Priya Sobti
Major: Computer Science
Thesis Advisor: Maggie Habeeb
Second Reader: Leandro Junes
HAB Member: Marta McClintock-Comeaux
Librarian: William Meloy
Keywords: Women, STEM, Gender, Science

Table of Contents:
I.
II.

III.

IV.
V.

Abstract
Introduction
a. Preliminary Statistics
b. Some Notable Women in STEM
i. Sally Ride
ii. Alice Ball
iii. Annie Easley
iv. Red Burns
v. Helen Greiner
vi. Esther Sans Takeuchi
vii. Edith Clarke
viii. Emily Warren Roebling
Modern Day Bias and Discrimination
a. High School
b. College
c. Workforce
d. Culture & Attitude
Moving Forward: Improvements and Suggestions
References

Section I: Abstract
This Honors Thesis is a research project on women in STEM fields and careers.
More specifically, it concerns the gender bias in STEM and how it affects women
currently in or wanting to pursue careers in those areas of study. This project will be
divided into three sections detailing the past, present, and future of women in STEM
fields, highlighting their struggles and achievements in adversity. A short section on
notable women contributors will be included in both the past and present sections of the
project.
By researching and analyzing past studies, surveys, and questionnaires this thesis
will demonstrate a better understanding on the imbalanced ratio between women and men
in STEM fields. This project will focus more in depth on American culture and research,
but supplementary information concerning other cultures and research will be included
when available. Statistical and empirical data as well as the aforementioned surveys and
questionnaires will be included.
At the end of the thesis, there will be some suggestions for encouraging women to
gain an interest or staying in STEM fields. I will include my thoughts on why current
methods aren’t as successful, along with some possible changes or improvements.
Additionally, I will suggest a few methods of my own for encouraging young girls to
pursue STEM careers.

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Section II: Introduction
Part A: Preliminary Statistics
The pinnacle of human achievement lies within our contributions to STEM fields.
STEM, an acronym standing for Science, Technology, Engineering, and Mathematics
(xiv Hill), contains a multitude of degrees of study and occupations that the public dubs,
‘the scientific' or ‘as part of the sciences’. However, it is common knowledge amongst
those with interests in STEM related topics that the ratio of women to men is greatly
unbalanced. According to statistics measured in 2013 to 2014, men have a majority in all
STEM related majors, where women do not even come close to reaching fifty percent
(Catalyst, 2016).
For example, across all United States bachelor’s degrees earned in STEM fields,
women accounted for only thirty-five-point one percent. This number slightly decreased
with master’s degrees at thirty-two-point seven, but increased slightly at the PhD level
with thirty-four-point four percent earned by women. The table below created by Catalyst
shows how degree levels and fields are broken down into ratios between female and male
students in the United States (Catalyst, 2016).

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Interestingly enough, the life sciences have gained a large female student
majority. As seen in the above table, more female students are earning degrees of all
levels in biological and biomedical sciences, all with numbers above fifty percent
(Catalyst, 2016).
Unfortunately, this issue carries on past graduation and into the workforce. Data
as recent as 2016 shows trends that at least half of the population in the United States is
female, but not even a third of those women are in science or engineering fields. The
statistics done in 2016 show only twenty nine percent of women are currently working in
either a science or engineering related field (National, 2017). The UNESCO Institute for
Statics also did a global study on the number of women in research and development. The
world map below breaks down the gap between women and men researchers (UNESCO).

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Many studies, questionnaires, surveys, and other methods of research have been
employed as to what causes these gaps in gender ratios relating to STEM careers and
education. But women are a large portion of the population responsible for contributions
to both previous and current accomplishments in STEM fields.
Without multiple women of various backgrounds and interests, even modern
society itself would not be where it is today concerning technology and modern
conveniences. Whether it is due to erasure or a preference for male coworker’s
achievements, many women have not received due credit or shares to fame for their own
work and contributions.
Part B: Some Notable Women in STEM
Amongst the group of notable women in STEM fields is Sally Ride, most
famously known for achieving the title as the first American woman in space (Grinter,
2000). She was preceded by two other women of the USSR space program, Valentina
Tereshkova in 1963 (Yaroslavl, 2010), then Svetlana Savitskaya just a year before in
1982 (Space, 2012). However, Ride’s work in NASA as a physicist and astronaut is not
without its own merits. At thirty-two years old, she holds the title for the youngest
American astronaut to have traveled into space (Grinter, 2000).
Despite her high qualifications and impressive educational background, media
attention was focused almost exclusively on her gender before her first space flight.
Questions asked by the media included:
•

How the upcoming expedition into space would affect Ride’s reproductive
organs.

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•

Questions regarding her emotional state when problems arise.

