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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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HYPOTHESIS AND THEORY ARTICLE
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,
USA
Reviewed by:
Andrei Cimpian, University of Illinois,
USA
Toni Schmader, University of British
Columbia, Canada
*Correspondence:
Sapna Cheryan, Department of
Psychology, University of Washington,
Box 351525, Seattle, WA 98195, USA
e-mail: scheryan@uw.edu
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
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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
behind?
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
them.
DUAL STEREOTYPES AND GENDER DISPARITIES
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
STEM.
THE ROLE OF STEREOTYPES EARLY IN THE PIPELINE
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.
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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.
WHAT IS THE CONTENT OF COMPUTER SCIENCE AND
ENGINEERING STEREOTYPES?
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
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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
engineering.
TRANSMISSION CHANNELS FOR STEREOTYPES ABOUT
COMPUTER SCIENCE AND ENGINEERING
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.
STEREOTYPES TRANSMITTED THROUGH THE MEDIA
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.
STEREOTYPES TRANSMITTED BY NARROW
CHARACTERIZATIONS OF PEOPLE IN THE 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 engineeryourlife.org 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
stereotypes.
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.
STEREOTYPES TRANSMITTED THROUGH ENVIRONMENTS
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.,
2009).
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
section.
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.
THE IMPORTANCE OF VARIABILITY AND DIVERSIFYING
PORTRAYALS OF COMPUTER SCIENCE AND ENGINEERING
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
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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.,
2011).
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.
CONCLUSION: CONTRIBUTIONS TO THEORY AND PRACTICE
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
them.
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.
ACKNOWLEDGMENTS
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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Frontiers in Psychology |Developmental Psychology February 2015 |Volume 6 |Article 49 |8
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Chapter
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). ...
Chapter
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. ...
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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.
Book
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
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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.
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