An Explanation and Evaluation of Various Theories on the Gender Difference in Mathematics

Daryl BagleyPsychology

Strawberry Crest High SchoolMay 2014

Word Count: 3595

Abstract

The goal of this paper is to identify, explain, and evaluate various explanations for the gender gap in mathematics.

This paper evaluates explanations in the cognitive, humanist, socio-cultural, and biological levels of analysis. Cognitive theories consider increased male competition, risk-taking, mathematical reasoning, and spatial ability as causes for the gap. Humanism claims that women's priorities are different from that of men. Socio-cultural explanations include the idea of low female confidence, math anxiety, romantic desirability, and the stereotype threat. Biological psychology claims that brain structure differences create the gap.

The sources for this paper include psychological journals, books, contemporary articles, and psychological studies. The sources were evaluated critically and compared against one another.

In conclusion, the gap has many causes. Because doing math is a cognitive process, there must be some cognitive difference. While there may be some small biological influences, socio-cultural factors contribute to the majority of the gender gap.

Word Count: 150

Table of Contents

Introduction 4Cognitive Explanations 4Spatial Skills 5Humanist Explanation 5Socio-Cultural Explanations 6Stereotype Threat 8Biological Explanation 9Conclusion 9Works Cited 10

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Introduction

One of the best advantages for a country to have is the ability to innovate. As the world becomes more connected and markets grow and unify, global competition increases. In order to compete, nations need to be properly equipped with innovation’s most important tool: math. However, females are greatly underrepresented in math-heavy fields and in the top-tiers of mathematical education. While psychology is past the days where Nietzsche’s comment, "When a woman becomes a scholar, there is usually something wrong with her sexual organs," is believed to be true, the evidence cannot be denied that there are more men than women in mathematical fields. While researchers agree that women and men are capable of equal mathematics achievement, psychologists vary in their explanations for the disparity between male and female mathematics achievement. The goal of this paper is to explain and evaluate various explanations for the gender gap in mathematics through different fields of psychology.

Cognitive Explanations

To begin with, cognitive differences between males and females may lead to a difference in mathematical intelligence. The cognitive processes men and women use to do math at a young age may impact their overall abilities. Males, on average, are more likely to take risks. Pinker says, “We see this sex difference in everyday life, in particular, in the following category: the Darwin Awards, ‘commemorating those individuals who ensure the long-term survival of our species by removing themselves from the gene pool in a sublimely idiotic fashion.’ Virtually all — perhaps all — of the winners are men.” Because young boys are more impulsive than girls, they rely less on finger-counting and other manipulatives to get the right answer, and instead will rely on memory or guessing to answer simple math problems. Contrarily, girls want to be accurate and will use manipulatives, such as finger-counting, which slows them down and makes it harder for them to learn advanced concepts (Azar). This difference in strategies is also contributed to by competitiveness. Because males are more competitive, the amount of risks they take increases when doing tasks in groups (Freeman). This difference in cognitive processes may cause a difference in mathematical intelligence between males and females.

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Steven Pinker goes as far as to suggest that while girls are better at mathematical computation, guys are better at mathematical reasoning, such as word problems and practical application. This idea is supported by much research. An increased mathematical reasoning ability would allow males to succeed in fields where the application of math is heavily used such as engineering and technology. Pinker uses the meta-analysis of Hyde, Fennema, and Lamon (1990) to support the idea that women are better at computation, and the fact that males typically get higher scores on the SAT Math portion to illustrate the male advantage in mathematical reasoning. However, CollegeBoard’s Total Group Profile Report highlights the fact that participants in the SAT are self-selected (2). Eliot brings this up when she says that more females than males from underprivileged families take the SAT, and because of that, many of the lowest levels of males are weeded out and the averages are skewed. Though this seems like a reasonable explanation for the variance in scores, the CollegeBoard contradicts this. While 53 percent of the graduating seniors that took the SAT were female (5), 62 percent of the math scores between 700 and 800 were received by males (6). These numbers indicate that there are more males at the top, although there were more females to take the test in general. If males and females were achieving the same levels in math as Eliot suggests, there would be equal numbers of males and females in every bracket, except where the lowest levels of males should be. Therefore, this evidence contradicts Eliot’s claim and supports Pinker’s belief that girls are better at mathematical computation while guys are better at mathematical reasoning, explaining the absence of females in math heavy careers.