•

If Ride had planned to become a mother.
Naturally, despite Ride’s calm demeanor, it was evident she did not have much

tolerance for these frivolous questions, as eventually she started asking why her male
coworkers were not also being questioned on their emotional responses when things go
wrong. When asked if she was going to become a mother, she stated that she wasn’t
answering that question. Ride later reflected on this questioning by stating, “It may be too
bad that our society isn’t further along and that this is such a big deal,” (Ryan, 1983).
Ride, however, praised her parents for raising her to embrace things that were out
of their comfort zones, especially related to the sciences, “Anytime I wanted to pursue
something that they weren’t familiar with, that was not part of their lifestyle, they let me
go ahead and do it. Tennis was an example; so was going into science. I think they were
kind of glad when I went into the astronaut program, because that was something they
could understand. Astrophysics they had trouble with.” (Ryan 1983). Perhaps this
upbringing encouraged her to write several books about science to children, and to
encourage both girls and women into science related careers. She co-founded Sally Ride
Science in 2001, which led to the creation of many publications and programs relating to
the sciences for students, parents, and teachers alike (BP, 2015).
Another notable woman that contributed to STEM achievements, more
specifically, to chemistry, was Alice Ball. As the first woman and African American
woman to graduate from the University of Hawaii, Ball was on the path to developing
more effective treatments for leprosy. It started with her graduate research, where her
advisor gave her a research project concerning chaulmoogra oil extract and its effects on

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patients with Hansen disease. Ball’s method of using the chaulmoogra oil extract to treat
patients was extremely effective and remained the most effective method until the late
1940s.
Sadly, Ball never received proper credit for her work during her lifetime from the
medical world, having died only a year after working strenuously on her graduate
research. In fact, her own university cited the chemistry department’s chairman for Ball’s
accomplishments for several years after Ball’s death, only officially recognizing her in
the year 2000 (Jackson 2007).
Annie Easley is another distinguished African American woman involved in
STEM, more specifically, in NASA. Easley was a multi-talented woman who worked in
computer science, mathematics, and rocket science. Though she started off doing
calculations by hand working for NASA, she quickly adapted to the use of programming
languages like FORTRAN and SOAP. She never considered herself a pioneer, nor did
she ignore the reality of her situation. When discrimination arose, she resolved herself to
‘work around’ people that ‘would not work with her’ (Mills 2015).
Easley’s achievements include developing and implementing code that was
essential for the Centaur upper-stage rocket. Her work in developing the battery
technology for hybrid vehicles made the Centaur project possible, which included
analyzing the power technology and energy conversion systems. Furthermore, the success
of the Centaur project led to the launch of the Cassini spacecraft (Mills 2015).
Supplementing her work in programming and a degree in mathematics obtained
after returning to school, Easley dedicated herself to tutoring young students and reaching

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out to them about NASA’s work. She hoped to inspire many female students into
choosing STEM related careers later in their lives. Furthermore, she took on the role of
Equal Employment Opportunity counselor later in her career to avoid discrimination
issues regarding gender, race, and age (Mills 2015).
Red Burns, nicknamed the ‘godmother of Silicon Alley’, has also contributed
greatly to the technological aspects of STEM. Burns founded the Interactive
Telecommunications Program, a graduate program focusing on communication
technology, digital media, and multimedia, after many projects. One of these projects was
a two-way television system to allow senior citizens to interact with each other or ‘visit’
community areas (Martin 2013). Burns also worked on telecommunication apps, one of
which was a first field trial of Teletext. For her work as professor and chairwoman of the
ITP, Burns has received multiple awards and recognitions. A few include: Mayor of New
York's Award for Excellence in Science & Technology, Crain's 100 Most Influential
Women in Business in New York, and Crain's All-Stars Educator's Award (GirlGeeks).
Continuing with the technological aspects of STEM, Helen Greiner is another
famous woman well known for her work in robotics. Greiner had always been interested
in robotics and admitted to often taking her older brother’s radio-controlled cars. She had
also quickly claimed the family’s first personal computer—a TRS-80—as her own.
Greiner spent her spare time playing around with the machine and figuring out how to
control her toys with it. Her future career path was set in stone the moment she saw R2D2
on screen in 1977. Her initial excitement about artificial intelligence was subdued upon
learning it was simply a person in a costume, but it led to a declaration that one day, she
would build her own (Helen).

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Years later, Griener found herself attending Massachusetts Institute of
Technology studying robotics and artificial intelligence. There she also met friends and
future partners of her iRobot company. As the current president and cofounder of the
iRobot company, she has done plenty of work making robots more accessible.
Previously, she had been working robots specifically adapted towards military purposes,
but as technological costs have gone down, she expanded her work into civilian needs as
well (Helen).
Greiner’s first big contract from the government was for the Department of
Defense, who commissioned an underwater minesweeper to be designed. Ariel
Underwater was modeled after a ghost crab in order to use the actual creature’s sixlegged physiology to grasp the ocean floor and withstand the tides. The robot was not
only capable of detecting mines, but also placing explosives and retreating out of harm’s
way. It was the success of Ariel Underwater to cause the company to grow and adopt the
name iRobot (Helen).
iRobot was then approached by National Geographic to design and build a robot
that would explore the northern and southern shafts to the Queen’s chamber of the
pyramids of Giza in 2002. The aptly named Pyramid Rover was small but performed
well, utilizing tools specific to archaeology to give millions of television viewers a look
inside the sealed chamber (Helen).
In the same year, Griener finally achieved her goals to break into the consumer
market and provide everyday civilians with a robot of their own. A previous attempt to
partner with Hasbro with a robotic doll had minimal success due to pricing. However,
their next project, a small disc shaped robot that would help civilians clean their homes,

