Gender Differences in First-Grade Mathematics Strategy Use: Parent and Teacher Contributions

Carr, Martha; Jessup, Donna L.; Fuller, Diana

doi:10.2307/749628

Cited by 64 publications

(45 citation statements)

References 31 publications

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“…In these studies, sex differences, favoring males, have been found for children's and young adults' strategic approaches to solving arithmetic problems and in the speed of executing some of the underlying component processes (Carr & Jessup, 1997;Carr et al, 1999;Fennema et al, 1998;Geary et al, 1993). The results are, however, inconsistent with Hyde et al's (1990) meta-analytic finding of no sex difference in computational abilities for 15-to 18-year-olds and a female advantage through early adolescence.…”

Section: Discussioncontrasting

confidence: 56%

“…Other studies of elementary-school children suggest no sex difference in overall arithmetical performance, but sex differences in problem-solving approaches are often found (Carr & Jessup, 1997;Carr, Jessup, & Fuller, 1999;Fennema, Carpenter, Jacobs, Franke, & Levi, 1998; but see Siegler, 1988). In these studies, boys used direct retrieval and covert strategies (e.g., mental counting) more often than girls did and girls used finger counting and overt strategies (e.g., blocks) more often than boys did.…”

mentioning

confidence: 82%

“…If the Royer et al findings are replicated, then follow-up studies with children and adolescents would be warranted, although, in any such studies, the assessment of sex differences in computational fluency should focus on strategy choice and speed of processing differences. This is because sex differences on paper-and-pencil computational tests are not always evident for adolescents and children (Carr & Jessup, 1997;Carr et al, 1999;Fennema et al, 1998). In any case, before such studies are conducted, an attempt to replicate Royer et al's most robust finding seems wise.…”

mentioning

confidence: 95%

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Sex Differences in Spatial Cognition, Computational Fluency, and Arithmetical Reasoning

Geary

Saults

Fan

et al. 2000

Journal of Experimental Child Psychology

235

141

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Alternative explanations for the male advantage in arithmetical reasoning, as measured by the ability to solve complex word problems, include a male advantage in spatial cognition and a male advantage in computational fluency. The current study was designed to test these competing hypotheses. To this end, 113 male and 123 female undergraduates were administered arithmetical computations and arithmetical reasoning tests, along with an IQ test and a test of spatial cognition. There was no sex difference on the IQ test, but males showed significantly higher mean scores on the arithmetical computations, arithmetical reasoning, and spatial cognition measures. A series of structural equation models indicated that individual differences in arithmetical reasoning were related to individual differences in IQ, spatial abilities, and computational fluency. Moreover, the results suggested that the male advantage in arithmetical reasoning is mediated by the male advantages in both computational fluency and spatial cognition.

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Section: Discussioncontrasting

confidence: 56%

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confidence: 82%

mentioning

confidence: 95%

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Sex Differences in Spatial Cognition, Computational Fluency, and Arithmetical Reasoning

Geary

Saults

Fan

et al. 2000

Journal of Experimental Child Psychology

235

141

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“…Gender effects have been investigated in children, rather than in adults. Several studies with children showed more frequent and more efficient retrieval use in boys than in girls (see, e.g., Carr & Jessup, 1997;Carr, Jessup, & Fuller, 1999;Royer, Tronsky, Chan, Jackson, & Marchant, 1999). Whether these differences exist in adulthood is a debated topic.…”

mentioning

confidence: 99%

Do multiplication and division strategies rely on executive and phonological working memory resources?