Spatial Skills

Furthermore, there are many cognitive differences in male spatial abilities that may contribute to the difference in mathematics intelligence between males and females (Eliot). According to Niederle, “boys have and develop superior spatial skills and … this gives them an advantage in math” (130). Eliot provides much evidence for the idea that men have better spatial skills than women. She refers to the idea that men have a smaller rate of car accidents than women, with the exception of teenagers, and the idea that young boys begin to pass Piaget’s water level test, a test that requires participants to draw the water level line in a tilted cup, earlier than young girls do. There are many explanations for the increased spatial abilities present in males. One theory suggests that male spatial ability is evolutionary in nature, resulting from the need of spatial abilities for hunting and other masculine tasks (Gaulin and Hoffman, 1988). However, Eliot argues against this idea, with the idea that evolution does not remove hereditary traits unless they are harmful, as seen with male nipples, and thus evolution would also give women their father’s increased spatial skills. Another explanation is the idea that male play encourages and teaches spatial skills that female play does not (Berenbaum, Martin, Hanish, Briggs, and Fabes, 2008; Eliot). This idea is more likely, as Eliot presents many examples where women are given typical male hobbies to engage in, such as video games, sports, or Legos, and their spatial abilities go up accordingly. Likewise, Gutbezahl argues that parents treat boys and girls differently from birth; boys get toys that enhance spatial ability while girls are engaged in conversation. Because of these ideas, spatial skills can be classified as being a socio-culturally formed cognitive explanation for gender differences in mathematics intelligence. Thus, male spatial skills offer reasons for the mathematics intelligence differences with cognitive and socio-cultural explanations as opposed to just spatial reasons.

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However, the question of whether or not spatial skills actually influences mathematic ability still remains. According to Gutbezahl, “Spatial ability is an important component of math skills and facilitates comprehension of abstract mathematical concepts used in geometry, trigonometry and calculus.” Likewise, both Spelke and Pinker believe spatial skills play a role in mathematics intelligence. Pinker states that “mental manipulation of objects in three dimensions figures prominently in the memoirs and introspections of most creative physicists and chemists, including Faraday, Maxwell, Tesla, Kéekulé, and Lawrence, all of whom claim to have hit upon their discoveries by dynamic visual imagery and only later set them down in equations.” Thus, it can be assumed that spatial skills do play some role in mathematics ability.

Humanist Explanation

It is also important to note how humanism may play a role in this issue. The humanist argument suggests that humans are inherently good. Humanists further argue that everyone wants to achieve their potential. However, men and women have differing priorities in life; while men aim more for status and success, women search more for fulfillment in their relationships (Pinker). Pinker adds that women and men differ in interest in people vs. interest in abstract ideas and things. He discusses the idea that men are attracted to things, which attracts them to occupations such as “physicist, chemist, mathematician, computer programmer, and biologist,” while women are interested in people, which attracts them to occupations in service or in teaching. Pinker supports this idea by highlighting the fact that “among the Ph.Ds awarded in 2001, for example, in education 65% of the doctorates went to women; in the social sciences, 54%; in the life sciences, 47%; in the physical sciences, 26%; in engineering, 17%.” Eastham furthers humanist concepts with the idea that guys will avoid areas they are not strong in and will instead spend as much time as they can in areas that they excel in (12); he suggest this comes from the male tendency to compartmentalize (10). These hypotheses help to explain the large amount of men in math-heavy fields.

