (1996). The 1991 International Assessment of Educational Progress inMathematics and Sciences: The gender differences perspective. Journal of EducationalPsychology, 88(2), 365–377.

Burgner, D., & Hewstone, M. (1993). Young children’s causal attributions for success and failure:“Self-enhancing” boys and “self-derogating girls”. British Journal of Developmental Psychology,11(2), 125–129.

Campbell, J. R., & Beaudry, J. S. (1998). Gender gap linked to differential socialization for high-achieving senior mathematics students. The Journal of Educational Research, 91, 140–147.

Christenson, S., Rounds, T., & Gorney, D. (1992). Family factors and student achievement: Anavenue to increase students’ success. School Psychology Quarterly, 7(3), 178–206.

Davies, J., & Brember, I. (1999). Boys outperforming girls: An 8-year cross-sectional study of attain-ment and self-esteem in Year 6. Educational Psychology, International Journal of ExperimentalEducational Psychology, 19(1), 5–16.

Dijker, A. J., & Koomen, W. (1996). Stereotyping and attitudinal effects under time pressure.European Journal of Social Psychology, 26, 61–74.

Dweck, C. S., Davidson, W., Nelson, S., & Enna, B. (1978). Sex differences in learned helpless-ness: II. The contingencies of evaluative feedback in the classroom and III. An experimentalanalysis. Developmental Psychology, 14, 268–276.

Ercikan, K., McCreith, T., & Lapointe, V. (2005). Factors associated with mathematics achieve-ment and participation in advanced mathematics courses: An examination of Gender differ-ences from an International perspective. School Science and Mathematics, 105(1), 5–14.

Feingold, A. (1988). Cognitive gender differences are disappearing. American Psychologist, 43,95–103.

Fiske, S. T. (1998). Stereotyping, prejudice, and discrimination. In D. T. Gilbert, S. T. Fiske, &G. Lindzey (Eds.), The handbook of social psychology (Vol. 2, pp. 357–411). New York:McGraw-Hill.

Frost, L. A., Hyde, J. S., & Fennema, E. (1994). Gender, mathematics performance, and mathe-matics related attitudes and affect: A meta-analytic synthesis. International Journal of EducationalResearch, 21, 373–386.

Furnham, A., & Rawles, R. (1995). Sex differences in the estimation of intelligence. Journal ofSocial Behavior and Personality, 10(3), 741–748.

Georgiou, S. N. (1999a). Parental attributions as predictors of involvement and influences ofachievement. British Journal of Educational Psychology, 69(3), 409–429.

Dow

nloa

ded

by [

Uni

vers

ity o

f T

exas

Lib

rari

es]

at 0

5:30

26

Nov

embe

r 20

14


Georgiou, S. N. (1999b). Achievement attributions of sixth grade students and their parents.Educational Psychology, International Journal of Experimental Educational Psychology, 19(4),399–412.

Georgiou, S. N., Christou, C., Stavrinides, P., & Panaoura, G. (2002). Teacher attributions ofstudent failure and teacher behavior towards the failing student. Psychology in the Schools,39(5), 583–595.

Graham, S. (1990). Communicating low ability in the classroom: bad things good teachers some-times do. In S. Graham, & V. Folkes (Eds.), Attribution theory: Applications to achievement,mental health and interpersonal conflict. Hillsdale, NJ: Lawrence Erlbaum.

Hedges, L. V., & Nowell, A. (1995). Sex differences in mental test scores, variability and numbersof high scoring individuals. Science, 269, 41–45.

Helwig, R., Anderson, L., & Tindal, G. (2001). Influence of elementary student gender onteachers’ perceptions of mathematics achievement. The Journal of Educational Research, 95,95–104.

House, J. D. (2003). Self-beliefs and science and mathematics achievement of adolescent studentsin Hong Kong: Findings from the Third International Mathematics and Science Study(TIMSS). International Journal of Instructional Media, 30, 195–211.