Imbo

Vandierendonck

2007

Memory & Cognition

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Working memory is a system devoted to short-term storage and processing and is used in various cognitive tasks, such as reading, reasoning, and mental arithmetic. Throughout the past decennium, research into the role of working memory in mental arithmetic has flourished (for a review, see DeStefano & LeFevre, 2004) and has shown that solving both simple arithmetic problems (e.g., 8 5, 3 9) and complex arithmetic problems (e.g., 23 98, 12 35) relies on working memory resources. The present study further investigates the role of working memory in simple-arithmetic strategies, on the basis of the multicomponent working memory model of Baddeley and Hitch (1974). In this model, there is an attentional system (the central executive) that supervises a phonological subsystem and a visuospatial subsystem. The phonological subsystem guarantees short-term maintenance of phonological information, and the visuospatial subsystem guarantees short-term maintenance of visuospatial information.The role of executive working memory resources in simple arithmetic has been shown extensively (see, e.g., Ashcraft, 1995;De Rammelaere, Stuyven, & Vandierendonck, 1999Deschuyteneer & Vandierendonck, 2005a, 2005bDeschuyteneer, Vandierendonck, & Muyllaert, 2006;Hecht, 2002;Lemaire, Abdi, & Fayol, 1996;Seitz & Schumann-Hengsteler, 2000. The role of phonological working memory resources in simple arithmetic is less clear. In some studies, an effect of phonological load on simple-arithmetic problem solving was observed (see, e.g., Lee & Kang, 2002;Lemaire et al., 1996;Seitz & Schumann-Hengsteler, 2002), whereas, in other studies, it was not (see, e.g., De Rammelaere et al., 1999Seitz & Schumann-Hengsteler, 2000). Investigations of the role of the visuospatial "sketch pad" in simple arithmetic are scarce (but see Lee & Kang, 2002;Seitz & Schumann-Hengsteler, 2000), and the findings in the few studies conducted are equivocal.A drawback of all the studies mentioned above, however, is that none of them showed any distinction between retrieval and nonretrieval trials. Yet it has been shown that adults use several strategies to solve even the simplest arithmetic problems (see, e.g., Hecht, 1999;. For instance, although direct memory retrieval (i.e., knowing that 3 4 12) is the most frequently used strategy, nonretrieval strategies (or procedural strategies) are used as well. Examples of such procedural strategies are transformation (e.g., 96 (10 6) 6 60 6 54) and counting (e.g., 4 7 7 . . . 14 . . . 21 . . . 28). The studies mentioned above notwithstanding, it is impossible to discern the specific simple-arithmetic strategies in which executive and phonological working memory resources are needed.Investigations of the roles of executive and phonological working memory across different simple-arithmetic strategies have only very recently been conducted, beginning with Hecht (2002). In his study, simple addition equa- 1759Copyright 2007 Psychonomic Society, Inc. Do multiplication and division strategies rely on executive and phonological working memory...

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“…Popular authors such as Gurian (5) make this error of inference, saying that girls and boys approach mathematics problems differently because of brain differences, not environmental forces, not understanding that different environmental experiences are registered precisely in the brain. Research, for example, shows that both teachers and parents, perhaps unintentionally, encourage girls and boys to use different strategies in solving mathematics problems (6).…”

mentioning

confidence: 99%

Reply to Crespi: Gender similarities, culture, and mathematics performance

Hyde¹,

Mertz²

2009

Proc. Natl. Acad. Sci. U.S.A.

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We appreciate Crespi's comments (1) regarding gender similarities in developmental dyscalculia and the biological basis of mathematics performance. We did not include developmental dyscalculia in our review (2), which focused on whether there are gender differences in average mathematics performance and at the level of the talented and mathematically gifted. Crespi's points (i) provide additional data supporting our conclusion of gender similarities in math performance and (ii) agree with our questioning of the validity of the Greater Male Variability Hypothesis. If males display greater variance in mathematical performance, then there should be an excess of males not only at the high end of the distribution, but also at the low end. Yet Crespi concludes that there is no gender difference at the low end of the distribution.Crespi goes on to argue that we conflated biology with determinism in our statements about cultural factors contributing to the gender difference in math performance. That was not our intent. Our argument was that cultural factors, not immutable biological factors, underlie the gender difference in mathematics performance. Of course, not all biological factors are immutable. And, certainly, biology is necessary for the development of mathematical skills; one needs a brain to learn math. Mathematical skills may show substantial heritability, as Crespi claims, but that does not mean that the gender difference is heritable or based on ''hard wiring'' of the brain. Modern neuroscientists, in fact, emphasize the phenomenal plasticity of the human brain, which allows it to be shaped by experience (3, 4). Even if gender differences have been found in the effect on math performance of transcranial magnetic stimulation of a brain region, (i) this finding has not been replicated to our knowledge and (ii) the effect may not be due to hard wiring of the brain, but rather to different experiences for males and females that result in slightly different brain functioning. Popular authors such as Gurian (5) make this error of inference, saying that girls and boys approach mathematics problems differently because of brain differences, not environmental forces, not understanding that different environmental experiences are registered precisely in the brain. Research, for example, shows that both teachers and parents, perhaps unintentionally, encourage girls and boys to use different strategies in solving mathematics problems (6).Crespi may be right that understanding the genetic and neurodevelopmental underpinnings of math performance may be useful in the design of optimal environments for math learning, but there is no evidence that one environment will be optimal for all girls and another, different one, will be optimal for all boys.

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Gender Differences in First-Grade Mathematics Strategy Use: Parent and Teacher Contributions

Cited by 64 publications

References 31 publications

Sex Differences in Spatial Cognition, Computational Fluency, and Arithmetical Reasoning

Sex Differences in Spatial Cognition, Computational Fluency, and Arithmetical Reasoning

Do multiplication and division strategies rely on executive and phonological working memory resources?

Reply to Crespi: Gender similarities, culture, and mathematics performance

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