Aren’t we over this?
(Retrieved from https://xkcd.com/)
The first unsettled question is whether females are still underperforming in mathematics today. Hasn’t it diminished due to a more inclusive and equitable society? Or isn’t it a quite negligible issue?
Well, if we only focused on students’ maths test scores, there would be no discernible gender differences in that aspect. And apart from girls’ slightly lower scores in standardized tests, they had consistently outperformed their male counterparts in maths grades from elementary schools to tertiary education in recent years (Ceci, Williams, & Barnett, 2009). However, if we probe deeper, the situation would appear differently.
Although boys and girls achieved similar mean scores, the two genders performed differently in different maths topics. For example, boys have performed consistently better at spatial reasoning and solving word problems and are more likely to use maths knowledge in their real lives (Ceci et al., 2009). What worth noting is that the spatial reasoning ability is not only related to students learning geometry, but also strongly related to students’ overall maths performance and confidence (Casey, 1996). Likewise, lack of practical application may also lead to a low learning motivation and ultimately unsatisfying learning outcomes.
And if we have a look at the right tail of the maths test score distributions, we can detect noticeable gender disparities too. Benbow and Stanley (1980, 1983, as cited in Wai et al., 2010) showed an astonishing 13 to 1 male-female ratio of those who achieved top 0.01% in SAT-M in the early 1980s. Although this ratio has dropped remarkably afterwards, it has remained stable at roughly 3.8 to 1 between 1991 and 2010 in the USA SAT-M top achievers (Wai et al., 2010). This right tail advantage emerged in preschool years and continued all the way to adulthood, and became more distinct if the maths test was designed more difficult (Benbow, 1992, as cited in Ceci et al., 2009). In sum, this gender disparity at the right tail was significant and consistent.
In sum, at the average level, males still outperformed females in spatial reasoning and maths application. At the right tail of their maths score distributions, males still outnumbered females for the last two decades. And in terms of personal attitudes, males showed greater enthusiasm in mathematics and maths-related jobs than females (Ceci et al., 2009). Therefore, females’ underperformance in mathematics is still a fact. So the next questions are what are the mechanisms behind this phenomenon and what should maths educators do?
Extraneous factors: nature vs. nurture
It may sound politically incorrect, but the biologic and neurologic perspectives do shed some light on the gender differences in maths learning. Plenty of research has been conducted on this topic (Eliot, 2013; Haier et al., 2005; Ceci, Williams, & Barnett, 2009). So far two main differences have been detected between males’ and females’ brains: males’ brains are generally larger than females’ brains by 8 to 14% (Paus 2010, as cited in Eliot, 2013) and males have undoubtedly higher white matter-gray matter ratios than females (Cosgrove et al., 2007, as cited in Eliot, 2013). Plus, though the two genders showed little difference in average IQ scores, neuroscientists found that they achieved the same results through absolutely different neural activations. The brain imaging showed different activated brain areas between two genders in solving mental rotation problems (Haier et al., 2005). Albeit these brain and neural differences, the exact mechanisms have not been unveiled yet. These undeniable facts do suggest some reasons for the gender differences in maths learning, BUT they are far from the whole story.
The socio-cultural context has a bigger part to play. Here is an interesting research done by Guiso and his colleagues in 2008. They analyzed 2003 PISA (Programme for International Student Assessment) maths scores of students from 40 countries: the gender gaps of their mean maths scores varied enormously, with some countries having huge advances in males, some of a negligible disparity, and some of a reverse gender gap. Then they used the World Economic Forum’s Gender Gap Index (GGI) to assess each country’s gender equality and found the correlation between the two variables was .27 (p<0.01). In order to eliminate the possible genetic influences, they repeated the analysis within a subset of 26 European countries that shared similar evolutionary processes. The correlation coefficient was .31 (p<0.01), still statistically significant! The gender equality in one society was significantly related to the gender gap in students’ maths test performance.
Guiso et al. (2008) then selected 13 genetically homogenous countries: Australia, Belgium, Canada, France, Iceland, Ireland, Luxembourg, New Zealand, Poland, Spain, U.S.A., U.K., and Uruguay. He then assumed that the biologic factors couldn’t account for a greater difference in maths scores than that in Australia (6 points with boys outperforming girls), where both genders are well supported and equally treated. Then compared with Australia, Luxembourg had a greater gender gap by 11 points and Iceland overcame and reversed the gap by 16 points. Either the 11-point loss or the 16-point gain could only be accounted to the broad contexts. Hence, we can say the macro-level social-cultural contexts, including gender equality and many other components, played a vital role in the gender disparity of students’ maths performance.
Penner (2008) concluded brilliantly in his paper that there is an upper bound to the biologic influences but just a lower bound to the environmental effects.
Intrinsic factors: Achievement vs. Identity
So what about the intrinsic factors influencing females’ maths performance? Achievements such as maths grades are critical to individual’s learning opportunities and self-confidence. Likewise, a student’s identity is also pivotal to her motivation of maths learning. Compared with students’ achievements, their identities have been found more influential in terms of maths performance.
During the last two decades, females have narrowed and even overcome the gender gaps in school grades and standardized test scores. But compared with their male counterparts, females still showed less confidence in maths learning, less early-commitment to maths intensive fields and less representation in these fields when they grew up (Ceci et al., 2009). This sharp contrast between females’ high performance and underrepresentation in maths could be stemmed from their gender identities. But what are these identities in terms of maths learning?