8

had a bigger impact. iRobot’s engineers had been working on the design for the Roomba
for twelve years, taking inspiration for the vacuum cleaner’s design from the horseshoe
crab. Countless hours of research into industrial cleaning paid off when the Roomba
became very well-known and popular (Helen).
Another woman famous for inventing is Esther Sans Takeuchi, who immigrated
with her parents to the United States during the second world war from Latvia. She
invented a silver vanadium oxide battery that is commonly used in defibrillators. Her
work on this battery led to receiving the award for top technological achievement at the
White House in 2009, along with multiple other awards and recognitions (Riga).
Takeuchi holds more than a hundred and forty-five patents, more than any other woman
in the country (USPTO Patent). Takeuchi, in the year 2011 was also inducted into the
National Inventors Hall of Fame and in the following year elected as a fellow into the
Electrochemical Society (BNL 2012).
On the subject of electricity, Edith Clarke was the first woman electrical engineer
and subsequently, the first professor of electrical engineering at the University of Texas.
Later on, in 1926 she became the first to present a paper to the American Institute of
Electrical Engineers, which discussed how the behavior of a certain mathematical
technique could model a power system. This power system could then be studied by
engineers for its longer transmission lines. This was the first of eighteen more technical
papers Clarke would publish. A paper Clarke co-authored received the National First
Paper Prize of the Year award, prompting her to write her own book, Circuit Analysis of
A-C Power Systems (Riddle 2016).

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Finally, another important woman engineer was Emily Warren Roebling, the first
woman field engineer. Initially, her father in law, John A. Roebling, had started a project
to construct a bridge over the east river in New York between Brooklyn and Manhattan.
She and her husband traveled to Europe to research the technical difficulties with the
project. Before construction on the project could begin, her father in law died of tetanus.
Soon after, her husband’s health began to fail due to working beneath the river’s surface.
As he was confined to his sickroom, Washington Roebling feared he would die from
decompression sickness before the project would be completed (ASCE).
Since her father in law had died and her husband was bed-ridden, Emily Roebling
took on the work of completing what would be the Brooklyn Bridge. Roebling took the
initiative to do her own studies on the technical aspects of the bridge, strength of
materials, cable construction, and other important details. She was noted to be on the site
of the construction every day to deliver instructions and answer questions. In the end, it
was Emily Roebling who rode with the president across the bridge when it was opened in
1883 (ASCE). With all these great women contributors to stem fields, why is there such a
large statistical gap of women entering stem majors and working in stem fields?

Section III: Modern Day Bias and Discrimination
Part A: High School
Numerous studies have been conducted on that very subject, and the data from
that research shows that problems begin to arise as early as middle school for students.
Issues concerning female students and their confidence towards STEM subjects only

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increase further in their education. The lack of confidence in turn becomes a hindrance to
students, who would rather give up and avoid tasks involving scientific or mathematical
skills and knowledge (22 Hill). One may assume that female students are not pursuing
STEM related careers or taking STEM courses in their secondary and tertiary education
because skills are lacking. After all, Hill et al state that, “A belief that one can succeed in
a STEM field is important but is not the only factor in establishing interest in a STEM
career” (22 Hill).
However, research conducted by the US Department of Statistics examined high
school students, male and female, from 1990 to 2005. Female high school students were
not only taking more science and math credits as their male counterparts, but also were
outperforming them in terms of grade point average as well. The gap between
performance has been narrowed, according to Hill et al (4 Hill). Yet, when it came to
pressuring tests such as the SAT or ACT, male students still held a slight advantage in
results over their peers. Less female students were also opting to take STEM related AP
tests. Female high school students who did choose to take STEM AP tests also typically
performed below average of their peers (5 Hill). Therefore, while it seems in recent years
that more female students are taking interest in STEM courses, the gap still exists when it
comes to test results.
Research done by Else-Quest in a questionnaire involving several tenth-grade
high school students in the Philadelphia area further suggests that attitude of female and
male students affect their attitude towards STEM subjects. Data from the questionnaire
included queries about the individual’s ‘self-concept of ability’. Meaning, each student
was asked questions such as how proficient they believed themselves to be at math and

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science, and to rank themselves amongst their classmates. Furthermore, students were
also asked about ‘task value’, or how important it was for them to learn about math and
science, or how interested they were in those subjects. Next, the participants were asked
about their perceived success in a mathematic or scientific field, and how well they
expected to perform in their next math and science courses. Finally, at the end of the
spring semester, the science and math grades of the participants were analyzed (298 ElseQuest).
Else-Quest et al, upon analyzing all data from the questionnaire and the
participant’s math and science grades, stated that, “Our data indicate that male
adolescents continue to report higher self-concept and greater expectations for success in
math and science than female adolescents do, as predicted by the theoretical models
described earlier, whereas female adolescents report greater science value than male
adolescents do” (301 Else-Quest).
Part B: College
According to Hill, matters begin to decline further upon high school graduation.
Hill states, “The transition between high school and college is a critical moment when
many young women turn away from a STEM career path” (5 Hill). Hill et al also propose
that the way degree programs are ran could be having a negative effect on drawing in
female prospective students into their programs. For example, most computer science
programs focus on the programming aspects earlier on, learning coding skills and
programming languages before tackling theory. This in turn, would intimidate both
female and male prospective students and become a deterrent, especially for female
students (60 Hill).

