published: 10 July 2019
Frontiers in Education | www.frontiersin.org 1July 2019 | Volume 4 | Article 60
Universität der Bundeswehr
Freie Universität Berlin, Germany
Jessica Lauren Degol,
Pennsylvania State University,
This article was submitted to
Frontiers in Education
Received: 28 December 2018
Accepted: 11 June 2019
Published: 10 July 2019
Makarova E, Aeschlimann B and
Herzog W (2019) The Gender Gap in
STEM Fields: The Impact of the
Gender Stereotype of Math and
Science on Secondary Students’
Career Aspirations. Front. Educ. 4:60.
The Gender Gap in STEM Fields: The
Impact of the Gender Stereotype of
Math and Science on Secondary
Students’ Career Aspirations
Elena Makarova 1
2and Walter Herzog 3
1Institute for Educational Sciences, University of Basel, Basel, Switzerland, 2Swiss Federal Institute for Vocational Education
and Training SFIVET, Bern, Switzerland, 3Institute of Educational Science, University of Bern, Bern, Switzerland
Studies have repeatedly reported that math and science are perceived as male domains,
and scientists as predominantly male. However, the impact ofthegenderimageofschool
science subjects on young people’s career choice has not yet been analyzed. This paper
investigates the impact of the masculinity image of three school subjects—chemistry,
mathematics, and physics—on secondary students’ career aspirations in STEM ﬁelds.
The data originated from a cross-sectional study among 1’364Swisssecondaryschool
students who were close to obtaining their matriculation diploma. By means of a
standardized survey, data on students’ perception of masculinity of science school
subjects were collected using semantic differentials. The results indicate that for both
sexes, math has the strongest masculinity attribution, followed by physics as second,
and, ﬁnally, chemistry with the lowest masculinity attribution. With respect to gender
differences, our ﬁndings have shown that among female students, the attribution of
masculinity to the three school subjects does not differ signiﬁcantly, meaning that female
students rated all subjects similarly strongly as masculine. Within the group of male
students however, the attribution of masculinity to math compared to chemistry and
physics differs signiﬁcantly, whereas the attribution of masculinity to chemistry and
physics does not. Our ﬁndings also suggest that gender-science stereotypes of math
and science can potentially inﬂuence young women’s and men’saspirationstoenrollina
STEM major at university by showing that a less pronounced masculine image of science
has the potential to increase the likelihood of STEM career aspirations. Finally, the paper
discusses ways of changing the image of math and science in thecontextofsecondary
education in order to overcome the disparities between females and males in STEM.
Keywords: gender, career aspirations, science, mathematics,secondaryschoolstudents
Gender segregation in the vocational orientation of adolescents has been well documented for
decades in most OECD countries (OECD, 2006, 2012). The persistence of gendered paths in
career choices has recently been reﬂected in the current Global Gender Gap Report of the
World Economic Forum (WEF), which states that on average men are underrepresented in
the ﬁelds of education, health and welfare whereas women are underrepresented in the STEM
Makarova et al. The Gender Gap in STEM Fields
ﬁelds (WEF, 2017, p. 31). Moreover, on the basis of
the occupational aspirations of 15-year-old adolescents,
the prognosis for change in gender-based disparities in
occupational and academic choices suggests that gender
segregation in the education and labor market will remain
persistent (OECD, 2017).
The persistence of horizontal gender segregation in
educational and occupational ﬁelds contributes decisively to the
spread of gender-stereotypic beliefs about a natural ﬁt of women
in careers in more expressive and human-centered ﬁelds and
men in technical and math-intensive ﬁelds (Charles and Bradley,
2009). Gender stereotypes are part of a broader belief system
that includes attitudes toward female and male family roles,
female and male occupations, and gender-associated perceptions
of the self. As bipolar constructs, gender stereotypes imply that
what is masculine is not feminine and vice versa (Deaux and
LaFrance, 1998; Worell, 2001; Renfrow and Howard, 2013).