Well, firstly, girls are vulnerable to the stereotype threats in maths. They are always depicted as more self-regulated learners than boys, but they themselves may interpret this as being “less talented”, and expecting their male classmates to be the maths experts (Lohman & Lakin, 2009). And the women’s underrepresentation in the maths world may also confirm this self-perception.
Secondly, females are generally more interested in people and personal relationships while males in things and their mechanism (Su, Rounds, & Armstrong, 2009). Young women may lose their interest in maths when they fail to find its relevance to their lives (Catsambis, 1995). Moreover, during puberty, females’ fear of awkwardness stops them from speaking up in class or outsmarting their peers, which results in less participation in maths class (Koch, 2003).
Last, females’ gender roles in human society also drive them away from excelling at mathematics (Ceci et al., 2009). Since most mathematics-intensive jobs are time demanding, females may find it unsuitable for their lifestyles when they get married or become mothers.
Compensating sex vs. assisting individuals
There are two ways to help females fulfilling their potentials in mathematics: to compensate sex or to assist individuals. As mentioned above, females and males have different biologic bases, hold different self-perceptions of and attitudes towards mathematics learning. Considering these gender differences, educators should still provide sex compensation in maths class. Here are some educational implications in terms of facilitating girls’ maths learning.
First, early childhood education is critical to females’ later maths learning. Because individual interests are formed at an early age, parents and caregivers can give their little girls accesses to sand tables, Lego, crafts and computers and encourage them to explore with courage and confidence (Koch, 2003). These interventions do not necessarily swift girls’ interests from people and relationships to matters and mechanisms, but hopefully may remove some limitations from them at their formative ages (Su, Rounds, & Armstrong, 2009).
Second, different teaching approaches can be taken to cultivate females’ spatial abilities and mathematical strategies. Since girls have underperformed in these aspects independently of their ages and cohorts, I may suggest that compensating practices are needed in these aspects. Feasible approaches, such as playing video games, have been deeply discussed in Casey’s (1996) research. Moreover, since girls usually do not buy in the usefulness of maths, teachers can include more mathematical knowledge application contents in class so as to foster girls’ interest and facilitate their learning.
Third, most secondary girls are reluctant to ask questions or speak up in class before authentic relationships have been built up between teachers and students. Encouraging and caring classroom environments are essential to girls’ active participation and effective maths learning. Teachers need to let these young ladies feel safe to make mistakes in maths class (Koch, 2003).
Lastly, teachers and parents could encourage their girls to be open-minded in terms of maths learning. Mathematics abilities and female identity are not mutually exclusive. There are more and more female role models in math realm who have shown their talents in maths and have used maths to help people. If only maths teachers can help their girl students see that maths is relevant and creative, and show them that it is plausible to be an interesting person, and in the meantime, loving maths.
However, despite the distinctive differences between the two genders, the disparities within gender groups are even greater (Gottfredson, 2002). Su, Rounds, and Armstrong (2009) found the variances of intra-gender mathematics scores were about four times larger than that of inter-gender scores, which implies the importance of assisting individuals. Specifically, some girls can be equal to or even better than boys in spatial abilities while some boys may be more sensitive to people and relationships than girls. In order to balance the sex compensation and individual assistance, teachers and parents should be mindful of each child’s traits and attributes, and avoid the trap of stereotyping them by gender averages.
Conclusion
Gender difference in mathematics learning is still an important issue today. It results from the interactions of the innate biologic basis, the socio-cultural atmosphere, and the gender identities, with the latter two factors of more influences. However, gender difference is only one of the individual differences that lead to mathematics disparities. Any approaches to help girls in maths learning should be given with the full awareness of their individual varieties.
References:
Casey, M. B. (1996). Understanding Individual Differences in Spatial Ability within Females: A Nature/Nurture Interactionist Framework. Developmental Review, 16(3), 241-260.
Catsambis, S. (1995). Gender, race, ethnicity, and science education in the middle grades. Journal of Research in Science Teaching, 32(3), 243-257.
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation in science: socio-cultural and biological considerations. Psychological Bulletin, 135(2), 218.
Eliot, L. (2013). Single-sex education and the brain. Sex Roles, 69(7-8), 363-381.
Gottfredson, L. S. (2002). Assess and Assist Individuals, Not Sexes. Issues in Education, 8, 39-47.
Guiso, L., Monte, F., Sapienza, P., & Zingales, L. (2008). Culture, gender, and math. SCIENCE, 320(5880), 1164-1165.
Haier, R. J., Jung, R. E., Yeo, R. A., Head, K., & Alkire, M. T. (2005). The Neuroanatomy of general intelligence: sex matters. NeuroImage, 25(1), 320-327.
Koch, J. (2003). Gender Issues In the Classroom. In W.M. Reynolds, G.E. Miller, and I.B. Weiner (Eds.), Handbook of Psychology: Volume 7, Educational Psychology. Hoboken, NJ: Wiley.
Lohman, D. F., & Lakin, J. M. (2009). Consistencies in sex differences on the Cognitive Abilities Test across countries, grades, test forms, and cohorts. British Journal of Educational Psychology, 79(2), 389-407.
Penner, A. M. (2008). Gender Differences in Extreme Mathematical Achievement: An International Perspective on Biological and Social Factors1. AJS, 114, S138-S170.
Su, R., Rounds, J., & Armstrong, P. I. (2009). Men and Things, Women and People: A Meta-analysis of Sex Differences in Interests. Psychological Bulletin, 135(6), 859.
Wai, J., Cacchio, M., Putallaz, M., & Makel, M. C. (2010). Sex differences in the right tail of cognitive abilities: A 30year examination. Intelligence, 38(4), 412-423.
Maths for us 