Socio-Cultural Explanations

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Hoffman enters the age old nature versus nurture debate with his 2011 study. In this study, Hoffman claims that there is a cultural explanation for the gender differences in spatial ability. To do this, he finds a situation in which biological factors are held constant while culture is manipulated. This scenario is found in Northeast India, with the Karbi, a patrilineal society, and the Khasi, matrilineal society. Both groups share a genetic background; they split up only 100 years ago, and they still intermarry enough that their genes would not have separated. Hoffman offered a monetary reward to attract his 1600 participants in the study. He tested spatial ability with a 4 piece puzzle. He found that in the Karbi society, the men solved the puzzle 1.5 times faster than the women. However, in the Khasi society, men and women solved the puzzle at about the same speed. Hoffman concludes with, “These results show that nurture plays an important role in the gender gap in spatial abilities.” Alas, Bailey presents many methodological flaws in this experiment. Bailey says that, “Unfortunately, their conclusion is undermined by major problems with their measures of spatial ability and sex equality.” Bailey highlights with the spatial task they used, “sex differences on this task are extremely small.” He states that if Hoffman wanted to study gender differences in spatial ability, he should have used a task that was more sensitive to the role of gender. Likewise, Bailey points out that there was no control task. Bailey says that because they used such a gender-equivalent task, there was no way to know if gender actually caused the difference they saw, or if some other factor, such as education, contributed to the difference. However, it is important to note that Hoffman’s study aimed to identify that the differences have some basis in cultural. In order for him to show that, all he has to do is prove that they are not entirely biological. The study succeeded at this task, because Hoffman was able to control biology and still found a gap. Bailey’s final complaint, however, is valid. He states that the ideas of matrilineal and patrilineal were not well defined, and don’t directly correlate with gender equality. While Hoffman decided that the matrilineal society is egalitarian in regards to gender, it is important to note that the matrilineal society could be biased towards women, and in that regard, the gender gaps wouldn’t correlate, and it would force a biological cause of the gender gap. Regardless, Hoffman’s study does serve to show that there must be some socio-cultural influence in the mathematics gender gap.

The socio-cultural explanations appear more accurate when the process of learning math is considered. Mathematician Keith Devlin, Executive Director of the Center for the Study of Language and Information at Stanford University, explains, in his article, “How do we learn math?” how math, like any other skill, is performed first, and through that performance, understood. This theory on learning mathematics presents a vicious cycle. Math will not be performed unless it is understood, but math will not be understood unless it is performed. Devlin suggests, in his book, The Math Gene, that younger females may not be doing as well in math as males because they do math less often (275). Many socio-cultural explanations are supported by Devlin’s theories.

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There are many possible socio-cultural explanations for the gender differences in mathematics intelligence. Azar’s article says that, “One factor inhibiting girls is self-confidence,’ says University of Wisconsin psychologist Janet Hyde, PhD. ‘Even when girls are getting better grades, boys are more confident in math.” One reason Azar gives for this is the fact that education majors are generally girls, and they are the most likely major to have math anxiety. Thus, by the time a girl reaches middle school, she’s been influenced by all of her teachers, mostly female, to be afraid of math, while males do not feel as strong an influence from their female teachers. Beilock confirms this with her 2009 study. In this study, Beilock assessed the math anxiety of 17 1st- and 2nd-grade female teachers, as well as the mathematics achievements of their students and the extent to which their students adhered to traditional academic stereotypes. At the beginning of the year, before the teachers formed relationships with the students, there were no correlations between the teacher’s math anxieties and the mathematics abilities of the students or the students’ belief in traditional gender roles. However, at the end of the school year, Beilock found that the higher a teacher’s math anxiety, the lower the girls’, but not the boys’, mathematics achievement. This study is a good example of social learning theory. Bandura‘s original study on social learning theory supports Beilock’s study. Like in Bandura’s study, participants adopted the behavior of a model that shared their gender, and were less likely to gain the behavior from models of the opposite gender. Unfortunately, Beilock’s study failed to see if anxieties could be learned by males as well as females, if a male teacher were used, so the social learning is not fully confirmed for this scenario. However, the self-confidence theory gains credibility when looking through Devlin’s theory of learning mathematics. Girls with math anxiety are less likely to do math, then fail to get understanding. Thus, they’d fall into the vicious cycle by increasing their math anxiety through their lack of understanding and their lack of understanding through their anxiety. Without the proper confidence levels, women are likely to drop math and science courses and careers.