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However, that gap between male and female performance results on tests does not
necessarily point one gender having an inherent advantage over the other. Human beings
after all, are not machines that can be expected to perform in the exact same way under
the exact same conditions day in and day out. Circumstances outside of the student’s skill
set and knowledge, such as their emotional state, are just as likely to affect test scores.
A study done by Spencer et al, showed that even being previously aware of the
stereotype of women having less skill in math affects performance on tests. This was
referred to as stereotype threat. Stereotype threat was hypothesized to be causing anxiety
in the women taking the tests (5 Spencer). The study was conducted a total of three
times. First, testing the hypothesis that men and women would perform equally on ‘easy’
tests, but not on more difficult ones. The more difficult test had questions involving
advanced mathematics such as advanced calculus in addition to abstract algebra. The
easier test entailed questions from standard geometry, trigonometry, and algebra within
the scope of the participant’s skills. Questions were displayed on a computer that gave
participants the option of skipping the question, answering it, or leaving it blank, all
while recording how long it took to submit a response (8 Spencer).
The results of this study showed that men and women performed equally well on
the easy test, but women did worse on the more difficult test. Spencer et al decided in the
next study to give the same difficult test as used in the previous study, but with an
alteration in how it was presented to the participants. Participants were made aware that
this test had shown gender differences in the results in the past, which is the stereotype
threat. However, the participants were also made aware that this should not affect their
performance on this particular test (10 Spencer).

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Merely mentioning those two statements greatly altered how the women
performed in the second study. Per Spencer et al, “Characterizing the test as insensitive to
gender differences was enough to totally eliminate women’s underperformance in this
experiment. Yet when the same test was characterized as sensitive to gender differences,
women significantly underperformed in relation to equally qualified men” (12 Spencer).
However, because of a floor effect, or extremely low measurements of the dependent
variable, results of the second study were not ideal. The mean for both men and women’s
results on the second test was not that far from zero, which did not make the two halves
of the test equally difficult as intended (12 Spncer). To combat this, Spencer et al decided
to do further research in the third and final study (14 Spencer).
In the third study, Spencer et al closely replicated the previous study’s procedures
and materials. Nonetheless, because they felt the previous studies did not emphasize their
point as clearly, a few alterations were made to the third study. Students were selected
from a different university and the test had a greater range of problems. The control
group also had no mention of gender differences on the test. This was to contrast the
previous studies where even the control groups were told that the test they were taking
had shown great differences in results between men and women (14 Spencer).
Finally, further research was done on the stereotype threat in which the study,
“measured participants’ evaluation apprehension, state of anxiety, and self-efficacy after
they received instructions that manipulated stereotype threat and before they took the
difficult math test” (15 Spencer). In the results of the third study, Spencer et al discovered
that anxiety could be a possible mediator for the stereotype threat. Self-efficacy and

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evaluation apprehension, however, were not shown to be likely mediators for women’s
underperformance on the test (20-21 Spencer).
Ganley and Vasilyeva also conducted research on this topic, using college
students as participants because “gender differences in math have been found to be
particularly robust at this age”. Both researchers sough to test the effects of anxiety and
working memory on the gender differences in math test results (107 Ganley). College
students were to first rate their worry about the upcoming test. This was measured with
statements that were scaled from strongly disagree to strongly agree. To test the students’
working memory, there was a word recall and a spatial recall task to test their verbal and
visuospatial working memory respectively (108 Ganely).
The word recall task was to test each participant’s verbal working memory, where
there were several trials. Each trial consisted of the participant listening to a few
sentences and determining if they were true or false. Next the participant was asked to
state the last word in each sentence in order as they were heard. The visuospatial working
memory, however, was tested with shapes rather than words. Participants had two shapes
right next to each other in each trial, and they had to determine whether the shape on the
right was either identical or a mirror image of the shape on the left (108 Ganley).
Additionally, the shape on the right side could be rotated either zero, one hundred
and twenty, or two hundred and forty degrees, with a red dot marking the top of the right
shape. Visuospatial working memory was more thoroughly tested, as the task was
separated into seven ‘blocks’ where the number of pairs of shapes being compared was
steadily increased. After testing whether each shape was identical or a mirror, the
students had to select a dot that matched the one on the right shape (108 Ganley).

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Results of the experiment showed a significant gender difference in ‘worry’ or
nervousness, visuospatial working memory, and math performance. Verbal working
memory, however, had no significant gender difference. Ganley and Vasilyeva claim that
these correlations show a link between worry, visuospatial working memory, and math
performance. Math performance was shown not to affect verbal working memory, even
though performance in its designated task was tied to visuospatial working memory and
worry (109 Ganley). Per Ganley, “Worry, in particular, appears to be strongly linked to
working memory, as monitoring anxious thoughts utilizes a substantial amount of
working memory resources” (114 Ganley).
As reported by Ganley and Vasilyeva, “These results suggest that one possible
reason gender differences in math performance might exist is because of increased worry
in female students, which taxes their visuospatial working memory, which, in turn, leads
them to perform more poorly on difficult math assessments” (113 Ganley). Their research
showed that the worry component of anxiety before the math test was involved as a
mediator in gender performance. Furthermore, the relationship between working
memory, gender, and math performance was different for verbal and visuospatial. Verbal
working memory, as previously mentioned, was not significantly tied to gender or math
performance, and so is not a mediator. Visuospatial, however, had a strong relationship to
both math and gender performance (114 Ganley).
Even taking anxiety and stereotype threat into account, there is still gender
segregation in US doctorate programs. The ‘leaky pipeline’ metaphor has been used to
describe how, even though numbers of women entering into STEM bachelor and PhD
programs is rising, they are still more likely than men to ‘leak’ from these programs after

