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Cultural Stereotypes as Gatekeepers: Increasing Girls’ Interest in Computer Science and Engineering by Diversifying Stereotypes


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Despite having made significant inroads into many traditionally male-dominated fields (e.g., biology, chemistry), women continue to be underrepresented in computer science and engineering. We propose that students' stereotypes about the culture of these fields-including the kind of people, the work involved, and the values of the field-steer girls away from choosing to enter them. Computer science and engineering are stereotyped in modern American culture as male-oriented fields that involve social isolation, an intense focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities that are typically more valued in men than women in American culture. As a result, when computer science and engineering stereotypes are salient, girls report less interest in these fields than their male peers. However, altering these stereotypes-by broadening the representation of the people who do this work, the work itself, and the environments in which it occurs-significantly increases girls' sense of belonging and interest in the field. Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and constraining their learning opportunities and career aspirations.
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published: 11 February 2015
doi: 10.3389/fpsyg.2015.00049
Cultural stereotypes as gatekeepers: increasing girls’
interest in computer science and engineering by
diversifying stereotypes
Sapna Cheryan 1*, Allison Master 1,2 and Andrew N. Meltzoff1,2
1Department of Psychology, University of Washington, Seattle, WA, USA
2Institute for Learning & Brain Sciences, University of Washington, Seattle, WA, USA
Edited by:
Stephen J. Ceci, Cornell University,
Reviewed by:
Andrei Cimpian, University of Illinois,
Toni Schmader, University of British
Columbia, Canada
Sapna Cheryan, Department of
Psychology, University of Washington,
Box 351525, Seattle, WA 98195, USA
Despite having made significant inroads into many traditionally male-dominated fields (e.g.,
biology, chemistry), women continue to be underrepresented in computer science and
engineering. We propose that students’ stereotypes about the culture of these fields—
including the kind of people, the work involved, and the values of the field—steer girls
away from choosing to enter them. Computer science and engineering are stereotyped in
modern American culture as male-oriented fields that involve social isolation, an intense
focus on machinery, and inborn brilliance. These stereotypes are compatible with qualities
that are typically more valued in men than women in American culture. As a result, when
computer science and engineering stereotypes are salient, girls report less interest in
these fields than their male peers. However, altering these stereotypes—by broadening
the representation of the people who do this work, the work itself, and the environments
in which it occurs—significantly increases girls’ sense of belonging and interest in the field.
Academic stereotypes thus serve as gatekeepers, driving girls away from certain fields and
constraining their learning opportunities and career aspirations.
Keywords: science, underrepresentation, belonging, gender, stereotypes
In 2010, Mattel let girls vote online for which career they wanted
Barbie to have next. They gave girls a choice of one of five careers:
news anchor, architect, surgeon, environmentalist, and computer
engineer. Computer Engineer Barbie ended up winning by a land-
slide after female engineers and others in technology launched
online campaigns in technology communities to get out the vote.
Their hope was that future generations of girls would play with
Computer Engineer Barbie and be inspired to pursue careers
in computer science and engineering (Martincic and Bhatnagar,
2012). After the voting closed, Mattel announced the simultane-
ous release of two of the Barbies: Computer Engineer and News
Anchor. Although Computer Engineer Barbie had won the “pop-
ular vote, Mattel’s empirical research showed that the “girls’vote
went to News Anchor Barbie (Zimmerman, 2010). This anecdote
is symbolic of a broader trend in our society: despite efforts by
people in education, technology, government, and non-profits to
get girls interested in a future in computer science and engineering,
girls are choosing other fields.
Women currently make up 48% of medical school graduates
and 47% of law school graduates (Jolliff et al., 2012;American
Bar Association, 2014). Even within STEM (science, technology,
engineering, and math), women obtain the majority of the U.S.
undergraduate degrees (59%) in biology and nearly half in chem-
istry and math (National Science Foundation, 2013). However,
in computer science and engineering, women earn less than 20%
of undergraduate degrees (National Science Foundation, 2013).
Gender disparities in computer science and engineering are prob-
lematic for at least three reasons. First, jobs in these fields are often
high-status, lucrative, and flexible (Kalwarski et al., 2007), and thus
women are missing out on jobs that are potentially beneficial for
them. Second, computer scientists and engineers design tools that
shape modern society, and diversifying the field can help to ensure
that these fields are creating designs appropriate for a broad pop-
ulation (Margolis and Fisher, 2002). Third, the U.S. is currently
not training enough computer scientists and engineers to keep up
with demand (Soper, 2014). Attracting more women and people
of color would be an effective way of reducing this gap.
Women have entered many other previously male-dominated
fields, including other STEM fields, but not computer science
and engineering. Why the differential? According to Gelernter
(1999), professor of computer science at Yale, the explanation
for women’s underrepresentation is obvious, “Women...must be
choosing not to enter, presumably because they don’t want to; pre-
sumably because they (by and large) don’t like these fields.” His
statement assumes that women’s choices are freely made and not
constrained. If women are freely choosing not to pursue computer
science, perhaps nothing can or should be done about it—after all,
it is their choice. However, it is clear from a large body of scientific
research that there are significant social barriers to women’s entry
into computer science and engineering that preclude women from
being able to make a truly “free” choice (Ceci et al., 2009). Here we
analyze those barriers and what can be done about them.
In what ways are girls’ educational choices constrained? First,
girls may be steered away from computer science and engineering
by parents, teachers, and others who think that these careers are
better suited for boys(Eccles et al.,1990;Sadker and Sadker, 1994).
Second, the mere fact of having underrepresentation can
perpetuate future underrepresentation (Murphy et al., 2007). If February 2015 |Volume 6 |Article 49 |1
Cheryan et al. Stereotypes as gatekeepers
girls do not see computer scientists and engineers as people with
whom they feel similar, they may be more reluctant to enter
these fields (Dasgupta, 2011;Meltzoff, 2013). Third, girls sys-
tematically underestimate how well they will do in these fields,
and this predicts their lower interest in entering them (Correll,
2001;Ehrlinger and Dunning, 2003). Fourth, girls may antic-
ipate encountering greater work-family conflicts in these fields
(Ceci et al., 2009). Fifth, there is discrimination in these fields
that prevents qualified women from receiving the same oppor-
tunities as their male counterparts (Moss-Racusin et al., 2012).