This is just one of the reasons Azar presents as to why girls may drop math and science; she also says that, “girls are more attracted to a variety of careers because they tend to have both strong math and verbal skills.” She suggests that while men that can do math well will identify themselves as mathematicians and scientists, women that can do math can also use their verbal skills in other areas, and are less likely than men to stay in math and science. Because of the many socio-cultural reasons that encourage girls to leave math and science, females don’t develop the mathematics intelligence that males do.

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Likewise, new research now suggests that a woman’s culturally programmed urge to be romantically desirable may keep her out of the stem fields. Park et al. found that for women, romantic goals decrease interest in STEM fields but raise interest in feminine domains such as English, languages, and arts (1270). Park’s first study consisted of priming males and females to have various goals, such as romantic, academic, or friendship through the use of pictures. Then she used surveys to collect opinions on various subjects. The second studies did the same, but this time the priming was done through the use of scripted conversation. The final study was more explicit. Rather than priming, Park had participants take a short survey every night asking about their goals and activities that day for 21 days. The three experiments all lent to the same conclusion. The idea is that women are culturally led to believe that being desirable comes from being feminine, and that things such as leadership, math-heavy fields, and higher education are more masculine. “Overall, these findings are consistent with the idea that women experience conflict between wanting to be romantically desirable and wanting to be intelligent in the male-stereotyped domains of STEM (1271).”

Stereotype Threat

The most popular theory given for the difference in mathematics achievement is the stereotype threat. This is the idea that the presentation of a negative stereotype will negatively influence performances due to the creation of anxiety. In regards to the gender gap, stereotype theory states that girls, when presented with the idea that girls are worse at math than boys, will become anxious and fail to do as well as boys on the same test. Many psychologists consider the stereotype threat from a long-term perspective; the stereotype threat continues to impact girls as they go through math classes and slowly deteriorates their performance. For example, Beilock’s 2009 study can be explained using the idea of the stereotype threat. Beilock found that, along with mathematics achievement, the math anxiety of female elementary school teachers affects the amount that young girls ascribe to the stereotypical idea of “boys are good at math, girls are good at reading.” Beilock goes as far as to say “girls who endorsed this stereotype had significantly worse math achievement than girls who did not.”

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Of course, in order for the stereotype threat to have an effect the stereotype has to come from somewhere. The idea that females perform math at a lower level than males permeates all of society. In 1992, the Teen Talk Barbie Doll was released by Mattel. She had the ability to say four random phrases from a bank of 270 possible phrases, one of which was “math class is tough,” a harmful phrase for young girls to ascribe to (New York Times). Gutbezahl argues that the stereotypes that harm girls’ mathematics performance come from three main sources: their parents, their teachers, and themselves. Gutbezahl states that not only do parents attribute a girl’s success in math to hard work, as opposed to ability, but parents talk to young girls more than young boys while allowing young boys more freedom to explore and grow than young boys. This is significant because research has shown that experimenters’ expectations of an animal’s learning capabilities will affect the animal’s progress (Rosenthal and Fode; Rosenthal and Lawson). The study done by these researchers can be generalized to small children as well. Along with the effect had by parents on female students, the expectations held by teachers negatively impact a girl’s mathematics performance. “Teachers expect less academically from girls than from boys and treat girls quite differently from the way boys are treated (Gutbezahl).” Gutbezahl points out that when girls succeed, teachers compliment the girls’ hard work as opposed to their abilities, while teachers attribute the girls’ failures to lack of ability. The opposite is true of male students. When boys succeed, their success is attributed to their abilities, while their failures are attributed to lack of effort (Gutbezahl).