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entering. Data from the year 2013 shows that women earn forty eight percent of
chemistry bachelor’s degrees compared to nineteen percent in 1970. However, what
Miller and Wai discussed during their research were multiple reasons that would cause
women to either leave or not pursue graduate school. These reasons range from gender
discrimination, raising a family, or even support from peers (Miller).
Furthermore, Miller and Wai proposed that research on this subject would carry
more difficulties, as sometimes the gap between undergraduate and graduate studies
could be decades. To combat this issue, they, “used nationally representative samples and
retrospective methods to investigate gender differences in the bachelor’s to Ph.D. STEM
pipeline in the U.S. since the 1970s” (Miller). Meaning, they simply interviewed
participants that had already earned their degrees and questioned them about their
experiences.
The below graph shows how often women or men went on to pursue a PhD after a
bachelor’s degree. Data shows that the gender difference closed sometime in the 1990’s.
The table, though, shows estimates that aided Miller and Wai in calculating their
persistence rates for PhD’s in pSTEM fields. This acronym includes the physical sciences
as a separate category of the acronym. Their participants were first divided based on
when they had first earned their bachelor’s and what their field of study was. Then,
persistence rates, or a measurement of how quickly a student would earn their Ph.D after
receiving their bachelor’s degree was measured. This was done by using a rough estimate
which divided the sum of the PhD holders by the sum of bachelor holders. Included
alongside the difference and p columns is the standard error (Miller).

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Results from this data showed that life science had a close convergence between
men and women. In the 1970s and 80s, results from this data show that women were 0.60.7 as likely as men to later earn a graduate degree in pSTEM. But, as recently in the
1990’s to 2000’s, more women have gone on to pursue graduate studies and narrowed the
difference in persistence rates. The below line graph represents how many degrees were
awarded to women over the years (Miller).

As the data shows, women representation in graduate school has been rising over
the decades. Compared with less than three percent of women earning PhD’s in the
1960’s, this number rose to twenty seven percent as of 2012. Miller and Wai propose that
the results are the cause of two factors: that there were more women in bachelor’s

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programs in the 1980’s and 1990’s, and the narrowing of gender persistence rates in those
year. Nevertheless, Miller and Wai theorize that this trend may not continue, due to the
fact that persistence rates have already closed and that women representation in the PhD
level has started declining (Miller).
Miller and Wai’s final thoughts on the ‘leaky pipeline’ metaphor is that it no
longer describes the modern demographic. That even though men earn more PhD degrees
than women in pSTEM fields, the data shows it cannot be due to persistence rates. Miller
and Wai suggest that, “gender diversity initiatives at the graduate level might have helped
increase women’s rate of persisting in a doctoral program after entering graduate school”
(Miller).
Part C: Workforce
Upon graduation from their studies, many women still struggle with biases in the
workforce. Such biases stem from the stereotype of STEM careers as solely ‘masculine’
despite that surely not being the case. Additionally, that the women who are in STEM
career fields can either be seen as competent, or likable, but not both (82 Hill). This in
turn negatively affects any women whose success in her field is not explicit, as she is
going to be seen as less competent than her male coworkers. Furthermore, if she is found
to be more successful than her male coworkers, she becomes less likable to not just her
coworkers, but to others outside her workforce as well. This also can affect her chances at
upward mobility and her evaluations, which can explain why so many women end up
leaving in the middle of their careers (86 Hill).

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The issue of competence and likability contributes to another common topic that
comes up when discussing women in STEM fields of the workforce. Hill et al. state that,
“Being disliked appears to have clear consequences for evaluation and recommendations
about reward allocation, including salary levels” (86 Hill). Research by Heilman supports
this statement, as a group of a hundred and thirty-one people participated in an
experiment of who to promote for salary increases. On average the participants were
people in their thirties who were employed and given a performance rating of the
employee up for review. Participants were asked to rate the employee on their future
success, how they as the participant would feel working under them, and finally rating the
employee overall (Heilman).
Next, the participants in the study were asked if the employee should be
recommended for a ‘special career opportunity’ and what level of salary the employee
should receive. Although it is true the competence played a fair part in how each
employee was evaluated, there were in fact, interesting results concerning each
employee’s likability independent of their competence. An employee who was found to
be likable was evaluated more favorably regardless of their ratings of competence.
Likable employees also were recommended for higher salaries ahead of unlikable
employees that were more competent (Heilman). Hill et al’s take on this research is that
even though a woman is successful and competent in a STEM field, that success can
cause her to be disliked and thus impede her career (85-86 Hill).
Such issues concerning how women are treated in the workforce are still
occurring as recently as 2017. Google, a company that has previously boasted of its
diversity and equal employment opportunities amongst its staff, seems to have taken