Sixth, women who enter traditionally masculine domains can be
socially and professionally penalized for exhibiting competence
and leadership qualities (Rudman, 1998). These are all barriers
that contribute to why some women choose not to enter and
persist in fields like computer science and engineering. Note,
however, that these barriers previously existed (and continue to
exist) in other male-dominated fields that women have entered.
A key question remains: what has allowed other fields to welcome
more women while computer science and engineering continue to lag
In this paper, we present evidence for a novel and power-
ful social factor perpetuating the underrepresentation of women
and girls: stereotypes about the culture of these fields. We begin
by differentiating stereotypes about the culture from the large
body of useful work on stereotype threat. Then, we describe
the content of students’ stereotypes about the culture of com-
puter science and engineering and document their pervasiveness
in the minds of American students. Third, we describe three
ways that these stereotypes about the culture are transmitted:
through environments, the media, and the people in the fields,
and why these stereotypes are a more powerful deterrent for
girls than boys. Fourth, we present empirical evidence that these
stereotypes cause gender disparities in interest in entering com-
puter science and engineering not only in college but earlier
in the pipeline, including among high-school students. Finally,
we show that these stereotypes, while powerful, are nonethe-
less highly malleable and that changing them encourages girls
and women to enter these fields (without dissuading boys and
men). Note that research on different populations, at differ-
ent ages, and asking different questions (e.g., why are women
underrepresented in the STEM workforce?) may discover differ-
ent factors responsible (e.g., Eagly and Carli, 2007;Hewlett et al.,
2008;Ceci et al., 2009,2014). Our argument is that stereotypes of
the field act as educational gatekeepers, constraining who enters
these fields, and that interventions to broaden the cultural rep-
resentation of these fields can help to draw more diversity into
By elementary school, indeed as early as second grade, girls already
hold stereotypes associating boys with math (Cvencek et al., 2011).
A large body of research on stereotype threat has investigated the
consequences of concerns about being judged through the lens
ofanegativestereotype(Steele, 1997). This research has shown
that negative stereotypes about girls’ math abilities hinder their
math performance (Huguet and Regner, 2007; see also Spencer
et al., 1999;Master et al., 2014). There are three ways in which the
work presented here differs from this established work on stereo-
type threat. First, work on stereotype threat focuses on stereotypes
about girls and women whereas our focus is on students’ stereo-
types about the culture of the fields. Both sets of stereotypes –
stereotypes about girls themselves and girls’ stereotypes about
the culture – may be operating simultaneously to make girls feel
like they do not belong in computer science and engineering (see
Figure 1).
Second, whereas stereotypes about girls’ math abilities (“girls
are not good at math”) are negative, we investigate stereotypes
that are not always negative (Cheryan et al., 2009). Indeed, stereo-
types of computer scientists and engineers can be a source of
pride, identification, and belonging for some in the field (e.g.,
the Geek Girl Dinners organization). This lack of objective neg-
ativity can make diversifying how the fields are portrayed more
challenging because these stereotypes might not be seen as prob-
lematic, even in the face of evidence that many students find them
incompatible with how they see themselves. Third, stereotype
threat effects are most prominent among women who are already
highly identified and invested with STEM, such as STEM majors
(Schmader et al., 2008). In contrast, we suggest that stereotypes
about the culture preclude many girls from even considering the
fields in the first place, and thus deter a larger number of girls from
At what juncture in the pipeline are girls and women opting out of
computer science and engineering? Although many highly quali-
fied women leave these fields (Hewlett et al., 2008), a much larger
contributor to the gender gap is that girls are much less likely
than boys to choose them in the first place (de Cohen and Deterd-
ing, 2009). Among high-school students, girls are significantly less
likely to take a computer programming class than boys (Shashaani,
1994;Schumacher and Morahan-Martin, 2001), less likely to take
the computer science Advanced Placement (AP) test than boys
(College Board, 2013), and express less interest in pursuing careers
in computer science and engineering than boys (Weisgram and
Bigler, 2006). By the time they enter college, men are already
more than four times more likely to have an intention to major in
computer science and engineering than women (National Science
Foundation, 2012). Even if every woman who intended to major
in computer science and engineering upon entering college was
retained in these fields, men would still be significantly more likely
to earn a computer science and engineering degree than women
(see Figure 2).
Though there is debate on whether biological factors play a role
in women’s underrepresentation in STEM (Benbow and Stanley,
1982;Spelke, 2005), differences in interest in computer science and
engineering between boys and girls are evident even among stu-
dents with the highest math abilities. Among the top scorers on a
standardized math test administered in the 10th grade, girls relative
to boys were more likely to choose social science and health-related
majors in college over majors in computer science, engineering,
physical sciences, and mathematics (Perez-Felkner et al., 2012).
Computer science and engineering are missing out on an entire
population of talented girls who are not entering these fields to
begin with.
Frontiers in Psychology |Developmental Psychology February 2015 |Volume 6 |Article 49 |2
Cheryan et al. Stereotypes as gatekeepers
FIGURE 1 |Students have stereotypes about the culture of computer science and engineering and girls face negative stereotypes about their
abilities. Both types of stereotypes signal to girls that computer science and engineering are not appropriate fields for them.
FIGURE 2 |Percentage of freshmen women and men who intend to
major in computer science and engineering, and percentage of
undergraduates who graduate with computer science and engineering
degrees. Freshmen data are drawn from U. S. postsecondary institutions
while degree data are drawn from U. S. degree-granting institutions eligible
to participate in Title IV financial aid programs.The latest available data were
used (2010 for freshmen intentions and 2012 for degrees granted). Source:
National Science Foundation.
Intervening early in the pipeline (i.e., before college) is impor-
tant to remedying disparities in computer science and engineering.