The social role theory (Eagly and Wood, 2012)suggeststhat
gender roles and their occupants are highly visible in everyday
contexts and that gender stereotypes emerge in response to the
observation of women and men in diﬀerent social roles and in
role-linked activities related to occupational choices (Koenig
and Eagly, 2014). This theoretical assumption was conﬁrmed
in a study by Miller et al. (2015), which analyzed how women’s
enrollment in science courses relates to the gender-science
stereotype. Based on a survey of about 3,50,000 participants
in 66 nations, this study concluded that explicit and implicit
national gender-science stereotypes were weaker in countries
with a higher female enrollment in tertiary science education.
This study also demonstrated that stereotypes about science were
strongly gendered, even in countries with high overall gender
equity. In addition, a meta-analysis of two major international
data sets—“Trends in International Mathematics and Science
Study” (TIMMS) and the “Programme for International Student
Assessment” (PISA)—has conﬁrmed that gender equity in
education is important not only for girls’ math achievement
but also for girls’ self-conﬁdence and valuing of mathematics
(Else-Quest et al., 2010). Furthermore, a cross-national data
analysis has indicated that gender diﬀerences in math are closely
related to cultural variations in opportunity structures for girls
and women, in particular to gender equity in school enrollment,
women’s share of research jobs, and women’s parliamentary
representation (ibid., p. 103). Accordingly, the low proportion
of women in STEM leads to the spread of a gender stereotypical
image of math and science as a male domain and beliefs about
male supremacy in technical and math-intensive ﬁelds. In turn,
such beliefs aﬀect young people’s career choices, leading to a
mutual reinforcement of gender stereotypes, and gender gaps in
career related interests and choices (Nosek et al., 2009, p. 10,596).
In Switzerland gender segregation is also persistent and
is especially noticeable in the STEM ﬁeld (FSO, 2013). In
educational tracks at the universities of applied science, with
only 21.3% of women enrolled in STEM courses in academic
year 2017–2018. However, some STEM ﬁelds are more strongly
gender segregated than others. The lowest proportion of women
is in the ﬁelds of informatics (10.4%) and technology (8.5%),
whereas in the ﬁelds of chemistry and life-sciences the proportion
of women is considerably higher (43.7%) (FSO, 2019a). In
secondary education, gender is almost balanced in chemistry and
biology (girls 18.4% and boys 20.5%) as a subject of specialization,
whereas considerably more boys (18.4%) than girls (4.4%)
decided to specialize in the subjects math and physics (FSO,
2019b). It is, thus, important to distinguish between diﬀerent
STEM disciplines and subjects when addressing the gender gap
in the STEM ﬁeld (Rosser, 2012; Ertl et al., 2017).
Following this notion, our study aimed to analyze the gender
stereotype of school science subjects among female and male
students and the impact of gender-science stereotypes on the career
aspirations of young people. The ultimate goal of our study is to
provide a more comprehensive understanding of gender equity
THE GENDER STEREOTYPE OF MATH
The gender stereotype of math and science has been analyzed
via a variety of quantitative and qualitative methods (review
in Makarova and Herzog, 2015). Among those are the Draw-
A-Scientist Test (DAST) (e.g., Chambers, 1983; Finson, 2002;
Scherz and Oren, 2006), the Implicit Association Test (IAT)
(e.g., Greenwald et al., 1998; Nosek et al., 2002, 2009), explicit
stereotype assessments using attitude questionnaires (e.g., Kessels,
2005), semantic diﬀerential assessments (e.g., Herzog et al., 1998;
Makarova and Herzog, 2015), and individual or group interviews
(e.g., Archer et al., 2010).
