Pink Diplomas: Gender Bias in Upper-Division Math and Science

By Amanda Bertsch

This essay was written for Tri-City Prep’s Math Honors class, which asks students each spring to write a paper on a topic in mathematics.

“What are you even doing here? You belong in the kitchen, barefoot and pregnant.”

These are the words that greeted Eileen Bertsch when she went to ask her calculus TA a question. Shocked, she didn’t respond, walking away without the answer to her query (Bertsch). The year was 1980.

Almost a century after the first women graduated from engineering programs, she was facing some of the same blunt rejection that these pioneering women engineers struggled through. As a freshman in college, she was hearing the same sexist rhetoric that had persisted for decades, still as sharply obvious as ever. Her calculus TA, while a particularly blatant example of why women are underrepresented in engineering, was only one of a series of challenges she and her sister Patricia Haslach would face as they earned engineering degrees.

“You will never be an engineer,” Haslach’s high school physics teacher told her after she struggled in his class. Her uncle told her the same thing when she enrolled in college (Haslach).  When Bertsch began her career in software engineering, she worked for a boss who would only acknowledge comments made by his male employees. When her friend Sylvia Laukshtein told their boss an idea wouldn’t work, he told her to “shut up and get with the team;” when the idea was implemented and failed miserably, he threw a table at her head (Bertsch). Meanwhile, Haslach saw her boyfriend completely deny her assistance in getting him a job at the chemical engineering company she worked at. He was embarrassed, it seemed, to be helped by a woman (Haslach).

To understand where this aggravated sexism in engineering originates, one must begin where the first differences in the performance of female and male students occur. For mathematics, this period is the spring semester of kindergarten. An American Educational Research Association study found that girls and boys showed equal mathematical abilities when they entered kindergarten, but by the spring, there were significantly more boys than girls in the highest achieving group of students (Gholipour). Not only that, but their data was comparable for a group of kindergarteners in 1998 and a group from 2010 (Gholipour). In those twelve years, there was no improvement in the gender disparity. Female students start to fall behind before they advance past arithmetic, and all the evidence suggests that teachers are to blame.

Implicit bias is difficult to quantify because the biased party is typically not aware of their own prejudice. Most elementary school teachers are female, but that doesn’t mean they aren’t negatively influencing female students (Gholipour). In fact, some studies suggest that female elementary school teachers who dread math are much more likely to pass this distaste to their female students, perhaps because these students view female teachers as role models (Gholipour). The idea that men are better than women at math is pervasive – a study showed that kindergarten teachers consistently rated their female students as lower achieving than male student with the same scores on a Department of Education test that the teachers are not aware of (Gholipour). In comparing male and female students as a whole, teachers would never display these biases; however, comparing ratings of specific students reveals a pattern of unconscious bias.

This bias continues far past kindergarten. A study in Israel revealed that female sixth-grade students scored significantly better than their male peers on anonymously-graded math and science tests, but significantly worse when the grader knew the gender of the student (Miller). The effect could not be replicated on tests in other subjects, suggesting that this data is linked to a gender bias in science and math (Miller “How”). This is important because the same study found that the students who received less encouragement in these fields in middle school (i.e. the female students) were less likely to choose advanced courses in high school (Miller “How”). The effect was notably smaller in households where the student’s mother was in a highly technical math or science field, like engineering (Miller “How”). However, for the many students that don’t have this privilege, discouragement by unconsciously biased teachers can have life-long effects.

Between high school and college, these small slights begin to have real impacts. Just 18.5% of the students who take the Advanced Placement computer science exam are female, and a mere 12% of computer science degrees are earned by women (Miller “How”). Women represent 55% of the collegiate population and 48% of the workforce, but hold only 24% of STEM (science, technology, engineering and math) jobs (Beede). One survey of science professors found that, when presented with identical candidates, professors whose survey reflected a male applicant were more likely to offer the applicant mentoring or a job. When they did offer the female applicant a job, it was for an average of $4,000 less pay (Chang). This could be one reason that less than a fifth of technical employees at Google, Facebook, and Apple are female (Miller “How”).

With this understanding of the problem, one can begin to consider solutions. Toys typically marketed toward boys, such as Legos, Transformers, and marble runs, help children develop spatial skills and interest in engineering, while dolls and dress-up have little effect on mathematical development. Toy startup GoldieBlox aims to market engineering- and discovery-based toys to young girls in an effort to even this gap (Miller “Ad”). Female students are often uncomfortable asking for help in predominately male engineering tutoring centers, so a program at Rutgers in the early 1980s saw women volunteer to tutor other women (Bertsch). Because of the powerful effects of something called self-efficacy, teachers can improve female students’ performance simply by assuming they are just as capable as their male counterparts (Dano). In the end, all of these solutions come back to the same thing: accelerating a cultural shift in the bias against women in STEM careers.

Gradually, things are getting better for women in male-dominated fields. Eileen Bertsch believes she saw this first-hand in her years teaching discrete math and computer science at a community college. “I know people want things to be perfect right away,” she says, but her students were “much nicer people” than the men she encountered when she was earning her degrees (Bertsch). However, being aware of implicit gender biases in these fields is the first step to creating a culture where women have just as many opportunities to succeed in math as men do. Right now, men are being rewarded for putting in the same amount of work as women who were discouraged from pursuing math-related careers. That just doesn’t add up.



Works Cited

Beede, David, Tiffany Julian, et al. “Women in STEM: A Gender Gap to Innovation.” US Department of Commerce, August 2011. Accessed 19 March 2017.

Bertsch, Eileen. Personal Interview. 13 March 2017.

Chang, Kenneth. “Bias Persists for Women of Science, a Study Finds.” The New York Times, 24 September 2012, Accessed 16 March 2017.

Dano, Rubee. “Tackling the Gender Bias in Mathematics Education.” Society and Education, 10 August 2015, Accessed 16 March 2017.

Gholipour, Bahar. “The Gender Gap in Math Starts in Kindergarten.” Huffington Post, 27 October 2016, Accessed 16 March 2017.

Haslach, Patricia. Personal Interview. 11 March 2017.

Miller, Claire Cain. “Ad Takes Off Online: Less Doll, More Awl.” The New York Times, 20 November 2013, Accessed 19 March 2017.

Miller, Claire Cain. “How Elementary School Teachers’ Biases Can Discourage Girls From Math and Science.” The New York Times, 6 February 2015, Accessed 16 March 2017.