Societal change will occur only to the extent that the students
who are initially drawn into the field are able to remain in it,
thus research on retention is, of course, important and useful.
However, closing the gender gap in computer science and engi-
neering participation will initially require convincing more girls
to join these fields. As we will argue, stereotypes of the culture
affect girls’ choices and interest, and do so early in the pipeline.
When students think of computer scientists, they often think of
“geeky” guys who are socially awkward and infatuated with tech-
nology (Mercier et al., 2006;Rommes et al., 2007).Theworkin
computer science and engineering is seen as isolating and rela-
tively dissociated from communalgoals such as helping societ y and
working with others (Hoh, 2009;Diekman et al., 2010). Computer
scientists and engineers are also perceived as having masculine
interests (e.g., playing video games; Cheryan et al., 2011b), and
their faculty are more likely than faculty in other fields (e.g., biol-
ogy, psychology) to believe that an inborn brilliance or genius is
required to be successful (Leslie et al., 2015). Of course, many
computer scientists do not fit these stereotypes (Borg, 1999).
But people’s beliefs have a tremendous power to determine their
attitudes, behaviors, and choices, even if these perceptions are
completely disconnected from reality (Hasdorf and Cantril, 1954;
Ross and Nisbett, 1991). In the words of one female computer sci-
ence major at Carnegie Mellon,“Oh my gosh,this isn’t for me.’...
I don’t dream in code like they do” (Margolis et al., 2000, p. 17).
Computer science and engineering stereotypes are pervasive
in modern American society and even young students frequently
endorse them. When high-school students described computer
scientists, the majority (84%) mentioned at least one measur-
able stereotype, including being technically oriented, singularly February 2015 |Volume 6 |Article 49 |3
Cheryan et al. Stereotypes as gatekeepers
focused on technology, socially awkward, masculine, intelligent,or
having particular physical traits such as glasses or pale skin (Master
et al., unpublished). College students reported similar stereotypes,
with 67% mentioning at least one of these stereotypes about com-
puter scientists (Cheryan et al., 2013b). College students were also
less likely to believe that computer science and engineering were
fields that could be used to help people or work with others than
fields such as medicine and law (Hoh, 2009;Diekman et al., 2010).
In today’s society, computer science and engineering stereo-
types are perceived as incompatible with qualities that are valued
in women, such as being feminine, people-oriented, and modest
about one’s abilities (Diekman et al., 2011;Cheryan, 2012;Leslie
et al., 2015). As a result, when these stereotypes are prominent,
girls and women, but not boys and men, believe that they are
dissimilar from those in the field and report a lower “sense of
belonging,” or feeling of fit with the culture of the field (Cheryan
et al., 2009; Master et al., under review). The less that students
feel a sense of belonging in a field, the less likely they are to pur-
sue that field (Good et al., 2012;Smith et al., 2013; Master et al.,
under review). Changing these stereotypes may allow more girls
and women to believe they are welcome in computer science and
Below we review three ways in which students may be exposed to
computer science and engineering stereotypes – through media,
people in the fields, and environments. Because computer science
and engineering are not mandatory and often not even offered in
U.S. high schools (Stephenson et al., 2005), many students do not
have direct experience with these fields. As a result, students often
rely on cultural stereotypes about computer scientists and engi-
neers for knowledge about these fields. However, these stereotype
transmission channels have an upside as well: they are particu-
larly well-suited mechanisms of cultural change if interventions
are designed appropriately.
Popular movies and television shows like Real Genius,The Big
Bang Theory, and Silicon Valley depict computer scientists and
engineers as mostly White (and more recently Asian) males,
socially unskilled, and singularly obsessed with technology. Simi-
larly, portrayals of technology companies in popular newspapers
and books often depict the “startup culture” that infuses some
technology and engineering jobs (e.g., Guo, 2014;Miller, 2014).
This is unfortunate because in reality such portrayals depict at
best only a small percentage of the jobs in computer science
and engineering (Bureau of Labor Statistics, 2014). Yet high-
school students report that their ideas about what scientists
are like are influenced more by the media than by any other
source (Steinke et al., 2007). Even brief exposures to television
portrayals can influence attitudes toward the group portrayed
(Weisbuch et al., 2009).
To examine the extent to which exposure to stereotypical and
non-stereotypical media representations influence women’s inter-
est in computer science, women undergraduates read one of two
fabricated newspaper articles. One article stated that computer
scientists fit the current stereotypes, while the other stated that
computer scientists were diversifying and no longer fit the stereo-
types. Women who read the stereotypical article expressed less
interest in majoring in computer science than women who read the
non-stereotypical article. Furthermore, women who read the non-
stereotypical article were significantly more interested in computer
science than women who read no article (Cheryan et al., 2013b).
Changing the images of computer science and engineering in the
media may increase women’s interest in these fields.
Faculty, students, and industry professionals embody certain char-
acteristics, habits, and belief systems that can signal what is
normative and valued in the field. For instance, the National
Academy of Engineering’s website features
a female computer engineer who appears to fit the definition of a
role model for girls: she is successful, competent, and shares their
gender (Marx et al., 2005;Stout et al., 2011). However, her profile
also describes how she embodies stereotypes of computer scien-
tists and engineers: she started programming at age 11 and works
as a Star Wars video game designer. Computer scientists and engi-
neers who embody these stereotypes may discourage women from
entering these fields.
To investigate whether encountering a stereotypical computer
science student can deter women, undergraduate women were
brought into a room to have a conversation with a participant
who was actually an actor. Three male and three female actors
were used. The conversation was brief – less than 2 min on aver-
age – and consisted of the participant and the actor exchanging
basic information about themselves (e.g., year, major, hobbies,
favorite movie). The actor always stated that he or she was a junior
and a computer science major, but half of the participants were
randomly assigned to interact with an actor who fit current stereo-
types in appearance and preferences (e.g., glasses, t-shirt that said
“I code therefore I am,” hobbies that included playing videogames)
or one who did not fit these stereotypes (e.g., solid colored t-shirt,
hobbies that included hanging out with friends). After the inter-
action was complete, participants were asked about their interest
in their partner’s major and then asked the same questions again
2 weeks later.