The stereotype threat gains further credibility when compared to Azar’s theory on math anxiety. The stereotype threat has been shown to create anxiety in many different arenas, while Beilock’s study on math anxiety has shown how anxiety can lead to poorer performance by females. Likewise, Devlin’s theory on learning mathematics supports the theory of stereotype threat. If girls believe negative stereotypes, they will be more likely to attribute their understanding to their gender, as opposed to a lack of understanding. This belief would cause them an anxiety fueled by hopelessness, forcing them into the vicious cycle as they actively avoid math, and consequently never gain understanding of mathematics.

Biological Explanation

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Though Eliot suggests that there are no biological factors for increased male spatial ability, Pinker argues that while there may not be a 100 percent biological basis for the gender difference, he says that, “The only issue is whether the contribution of biology is greater than zero.” He continues with the idea that there are many biological differences between the genders, including hormones, brain size, and the degree of cortical asymmetry. The idea is that with so many possible areas for variations, the probability that there is some sort of variation goes up. He furthers that there must be a biological basis for gender differences because many gender specific traits are cross-cultural. “Israeli kibbutz, various American Utopian communes a century ago, and contemporary androgynous academic couples” are all examples of societies that tried to remove gender differences and failed. However, Hoffman’s Karbi vs. Khasi study shows that the biological factors have little influence, if any at all. Pinker goes on to point out that there are also gender differences in other mammals that mirror many differences in humans. Rhoads suggests that there are biological influences to spatial skills through the difference between the male tendency for compartmentalizing and the female tendency for networking (28). Keith Devlin brings up the idea that no one is designed to do math. “The human brain evolved into its present state long before mathematics came onto the scene, and did so primarily to negotiate and survive in the physical world. As a consequence, our brains do not find it easy to understand mathematical concepts, which are completely abstract (Devlin “How we learn…”).” He also states that anyone can learn math if when proper interest is there, comparing success in mathematics to success in a marathon (The Math Gene 275), implying that there are no biological factors. However, Devlin’s example is flawed, because even in a marathon there are slight genetic advantages and disadvantages present. Therefore, it can be concluded, that while there may not be strong biological influences, some biological influences must exist.

Conclusion

In conclusion, mathematics is a cognitive process, and because of such, there must be some cognitive differences that influence the gender differences in mathematics performance. Really, the question is from where these variations in cognition stem. While evolution presents many arguments for the creation of a biological spatial advantage for males, the connection between spatial skills and mathematical ability is still questionable. Furthermore, biological influence on mathematics will be small, if there is any at all. Socio-cultural explanations appear to be much stronger, especially when considered with Devlin’s theory on learning mathematics. Humanist explanations are strong on their own, but pale in comparison to socio-cultural explanations. Therefore, it can be concluded that the primary reason for the gender gap in mathematics performance is socio-cultural factors that contribute to a girl’s avoidance of math.

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Works Cited

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Berenbaum, Sheri A., Carol Lynn Martin, Laura D. Hanish, Phillip T. Briggs, and Richard A. Fabes. 2008. “Sex Differences in Children’s Play.” Chap. 14 in Sex Differences in the Brain: From Genes to Behavior, ed. J. B. Becker, K. J. Berkley, N. Geary, E. Hampson, J. Herman, and E. Young. New York: Oxford University Press.

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Hoffman, Moshe, Uri Gneezy, and John A. List. "Nurture affects gender differences in spatial abilities." Proceedings of the National Academy of Sciences 108.36 (2011): 14786-14788.

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Hyde, Janet S., Elizabeth Fennema, and Susan J. Lamon. "Gender differences in mathematics performance: a meta-analysis." Psychological bulletin 107.2 (1990): 139.

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