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great pains to reduce gender discrimination and bias in its operations. However, in
September of 2017 a lawsuit was filed against Google by several plaintiffs, trailing
allegations of gender discrimination in April of that year from the United States
Department of Labor. Pay discrimination allegations from the Department of Labor
forced the corporation to reveal their salary records (Levin).
Though filed on behalf of multiple women who had worked at Google in the past
four years, only three women were named and supplied a detailed version of events that
caused the lawsuit. One woman, Ellis, was hired as a level three software engineer for
Google Photos, which she claimed was a position often filled for post-graduate college
students. Her complaint was that a male candidate that had graduated the same year as
her was assigned to a level four position who received better salary, benefits, and bonus
opportunities. A few other male candidates at the same level of qualifications or even
under qualified were also filling in higher level positions. Google’s comments on why
Ellis herself wasn’t promoted to a higher level, in spite of exceptional performance
reviews, was that she simply hadn’t been working at Google long enough (Levin).
Another issue that Ellis brought up was with how Google had sequestered a
number of its female employees on the ‘front-end’ occupations which were seen as less
impressive, and therefore, were lower-paying compared to the ‘back-end’ jobs in the tech
sector. Ellis’s background in mathematics and computer science proved her more than
experienced for a role in back-end development of software engineering, yet she found
herself falling behind male coworkers who had been promoted ahead of her from the
beginning (Levin).

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Kelli Wisuri, another plaintiff, became a part of the suit when Google acquired
her company in 2012 and had placed her into a level two position, considered the lowest
level for a full-time employee. Her complaint was that male candidates containing similar
amounts of experience were always started at level three positions or higher. Wisuri also
claimed that fifty percent of the employees in the lower paying track were women, as
opposed to the majority of men in the higher sales track (Levin).
Finally, Holly Pease, who had been hired in 2005 and had over ten years of
experience working as a network engineer, was placed into a ‘nontechnical’ role. All of
the fifty product managers and software engineers she oversaw were in ‘technical’ roles
that claimed higher compensation. Google claimed that she lacked the technical ability
for a promotion. However, she had previously helped a male manager working in the
nontechnical sector pass an interview to transition into the technical department. This
manager, who had been working a level below Pease, transferred into the technical
department and was promoted. She, like the other two plaintiffs, resigned due to the lack
of opportunities with Google (Levin).
Part D: Culture & Attitude
Subsequently, it seems that even though a lack of skill may be a factor, it is small
compared to others such as pressure and anxiety. On the word of, Else-Quest et al, it is
not that there are differences in achievement between male and female students towards
mathematics and the sciences. Rather, it is the difference in attitudes of those subjects
that is causing the gap in the ratio of women to men in STEM majors and careers (294
Else-Quest).

23

Cultural stereotypes and expectations also play a significant factor. The main
idea that Hill brings up as a hindrance is, ‘the notion that men are mathematically
superior and innately better suited to STEM fields than women’ (19 Hill). Examples set
by parents also could contribute to a cultural barrier that prevents women from entering
STEM fields. As stated by Irby et al, “Mothers can also instill personal and cultural
values and interests in their daughters, which can influence how and why students choose
particular majors” (54 Irby). This also includes not just the attitudes and beliefs of the
parents, but also their own knowledge and experience when it comes to STEM. As stated
by Hill et al, “Distinguishing between an interest in computer science and an interest in
computers and technology is important” (59 Hill).
When Irby et al interviewed three different adult women with daughters, they
discovered that a parent’s ignorance of what a career in STEM demands can affect their
children going into those courses in their education. One woman, Guadalupe, often
encouraged her daughter Mónica to continuously work hard on her homework and at
school. Guadalupe insisted that the key to her daughter’s success in life was to work hard
and further her education as much as possible. She further cemented this advice by
having her daughter work in the fields with her (56 Irby).
While this did inspire her daughter to work hard at her studies and excel, it did not
prepare Mónica when she began to take an interest in computer science. When Irby
approached her about the subject, Guadalupe claimed her daughter would excel because
she was ‘good at creating PowerPoint presentations’ (56 Irby). Mónica herself had little
understanding of what sort of skills are demanded in a computer science field or even a
basic understanding of programming. She herself stated that, “This is going to be easy.

24

Simple, right? I can pick up on it. It’s computers. OK. It’s our generation.” However,
after receiving poor results on her midterm, it became clear that that it was not the case
(57 Irby).
But, the culture taught to her by her mother encouraged Mónica to put more effort
into her education, which resulted in high grades for the rest of her coursework (57 Irby).
Seeing her mother return to school to complete her GED also encouraged Mónica further,
showing that the culture and beliefs passed on by parents can be either a positive or
negative influence on their daughter’s attitude towards STEM (58 Irby).