Results revealed that women who interacted with the stereo-
typical student were significantly less interested in majoring
in computer science than those who interacted with the non-
stereotypical student, and this effect was equally strong regardless
of whether the actor was male or female. Moreover, negative
effects of stereotypes endured for 2 weeks after the interaction
(Cheryan et al., 2013a). The computer science major’s gender mat-
tered less in influencing women’s interest in computer science
than the extent to which he or she fit current computer science
Follow-up experiments (a) revealed similar effects of peer
stereotypicality on anticipated success in computer science
(Cheryan et al., 2011b) and also (b) investigated why people in
the field who embody computer science stereotypes may be steer-
ing women away from the field. Interacting with a stereotypical
computer science major reduced women’s anticipated success in
Frontiers in Psychology |Developmental Psychology February 2015 |Volume 6 |Article 49 |4
Cheryan et al. Stereotypes as gatekeepers
computer science but did not affect men’s anticipated success
(Cheryan et al., 2011b). Why? Women felt less similar to the stereo-
typical student than to the non-stereotypical student, suggesting
students may look to other characteristics besides gender when
determining with whom they feel similar (see also Cheryan et al.,
2011b;Meltzoff, 2013). When the people in computer science
depict themselves in a manner consistent with the stereotypes, it
can convey to other students that one must fit the stereotypes to
be successful in these fields.
Computer scientists and engineers who depict the work in their
fields as highly independent may also discourage women from
entering their fields. College women who read about an entry-
level scientist who spent a typical day doing independent tasks
reported less positive attitudes about science careers than col-
lege women who read about an entry-level scientist who spent a
typical day doing collaborative tasks (Diekman et al., 2011). More-
over, fewer female students are present in fields whose faculty
believe that success in their field requires innate brilliance, a belief
that is prominent in computer science and engineering (Leslie
et al., 2015). Changing stereotypes about the work being isolating
and requiring an innate brilliance may draw more women into
computer science and engineering.
Objects and environments are powerful because they are seen as
providing clues about the dominant culture within that environ-
ment, including information about the values, beliefs, norms,
and practices (Whiting, 1980;Cialdini et al., 1990;Markus and
Kitayama, 1991). Environments that depict computer science and
engineering as more compatible with characteristics, interests, and
values associated with men and boys are likely to draw fewer girls
than boys into them. However, exposing students to computer
science and engineering environments that do not fit current male-
oriented stereotypes may reduce gender disparities in interest in
these fields.
College undergraduates who were not computer science majors
(in order to focus on recruitment) entered a classroom in the
computer science department at Stanford University, which was
decoratedinoneoftwoways(Cheryan et al., 2009). For half the
participants, the room had objects that other undergraduates asso-
ciated highly with computer science majors—Star Trek posters,
science fiction books, and stacked soda cans. For the other half of
participants, the room contained objects that other undergrad-
uates did not associate with computer science majors—nature
posters, neutral books, and water bottles. Women in the room
that did not contain the stereotypical objects expressed signifi-
cantly more interest in majoring in computer science than those
in the room that did fit the stereotypes. For men, the environment
did not affect their interest in computer science (Cheryan et al.,
Online educational environments are becoming an increasingly
important presence in students’ lives as universities use them as
tools for education. To test whether the design of virtual class-
rooms influences educational outcomes, undergraduates virtually
entered two classrooms in Second Life, an online 3D interactive
virtual environment. Both were introductory computer science
classrooms, but one contained stereotypical objects while the other
contained non-stereotypical objects. Whereas only 18% of women
chose to take the course in the stereotypical classroom, more than
half of men (60%) chose that classroom. Furthermore, women
expected to perform worse in the class with the stereotypical
objects than men, but in the non-stereotypical classroom, women’s
expectations rose, so that women and men expected to do equally
well (Cheryan et al., 2011a).
Why did the stereotypical environment deter womenmore than
men? Women reported a lower sense of ambient belonging in
the stereotypical environment, or sense of fit with the material
components and with the people assumed to inhabit the envi-
ronment. In contrast, men reported an equal, and sometimes
greater, sense of ambient belonging in the stereotypical envi-
ronment than the non-stereotypical environment (Cheryan et al.,
2009,2011a). Women were less likely than men to associate them-
selves with the stereotypical objects, and the more that women
perceived the stereotypical environment as masculine, the less
interest they expressed in being in that environment (Cheryan
et al., 2009).
Earlier in the pipeline, high-school students also show sim-
ilar effects on their interest in taking introductory computer
science in a classroom that fits or does not fit current com-
puter science stereotypes (Master et al., under review). Girls were
more likely to choose a non-stereotypical classroom (68% of
girls) over a stereotypical one, while boys showed no prefer-
ence for a non-stereotypical classroom (48%). Moreover, girls’
baseline interest in a computer science course in which the class-
room was not described was no different from their interest
in a stereotypical course (and both were lower than the non-
stereotypical course), suggesting that a stereotypical classroom
was consistent with girls’ default assumptions about introduc-
tory computer science courses. However, a non-stereotypical
environment provided a new image of computer science and
increased their interest over baseline. Like their college coun-
terparts, high-school girls felt a lower sense of fit with current
computer science stereotypes than did boys. The less that girls
reported a sense of fit with the current stereotypes, the more
likely they were to be deterred from a stereotypical (but not a
non-stereotypical) computer science environment (Master etal.,
under review). The observed variability between girls is striking
and suggests that current stereotypes should be diversified rather
than eliminated, a point we discuss in more detail in the next
Thus, women and girls may be choosing fields other than com-
puter science and engineering in part due to the constraining
power of current stereotypes that portray the culture of the field
in a manner that is incompatible with the way that women see
themselves. When the constraint is lifted by presenting a non-
stereotypical image, girls’ sense of belonging and interest in the
field can increase, without reducing boys’interest.