Kimball, M. M. (1989). A new perspective on women’s maths achievement. Psychological Bulletin,105(2), 198–214.

Leder, G. C., Pehkonen, E., & Torner, G. (2002). Beliefs: A hidden variable in mathematics educa-tion? Dordrecht: Kluwer.

Lightbody, P., Siann, G., Stocks, R., & Walsh, D. (1996). Motivation and attribution at secondaryschool: The role of gender. Educational Studies, 22(1), 13–25.

Lundeberg, M. A. (1997). You guys are overreacting: Teaching prospective teachers about subtlegender bias. Journal of Teacher Education, 48, 55–61.

Ma, X., & Xu, J. (2004). Determining the causal ordering between attitude toward mathematicsand achievement in mathematics. American Journal of Education, 110, 256–280.

Manning, L. (1998). Gender differences in young adolescents’ mathematics and science achieve-ment. Childhood Education, 74, 168–172.

McGillicuddy-Delisi, A. (1992). Parents’ beliefs and children’s personal–social development. In I.Sigel, A. McGillicuddy-Delisi, & J. Goodnow (Eds.), Parental belief systems: The psychologicalconsequences for children. New York: Erlbaum.

O’Sullivan, J., & Howe, M. (1996). Causal attributions and reading achievement: Individualdifferences in low income families. Contemporary Educational Psychology, 21(4), 363–387.

Penner, A. M. (2003). International gender X item difficulty interactions in mathematics andscience achievement tests. Journal of Educational Psychology, 95, 650–656.

Powers, S., & Wagner, M. (1984). Attributions for school achievement of middle school students.Journal of Early Adolescence, 4(3), 215–222.

Randhawa, B. S. (1994). Self-efficacy in mathematics, attitudes, and achievement of boys and girlsfrom restricted samples in two countries. Perceptual and Motor Skills, 79, 1011–1018

Reyna, C. (2000). Lazy, Dumb, or Industrious: When stereotypes convey attribution informationin the classroom. Educational Psychology Review, 12, 85-110.

Reynolds, A. J., & Walberg, H. J. (1992). A structural model of science achievement and attitude:An extension to high school. Journal of Educational Psychology, 84(3), 371–382.

Sadker, D. (1999). Gender equity: Still knocking at the classroom door. Educational Leadership,56, 22–26.

Singh, K., Granville, M., & Dika, S. (2002). Mathematics and science achievement: Effects ofmotivation, interest, and academic engagement. The Journal of Education Research, 95(6),323–331.

Skaalvik, E. M. (1994). Attribution of perceived achievement in school in general and in mathsand verbal areas: Relations with academic self-concept and self-esteem. British Journal ofEducational Psychology, 64(1), 133–143.

Dow

nloa

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Uni

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exas

Lib

rari

es]

at 0

5:30

26

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Skaalvik, E. M., & Rankin, R. J. (1995). A test of the internal/external frame of reference model atdifferent levels of maths and verbal self-perception. American Educational Research Journal,32(1), 161–184.

Stevenson, H., & Lee, S. (1990). Contexts of achievement. Monographs of the Society for Research inChild Development, 55(1/2, serial number 221).

Stipek, D., & Gralinski, H. (1991). Gender differences in children’s achievement-related beliefs andemotional responses to success and failure in mathematics. Journal of Educational Psychology,83(3), 361–371.

Vanden, A., & Peterson, C. (1991). Parental explanatory style and its relationship to the classroomperformance of disabled and nondisabled children. Cognitive Therapy and Research, 15(4),331–341.

Weiner, B. (1985). An attributional theory of achievement motivation and emotion. PsychologicalReview, 92, 548–573.

Wong, D. P. (1993). Causal attributions and affective reactions to academic performance of Chinesestudents in Hong Kong. Unpublished master’s thesis, The Chinese University of Hong-Kong,Division of Education.

Yee, D., & Eccles, J. (1988). Parenting perceptions and attributions for children’s maths achieve-ment. Sex Roles, 19, 317–333.

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