Section IV: Moving Forward: Improvements and Suggestions
Since discrimination and bias women have faced in STEM fields is well
researched, there have been a plethora of discussions and methods tested to try and chip
away at the barriers that prevent female students from taking on STEM majors and
entering in to STEM occupations later on in the workforce. However, are these methods
really successful at reducing bias and getting young women interested in STEM?
One improvement I feel that could be made is to change current public education
curriculum to include introductory programming and computing courses as mandatory
classes rather than electives. The benefits are clear for students of all genders as our
society’s technology continues to advance and assist people in their everyday lives. The
activities and lectures of this elective could be easily adapted to appeal to the women in
the class. Apple’s trademark slogan ‘there’s an app for that’ comes to mind, and

25

introducing that concept to the female students connects the apps that help run their lives
and programs they use daily for leisure and academics to the code that builds them.
Although some high schools have been offering computing courses as electives or
even classes focused on programing languages, this is not the case nationally, especially
concerning high schools and middle schools with smaller student populations.
Additionally, students will have equal opportunities within the course to learn more about
the computing aspects of STEM and gain confidence. Furthermore, I would suggest
adding elements of basic computer and electronic repair as well as more intermediate
troubleshooting that would help students gain better critical and problem-solving skills
that are crucial in STEM occupations and majors.
However, the downside is that implementing such a curriculum change nationally
would likely involve a lot of hoops to jump through, not just in educational policies but
also concerning budgets, scheduling issues, etc. It is possible for students to seek out their
own education outside of the classroom, using public resources such as the local library
and Internet. Nonetheless, the likelihood of a student who wasn’t already interested in
STEM taking the time out of their schedule to commit to learning about it on their own is
already slim. Independent learning done outside the classroom also requires commitment
and dedication, not something every student can achieve.
Hence, implementing more electives within public schools themselves would be a
nice compromise. For example, organic chemistry is an elective that goes more in depth
than standard chemistry classes and would be open for public high school students to take
if they decided they had more interest in chemistry. Several math courses are already
required for high school graduation, but engineering and computing electives are lacking

26

in many public high schools. Many students discover what major they wish to study in
college or what career path they initially want to follow based on what their classes were
like in high school, so the addition of these electives could help increase young women’s
interest in STEM.
Another method that has been introduced is a variety of out of school programs
catered towards young women and their interests in STEM. According to, Irby et al,
“Girls must be engaged, that is, have the awareness, interest, and motivation toward
science” (140 Irby). Programs that take place after school or during the summer are ideal
for allowing girls to learn about STEM to discover if they have an interest in pursuing a
career in STEM later in life. A positive aspect of school programs is that they are free
from the constraints of public education, meaning that the program is able to focus more
in depth on certain topics. Besides, students can feel free to ask questions and learn about
the topic rather than fear being incorrect or harshly graded (140 Irby).
These after school programs have been shown to be successful. Hill et al
claim that, “Plant et al. (2009) reported an increase in middle school girls’ interest in
engineering after the girls were exposed to a 20-minute narrative delivered by a
computer-generated female agent describing the lives of female engineers and the
benefits of engineering careers” (23 Hill). There are, however, some cons to these
programs, mainly in making sure that they are accessible.
As the students are minors who likely do not have a license or reliable means of
transportation, they are entirely dependent on their families to drive. Other programs that
are offered during the summer are likely to take place in the nearest city, for example in
Pittsburgh. A student could take the bus or an Uber ride for transportation with no

27

problems if they lived within any of the towns or suburbs outside the city proper.
However, the situation changes when driving to the city takes an hour or more at the very
least.
Another alternative that has been suggested is implementing all female classes to
lessen anxiety issues and help the students gain more confidence when it comes to
developing skills in STEM areas. According to Rosenthal et al, “Single-sex schooling or
single-sex programs within co-educational environments are a potentially effective
solution to help promote women’s engagement in STEM fields despite the sexism they
face in those fields. However, to date, the mechanisms and processes through which
single-sex programs may contribute to engagement in STEM fields for women are not
well understood” (10 Rosenthal).
In my opinion, the results of these studies are too mixed to depend on to fix the
issues. Other methods have better rates of success, such as the after-school programs, and
take less effort to implement. Furthermore, segregating students based on gender could
lead to discrimination against transgender and nonbinary individuals. That in of itself
could open a metaphorical can of worms that school administrations would not want to
deal with. There is also the fact that eventually the women will no longer be segregated
from the men, whether it be as a student body or in the workforce. When that happens,
there is the likelihood that the women will still end up comparing their performance to
that of their male peers and coworkers, regardless of what the actual results were.
Improvements could be made to the attitudes of young women towards STEM
classes and their achievements without separating them from their peers. A student’s
teacher plays a significant role not only whether they like or dislike a course or subject,

28

but also in the student’s own personal understanding of it. The teaching style
demonstrated during lectures of certain courses can greatly influence how receptive a
student is and how well they will learn the material.
Specifically concerning math courses, nineteen teachers that Irby et al researched
in their study had to concede to a curriculum change in what math courses were required
for students to graduate from high school. Previously, the requirements stated only basic
levels of mathematics be taught, up to the first levels of geometry and algebra, but this
new mandate also put the second level of algebra on the list of requirements for high
school graduation. This new curriculum, known as 4 x 4 Curriculum Model, was made to
better prepare all students for more rigorous graduation standards (198 Irby).
One method the teachers learned about was mathematical modeling. The goal of
this model is to encourage students to learn by practicing as opposed to thinking of
mathematics as the ‘search for a single answer’. The mathematical course model, divided
into four sections, focuses on what the problem is about, what problem is it similar to,
analyzing the problem, and applying context. Teachers were also instructed to use rubrics
and feedback from their students to more accurately measure how they were learning the
material (200 Irby).
Teachers also benefitted from this study. Compared with the results of the pretest
the teachers took before the study, afterwards they showed more knowledge of their
course material by its completion. Three quarters of the teachers involved claimed that
they had learned a great deal of content (204 Irby). Irby et al note that, “Overall, the
limited research in this area indicates that self-reflection and lesson feedback are
beneficial in helping teachers integrate the science and art of teaching, especially