In all studies investigating effects of stereotypes, there is a siz-
able portion of students who may be drawn to these fields
because of these stereotypes. In the studies on environments, some
women (typically 20–25% of women) preferred the stereotypical February 2015 |Volume 6 |Article 49 |5
Cheryan et al. Stereotypes as gatekeepers
environment over the non-stereotypical environment. Rather than
attempting to overhaul current stereotypes, which may deter some
men and women, a more effective strategy may be to diversify the
image of these fields so that students interested in these fields do
not think that they must fit a specific mold to be a successful
computer scientist or engineer.
Diversifying the image of computer scientists and engineers
may not only attract more women to the field, but also make some
men feel more welcome in these fields. Indeed, in the studies
on environments, some men (typically 25–30% of men) pre-
ferred the non-stereotypical environment over the stereotypical
environment. In addition, many men also highly value oppor-
tunities to work with and help others (Diekman et al., 2011).
Attracting more non-stereotypical men to the field is a way to
further stretch stereotypes and diversify a field (Drury et al.,
A question that our readers may have is whether it is fair to
present girls with a non-stereotypical image of the fields of com-
puter science and engineering if they will then enter these fields and
be unprepared for the male-oriented culture that they encounter
there. We believe it is necessary and useful to prepare girls and
women for the obstacles they may encounter in male-dominated
fields and how to overcome them. We also believe that the cul-
tures of these fields should be changed to be more welcoming of
a diversity of people. However, our viewpoint is that girls are cur-
rently exposed to an unrealistic image of these fields that depicts
all computer science and engineering cultures as fitting a narrow
profile. A broader image that shows many different types of people
and working environments in computer science and engineering
actually represents a more realistic portrayal. Furthermore, once
we start the process of welcoming more women and girls into these
fields, the process of culture change will likely build on itself and
contribute to further improving the actual and perceived culture
of these fields for women.
The computer science departments at Carnegie Mellon and
Harvey Mudd provide two real-world examples of the power of
changing cultural stereotypes to reduce gender disparities in par-
ticipation. Both increased the proportion of women majoring
in computer science from 10 to 40% in 5 years (Margolis and
Fisher, 2002;Hafner, 2012). In addition to structural changes (e.g.,
changes in recruiting procedures), both programs changed stereo-
types of computer science by using diverse role models, exposing
students to a wide range of applications of computer science, and
revamping their introductory course so that it was no longer seen
as a field only for “geeky know-it-alls” (Margolis and Fisher, 2002;
Hafner, 2012). These examples show that efforts to reduce gen-
der disparities in computer science and engineering benefit from
actively working to change the culture of these fields, so that
they are seen as places where all students are valued and have
the potential to be successful.
Why are girls, even those who grew up with technology in their
homes and took advanced math classes in high school, less likely
than boys to pursue computer science and engineering? Our cen-
tral thesis is that girls’ underrepresentation in these fields is not
due to their intractable lack of interest in choosing these fields.
Instead, we argue that women’s choices are constrained by societal
factors, particularly their stereotypes about of the kind of people,
the work involved, and the values of these fields (see Figure 1).
These perceptions, even if they are not accurate, shape the aca-
demic choices that girls make by communicating to them where
they belong.
We also argue that we can change students’ stereotypes of
the culture using relatively simple interventions to environments,
the media, and by diversifying the type of people representing
these fields. Rather than “de-geeking” the fields, a more successful
approach involves creating inclusive cultures so that those who
are considering these fields do not necessarily have to embody the
stereotypes to believe that they fit there. One concrete way to cre-
ate inclusive cultures is to consider who is selected to represent
the field (e.g., who teaches the introductory courses) and what
messages he or she signals about the kind of student who belongs
in the field. If all representatives are similar to one another, it
can signal that one has to fit that mold in order to be successful
in that environment. If there is diversity in who is presented, it
sends the message that a variety of people can be successful. Phys-
ical spaces are another effective way to signal who belongs. We
have shown that it is possible and feasible to create physical spaces
within the larger environment that allow both men and women
to feel welcome there. Finally, it is also important to change the
stories told in the media about these fields and who is found in
The main message of this research is that variability is key.
Instead of portraying computer science and engineering as nar-
row fields that are easily stereotyped—and which therefore steer a
large number of students away because they “do not belong”—we
can alter how the culture of these fields is represented in the minds
of youth. By broadening the mental picture of what it means to
be a computer scientist or engineer, we may not only attract more
women to these fields, but also be more accurate about what com-
puter science and engineering are like and what they have the
potential to become.
This work was supported by grants from the National Science
Foundation, DRL-1420351 to SC and SMA-0835854 to ANM.
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Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 17 October 2014; paper pending published: 01 December 2014; accepted: 10
January 2015; published online: 11 February 2015.
Citation: Cheryan S, Master A and Meltzoff AN (2015) Cultural Stereotypes as gate-
keepers: increasing girls’ interest in computer science and engineering by diversifying
stereotypes. Front. Psychol. 6:49. doi: 10.3389/fpsyg.2015.00049
This article was submitted to Developmental Psychology, a section of the journal
Frontiers in Psychology.
Copyright © 2015 Cheryan, Master and Meltzoff. This is an open-access article dis-
tributed under the terms of the Creative Commons Attribution License (CC BY). The
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... Further, Wang and colleagues suggest that girls may get more out of science and maths lessons if they are taught through the lens of a storytelling and gamified lessons since stories make the lessons more relatable [53]. The studies reported in [29,11] introduce girls to stories and events that can influence their professional choice at an early age. ...
... The strategy of using the female histories as role-models in CS has been used in the past [4,22]. Indeed, the lack of female role models in CS [4] [22] is still an issue and it has been recognised as one of the most detrimental factors for young girls causing them to stop relating to CS; and hence they require a female role model to be motivated to study CS or pursue a career in the field [4,11]. More specifically, a project called CS for Fun (CS4FN [16]) can be mentioned, that has produced and made freely available (online) a booklet that showcases female role models and their groundbreaking work in CS. ...
... Another potential development for the future concerns the gamification of the framework [29,11,12], as gamification can influence professional choice at an early age. Storytelling and gamification together have the potential to appeal to a young audience and help inducing behavioural changes as discussed in Rubegni et al. [37]. ...
Full-text available
Motivation & challenge: Computer Science suffers from a lack of diversity that gets perpetuated by the most dominant and visible role models. The community is doing itself a disservice by upholding techno-solutionism, short-term efficiency, and busyness as central values. Those models are created and consolidated over time through social and cultural interactions that increase the perpetration of gender stereotypes. Exposing people to diverse types of role models and stories can contribute to making them more aware of the complexity of reality and inspire them taking better informed decisions-making on their career paths. Likewise, showing different role models to stakeholders in society and industry can contribute to increase the workforce diversity in the profession of computing as well as to make a shift towards the consolidation of different role models. This, in turn, may contribute to strengthen resilience and adequacy for solving issues related to diversity, equality and inclusion in Computer Science and more importantly allowing women take the ownership of their career path. Goal: To encourage the dissemination, sharing and creation of stories that show diverse career pathways to address gender stereotypes created by dominant stories in Computer Science. We tackle this issue by developing a framework for storytelling around female scientists and professionals to show a diversity of possibilities for women in pursuing an academic career based on the ownership of their pathways. Method: We apply a qualitative approach to analyse stories collected using the auto-ethnography and use thematic analysis to unpack the components of what in these stories contribute to building the academic path in the field of Computer Science. Authors used their own professional histories and experiences as input. They highlighted the central values of their research visions and approaches to life and emphasised how they have helped to take decisions that shaped their professional paths. Results: We present a framework made of the nine macro-themes emerging from the autoethnography analysis and two dimensions that we pick from the literature (interactions and practices). The framework aims to be a reflecting storytelling tool that could support women in Computer Sciences to create their own paths. Specifically, the framework addresses issues related to communication, dissemination to the public, community engagement, education, and outreach to increase the diversity within Computer Science, AI and STEM in general. Impact: The framework can help building narratives to showcase the variety of values supported by Computer Science. These stories have the power of showing the diversity of people as well as highlighting the uniqueness of their research visions in contributing to transformation of our global society into a supportive, inclusive and equitable community. Our work aims to support practitioners who design outreach activities for increasing diversity and inclusion, and will help other stakeholders to reflect on their own reality, values and priorities. Additionally, the outcomes are useful for those who are working in improving the gender gap in Computer Science in academia and industry. Finally, they are meant for women who are willing to proceed into an academic career in this area by offering a spur for reflection and concrete actions that could support them in their path from PhD to professorship.
... There is a growing body of literature on the factors which lead to gender disparities in STEM education and professions, highlighting the role played by gender stereotypes and their effect on selecting certain education areas (Chatzi & Murphy, 2022). According to Cheryan et al. (2015), there are two types of stereotypes that influence women's participation in the fields of Computer Science and Engineering. One set of student stereotypes is about the culture (the type of work, the type of people working in certain professions, and the values attached to these fields), and the other set of stereotypes is about girls having less abilities in STEM fields, known as negative stereotypes about girls' abilities (Cheryan et al., 2015). ...
... According to Cheryan et al. (2015), there are two types of stereotypes that influence women's participation in the fields of Computer Science and Engineering. One set of student stereotypes is about the culture (the type of work, the type of people working in certain professions, and the values attached to these fields), and the other set of stereotypes is about girls having less abilities in STEM fields, known as negative stereotypes about girls' abilities (Cheryan et al., 2015). ...
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The prevalence of gender stereotypes in STEM fields is evidenced by a large body of literature across the world, however, this area of research is still understudied in the Western Balkan region. To get a better knowledge of the extent of studies addressing this topic, we conducted a scoping review investigating existing gender stereotypes and educational choices in STEM in that region. As expected, the number of studies discovered was very limited, despite our generous inclusion criteria. In these limited studies, however, we found ample evidence of existing gender stereotypes in STEM and their impact on career aspirations. As this scoping review focused only on high-school university students, we conclude the paper with thoughts on future work ideas to expand the target group as well as to use systems thinking as an overarching perspective to conduct a holistic examination. This could be achieved by including relevant actors within and outside the immediate context, such as parents, schools, policymakers, businesses, and organizations. Finally, the paper also discusses the impact and opportunities that come with digitalization efforts, which could be leveraged to increase women participation in STEM. Received: 11 December 2022 / Accepted: 17 February 2023 / Published: 5 March 2023
... Yet, the lack of diversity and potential discrimination towards underrepresented groups in these work environments is an obstacle for them to succeed in engineering [7], [8]. Moreover, potential gatekeeping such as stereotyping in computer science and engineering even unintentionally can have negative effects on whether a minority feels comfortable staying in our field [9]. Ultimately, the lack of diversity can create unwelcoming environments or negatively impact the sense of belonging which can inhibit whether someone from an underrepresented group continues to pursue engineering [10], [11]. ...
... Studies suggest students leave STEM fields or choose different careers after graduation due to factors such as level of success and demographic characteristics [14]. Moreover, gender stereotypes often "gatekeep" the field of computer science or software engineering hindering women and other underrepresented individuals' intentions of choosing these field [9]. As such, researchers have tried to introduce new ways of incorporating diversity into education [15]. ...
While a lack of diversity is a longstanding problem in computer science and engineering, universities and organizations continue to look for solutions to this issue. Among the first of its kind, we launched INSPIRE: STEM for Social Impact, a program at the University of Victoria, Canada, aimed to motivate and empower students from underrepresented groups in computer science and engineering to develop digital solutions for society impactful projects by engaging in experiential learning projects with identified community-partners. The twenty-four students in the program came from diverse backgrounds in terms of academic areas of study, genders, ethnicities, and levels of technical and educational experience. Working with six community partners, these students spent four months learning and developing solutions for a societal and/or environmental problem with potential for local and global impacts. Our experiences indicate that working in a diverse team with real clients on solving pressing issues produces a sense of competence, relatedness, and autonomy which are the basis of self-determination theory. Due to the unique structure of this program, the three principles of self-determination theory emerged through different experiences, ultimately motivating the students to build a network of like-minded people. The importance of such a network is profound in empowering students to succeed and, in retrospect, remain in software engineering fields. We address the diversity problem by providing diverse, underrepresented students with a safe and like-minded environment where they can learn and realize their full potential. Hence, in this paper, we describe the program design, experiences, and lessons learned from this approach. We also provide recommendations for universities and organizations that may want to adapt our approach.