29

important when improving teaching and learning in culturally diverse classrooms” (202
Irby).
Cai Gao, a software engineer, claims that there are four major groups that could
help improve and encourage women’s interest in STEM. Those four groups are local
governments, local organizations, companies, and finally engineering managers. Gao
rightly asserts that while efforts are being made to get young women interested in STEM,
these programs are organized at the national level. Furthermore, Gao asserts that these
programs are often a commitment of time and money (Gao).
Personally, I agree with Gao’s suggestion of having public libraries having free
workshops for girls to try out coding to see if it’s something they would be interested in.
To combat funding issues, the program could be run once a year during the summertime,
when a student is most likely to have more free time.
Gao also asserts that certain local events, while helpful, are not circulating enough
advertisements to reach enough people. Additionally, companies must work harder to
make their hiring practices more inclusive and that “companies should give women the
opportunity to lead from day one” (Gao). However, Gao also places significance to
managers of the firms. According to Gao, it is essential that managers are advocating for
their employees, that one on one sessions between them help the employees feel valued
(Gao).
With smartphones and smart technology becoming more and more integrated in
our society, it only makes sense that unlimited access to information can help get more
young women interested in STEM and help them gain the skills necessary to succeed in

30

those fields. I remember playing typing games in elementary school that encouraged me
to beat my fastest typing speed. Because the game was set in a way that it was fun to
play, I picked up typing skills much more quickly than other kids my age. Something
similar could easily be implemented into web browser games or even mobile apps geared
towards young children. Fun mobile apps could be designed in a way to introduce the
basics of a STEM field as a game.
Puzzle games would help develop the critical thinking skills necessary for STEM
undergraduate courses, for example. In between loading levels could show a bit of trivia
highlighting some famous women in the chosen field to serve as inspiration. Seeing these
role models would encourage as well as inspire young women. Using free mobile apps
would allow for a wider audience, as though video games have become more popular
over the years, not everyone can afford to pay for the newest console or handheld.
Web browser games would also be more accessible, as most people now have
easy access to the Internet in some form, be it a smartphone, laptop, or desktop computer.
One of my favorite things to do in the computer lab when I was younger was to go play
games online. For a young girl, learning about genetic sequences and DNA could become
immensely more appealing if it were packaged as a web game about building your own
dinosaur theme park. Lining up the correct amino acids in the style of a Candy Crush or
Bejeweled minigame that gradually gets more complex and difficult could be one of the
features of such a game.
Tower defense games are a popular genre of game that increase one’s ability to
strategize about what pieces you have at your disposal, which can easily be repurposed to
learn some very basic engineering skills. One idea would be a sort of tower defense game

31

where you as the player have to design your own bridges and towers that have to be
stabilized, therefore teaching you some basics about engineering. Alternatively, there
could be a simple game about calculating the best way to safely launch and land a rocket
reliant on the target planet’s gravity and distance to get women interested in aerospace
engineering as well as mathematics and physics.
As mentioned above between loading levels trivia about women in STEM could
be displayed on the screen. These women could serve as an inspiration to young girls to
pursue a STEM major. I was able to design some screenshots as to what these mobile
apps could look like, as well as the trivia screens shown between levels.

Figure 1: Trivia Splash Screen

32

Figure 2: Matching Mode for Learning Data Types in Programming

33

Figure 3: Gene Sequencing, Matching, and Memorization
The first figure displays a prototype of what a splash or loading screen could look
like, that highlights a role model in STEM for young girls. The information would be
kept simple, with just the woman’s name, profession, and a quick fact about her. The
second figure would show how you can introduce young girls to programming by having

34

them quickly match as much data to its correct type as possible. The third figure is
another type of matching game, but this one would dive into gene sequences and build
memorization skills.
Issues concerning discrimination and bias against women in STEM will not go
away overnight. Some improvements have been made towards encouraging young female
students to get interested in STEM, with mixed results in easing their anxieties. It is of
my opinion that while focusing on students and improving both their confidence and
actual skills is important, discrimination is based on beliefs—and therefore,
subconsciously, or consciously—an act of the mind.
Our society can continue to move forward if we ask not only ‘why aren’t women
interested or in STEM?’ but rather, ‘what’s keeping women out of STEM?’. A person can
of course, gain multiple interests or hobbies later in life, and career changes are not
unheard of. But all the interest and passion in the world sometimes isn’t enough to
overcome the barriers that hinder women in modern day society. It is not possible to
completely erase problems of prejudice and discrimination from our society, but
conditions can improve if care is taken to look at the issue seriously.
Technology has been advancing in a rapid-fire fashion and will continue to do so.
However, when we learn about what has passed or hypothesize what’s to come, we
cannot do so without thanking all the women in STEM who have contributed, and those
that are working diligently even now to provide a better world.

35

Section V: References
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