... Team working is an essential skill required in any university graduate and is particularly important in programmes aiming to impart computing knowledge (Shneiderman, 2016;Vivian et al., 2013). The stereotype of the solitary coder, wearing a hoodie and hunched over a machine with three (sometimes up to five) screens is becoming a thing of the past (Cheryan et al., 2015;Vera, 2021). Employers are keen to ensure that their computing employees can function in a team (Hiter, 2021;Riebe et al., 2010;Vogler et al., 2018), and some even use this as an interview differentiator. ...
Full-text available
One of the core aims of higher education degrees is to provide an environment for students to acquire essential skills that will help them in the workplace. Team working is one of those essential skill and it is also one that experience and research show is regularly resisted by students. This resistance can become even more amplified when the degree is delivered online, although some have pointed out that a good team provides much-needed community spirit and support in such environments. The purpose of this study is to review the delivery of a team assessment format that has been specifically designed for the online environment. The results presented provide insight into the student’s perspective on the delivery as well as the reflections of the instructors involved in the delivery. The overall outcome is positive for both parties and provides further guidance on implementation to ensure the pedagogical design continues to be viable. This includes insights into team composition, instructor involvement, and peer review scoring formats.
... This process could not be considered transparent or nor-linear since forms of gatekeeping shape communities' and individuals' efforts to stay and progress within the system of science. Geopolitical conditions, gender, age and experience have been considered crucial factors when determining access, stability and practices within the academic community (Cheryan et al., 2015;Wagner, 2008). ...
This chapter complements the introduction to the book “Data Cultures in Higher Education: Emerging Practices and the challenges ahead”. This chapter explores policy-making areas that impact higher education directly or indirectly. These areas are (a) transformation of higher education (from discourses of modernisation to the problem of managerialism, (b) open science and data connected to research practices and (c) the evolution of Artificial Intelligence (AI). In our view, the aforementioned areas support the initial theoretical assumption that data practices are based on several perspectives on how data are produced and used; hence, they encompass complexity. Moreover, this complexity sets the basis for different reactions from Higher Education Institutions (HEIs), which shape their situated institutional data cultures. Through the evidence of concrete evolution of policy-making around data in society and in education, our goal is to provide a frame to understand the relevance of the cases and proposals presented in each of the following chapters.
... This process could not be considered transparent or nor-linear since forms of gatekeeping shape communities' and individuals' efforts to stay and progress within the system of science. Geopolitical conditions, gender, age and experience have been considered crucial factors when determining access, stability and practices within the academic community (Cheryan et al., 2015;Wagner, 2008). ...
This chapter introduces the book “Data Cultures in Higher Education: Emerging Practices and the Challenges Ahead”. It is based on four sections that frame several chapters’ work and present it. In the first section, we briefly explain the problem of data and datafication in our contemporary society. To offer conceptual lenses, the idea of complexity is applied to the entropic and chaotic way with which datafication appears in several areas of higher education, triggering fragmented responses, ambiguity, and in the worst cases, harm. Hence, we offer the idea of higher education institutions’ data culture as potential apparatus to explore and understand the above-mentioned complexity. Data cultures characterise an institution and its tradition, people, narratives, and symbols around data and datafication. We purport here that awareness about their existence is crucial to engage in transformation to achieve fairness, equity, and even justice, beyond the subtle manipulation embedded in many of the assumptions behind data-intensive practices. Over these bases, we present the twelve central chapters composing this book, highlighting their perspectives and the way they contribute to study, act, and change data cultures. Finally, space is left to the book’s conclusions and the afterword by invited scholars as a point of arrival for the reader. Several threads conjoin in a web that will hopefully inspire future research and practice.
... Thus, while learning from failures of recruiting women through the conventional route, we should also look at unconventional routes as solutions with a potential for bringing a more diverse group into ICT work. Our study supports the often-repeated advice to develop the message about 'who belongs' in ICT to also include women (Cheryan et al, 2015;Master and Meltzoff, 2020), though this is also mainly limited to the conventional route. To capture a wider group of women including those who feel diverted away from the conventional route, we need to expand the message to include the vital role of ICT across a vast range of disciplines, industries and sectors not previously considered technological, including fields dominated by women. ...
... Further, authentic science learning often involves solving real life problems that help people in need of solutions. Such a focus on helping people is much more appealing to minorities than a programmatic emphasis on promoting learning focusing solely on individual STEM disciplines (Cheryan et al., 2015;Su & Rounds, 2015). In BIA we engaged students in authentic science learning of the therapies to help people suffering from disorders such as Parkinson's disease. ...
The call to increase student interest in science and related careers continues to receive national attention in the United States. While many current efforts have focused on infrastructure support and innovative pedagogies to better reach and engage students, research suggests that having a career role model can influence adolescents’ interest in and choices of science courses and career pathways. This exploratory study investigated the impact of a week-long online biotechnology program called Biotech in Action (BIA) that featured career role modeling and authentic science learning. Students were engaged in career modeling sessions with multiple professionals working in related STEM fields while learning life sciences within authentic biotechnology research contexts. In total, over 400 high school students participated in BIA. The results showed that students felt they developed a better understanding of the biotechnology field and became more cognizant about steps to achieve their future career goals after BIA. Many students reported that the interactions with career role models and learning about their educational and professional pathways helped demystify science career fields. Overall, this research provides new insights to curriculum designers and researchers on integrating career role modeling and authentic learning to spark and sustain student interest in science.
Why AI does not include gender in its agenda? The role of gender in AI, both as part of the community of agents creating such technologies, as well as part of the contents processed by such technologies is, by far, conflictive. Women have been, again, obliterated by this fundamental revolution of our century. Highly innovative and the first step in a series of future studies in this field, this book covers several voices, topics, and perspectives that allow the reader to understand the necessity to include into the AI research agenda such points of view and also to attract more women to this field. The multi-disciplinarity of the contributors, which uses plain language to show the current situation in this field, is a fundamental aspect of the value of this book. Any reader with a genuine interest in the present and future of AI should read it.
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Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates—with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, social science) than in the math-intensive fields in which they are underrepresented but in which the number of females holding assistant professorships is at least commensurate with (if not greater than) that of males. That is, invitations to interview for tenure-track positions in math-intensive fields—as well as actual employment offers—reveal that female PhD applicants fare at least as well as their male counterparts in math-intensive fields. Along these same lines, our analyses reveal that manuscript reviewing and grant funding are gender neutral: Male and female authors and principal investigators are equally likely to have their manuscripts accepted by journal editors and their grants funded, with only very occasional exceptions. There are no compelling sex differences in hours worked or average citations per publication, but there is an overall male advantage in productivity. We attempt to reconcile these results amid the disparate claims made regarding their causes, examining sex differences in citations, hours worked, and interests. We conclude by suggesting that although in the past, gender discrimination was an important cause of women’s underrepresentation in scientific academic careers, this claim has continued to be invoked after it has ceased being a valid cause of women’s underrepresentation in math-intensive fields. Consequently, current barriers to women’s full participation in mathematically intensive academic science fields are rooted in pre-college factors and the subsequent likelihood of majoring in these fields, and future research should focus on these barriers rather than misdirecting attention toward historical barriers that no longer account for women’s underrepresentation in academic science.
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Women's participation and attitudes to talent Some scientific disciplines have lower percentages of women in academia than others. Leslie et al. hypothesized that general attitudes about the discipline would reflect the representation of women in those fields (see the Perspective by Penner). Surveys revealed that some fields are believed to require attributes such as brilliance and genius, whereas other fields are believed to require more empathy or hard work. In fields where people thought that raw talent was required, academic departments had lower percentages of women. Science , this issue p. 262 ; see also p. 234
An important source of people's perceptions of their performance, and potential errors in those perceptions, are chronic views people hold regarding their abilities. In support of this observation, manipulating people's general views of their ability, or altering which view seemed most relevant to a task, changed performance estimates independently of any impact on actual performance. A final study extended this analysis to why women disproportionately avoid careers in science. Women performed equally to men on a science quiz, yet underestimated their performance because they thought less of their general scientific reasoning ability than did men. They, consequently, were more likely to refuse to enter a science competition.
We recount some of the most significant and colorful findings of our four-year study of gender issues in the undergraduate computer science program at Carnegie Mellon. We also discuss the subsequent dramatic increase in the number of women in the program. We conclude with recommendations for the most generally useful and effective actions departments can take to attract and retain female students.
Between 1972 and 1974 the Study of Mathematically Precocious Youth (SMPY) identified over 2,000 7th and 8th graders who scored as well as a national sample of 11th and 12th grade females on the College Board’s Scholastic Aptitude Test (SAT) Mathematics or Verbal tests. A substantial sex difference in mathematical reasoning ability was found (Benbow & Stanley, 1980b, 1981). The consequences and development of this sex difference over the following 5 years were investigated longitudinally. Over 91 percent (1,996 out of 2,188 SMPY students) participated. This study established that the sex difference persisted over several years and was related to subsequent sex differences in mathematics achievement. The sex difference in mathematics did not reflect differential mathematics course taking. The abilities of males developed more rapidly than those of females. Sex differences favoring males were found in participation in mathematics, performance on the SAT-M, and taking of and performance on mathematics achievement and Advanced Placement Program examinations. SMPY females received better grades in their mathematics courses than SMPY males did. Few significant sex differences were found in attitudes toward mathematics.
In two experiments, we examined how teacher gender and stereotype threat cues affected adolescents' self-reported concerns about being negatively stereotyped in computer science courses. High-school students (Experiment 1: N = 218; Experiment 2:N = 193) read about two computer science courses, one with a competent male teacher and one with a competent female teacher, and were randomly assigned to one of three experimental conditions. In the stereotype threat condition, they read a paragraph that introduced negative stereotypes about girls' performance; in the no gender difference condition, they read a paragraph that countered negative stereotypes; and in the baseline control condition, they read neither paragraph. In both experiments, girls reported more concerns about being negatively stereotyped than boys when the teacher was male versus female, and this effect was specifically driven by significant differences in the stereotype threat condition. When situational cues are threatening, female teachers (compared to male teachers) reduce girls' concerns about being negatively stereotyped, with implications for both theories of identity and educational practice.
A general theory of domain identification is used to describe achievement barriers still faced by women in advanced quantitative areas and by African Americans in school. The theory assumes that sustained school success requires identification with school and its subdomains; that societal pressures on these groups (e.g., economic disadvantage, gender roles) can frustrate this identification; and that in school domains where these groups are negatively stereotyped, those who have become domain identified face the further barrier of stereotype threat, the threat that others' judgments or their own actions will negatively stereotype them in the domain. Research shows that this threat dramatically depresses the standardized test performance of women and African Americans who are in the academic vanguard of their groups (offering a new interpretation of group differences in standardized test performance), that it causes disidentification with school, and that practices that reduce this threat can reduce these negative effects.
Controversy and fanfare accompanied the announcement in 2010 by Mattel, Inc. of the Barbie® doll's 126th career - computer engineer. Even though women have been and still are in a minority in the information technology (IT) and computer science (CS) fields, enough women voted for the computer engineer as the next career for Barbie® on Mattel's website that it won the overall vote, while the winning choice voted for by young girls was news anchorwoman. The discrepancy resulted in Mattel producing Barbie® dolls in both careers. This paper reports the results of a survey completed by women in the IT and CS fields regarding their attitudes about and purchases of Computer Engineer Barbie®.