Studies that applied the DAST method reported that students
from kindergarten to high school perceive a scientist as a male
person. The children’s drawings contained very few portrayalsof
female scientists and these few drawings were mostly drawn by
female students. For example, in a study among students from
kindergarten through ﬁfth grade there were only 28 pictures
of a female scientist out of 4,807, and all of these 28 drawings
were drawn by girls (Chambers, 1983); in a study surveying
students in grades 2–12 only 135 pictures out of 1,600 displayed
female scientists and only six out of 135 pictures of a female
scientist were drawn by male students (Fort and Varney, 1989);
in a study among students of 9–12 years of age, there were
only 72 pictures of a female scientist out of 223, and of those
72, only 13 pictures were drawn by male students (Huber and
Burton, 1995). The precise way in which a scientist was pictured
by middle school students was reported in a study by Scherz
and Oren (2006, p. 977): “The common image was that of a
scientist as a bespectacled male with unkempt hair in a white
lab-coat.” Moreover, the following quote from a study by Mead
and Metraux (1957) on high-school students’ image of a scientist
highlights how persistent the scientist-stereotype remains over
decades. The image of a scientist is depicted in students’ essays
as “a man who wears a white coat and works in a laboratory.
He is elderly or middle aged and wears glasses .. . He may
wear a beard, may be unshaven and unkempt” (Mead and
Metraux, 1957, p. 386). Finally, the most recent meta-analysis
of ﬁve decades of U.S. DAST studies based on 78 studies (N=
20,860) among children grades K-12, shows a growth in children’s
depictions of female scientists in later decades. However, the
more female scientist appeared only in drawings by young
Frontiers in Education | www.frontiersin.org 2July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
children, but science was still associated with men among older
children (Miller et al., 2018). The authors conclude that despite
the increase of women’s representation in science over the last
decades, children still observe more male than female scientists
in their social environments (Miller et al., 2018, p. 1,943).
Furthermore, research on gender stereotypes has revealed
that science is not only associated with a male person, but
that masculine traits are also attributed to it. A study by
Archer et al. (2010) suggested that although young children
do not have profound knowledge about science subjects, they
attribute masculine traits to science at an early age. In the
same vein, a study by Cvencek et al. (2011) reported that as
early as second grade children perceive that math is a male
domain, demonstrating the American cultural stereotype. In
addition, a study among high school students reported that
better performance in STEM subjects was attributed to boys,
and masculine traits to a person who works as a scientist
(Hand et al., 2017). Another study among school children
and university students by Weinreich-Haste (1981) assessed the
gender image of diﬀerent academic subjects using ratings on
a six-point masculine-feminine scale. The study reported that
math, physics and chemistry had the strongest connotation as
masculine academic subjects. Moreover, it showed that science
subjects were not only rated as masculine but also associatedwith
being hard, complex, based on thinking rather than on feelings
(Weinreich-Haste, 1981, p. 220f.). In contrast, a study on gender
perception of school subjects among students aged 11–12 years,
which applied a seven-point masculine-feminine scale, reported
that while physics was rated as signiﬁcantly more masculine,
chemistry and mathematics were rated as neither masculine nor
feminine (Archer and MacRae, 1991).
To summarize, we can state that the male stereotype of
science and of a scientist is persistent and appears as early as
in kindergarten age, while the association of science with men
is especially persistent among older children. Research has also
shown that students predominantly perceive science subjects
(math, physics, and chemistry) as a male domain, although
ﬁndings do not provide a clear picture as to which of these
subjects is more strongly associated with male gender. The reason
is the very broad age-range of students (K-12) across reported
studies, lack of comparison of gender stereotypes of diﬀerent
school subjects within one study, diﬀerent methodology (explicit
and implicit assessment) used to assess gender stereotypes of
science, as well as the time span between ﬁndings of diﬀerent
studies. Thus, further research on the perception of masculinity
of chemistry, math, and physics among school students is needed
to gain deeper insight into the impact of the gender stereotypes
of science subjects on STEM-career aspirations.
GENDER DIFFERENCES IN THE
PERCEPTION OF GENDER-SCIENCE
Research on gender-science stereotypes has illustrated diﬀerences
between female and male youth with respect to the endorsement
of stereotypic beliefs about STEM. A study among primary school
students illustrated that stereotypical beliefs that STEM school
subjects are more suitable for boys than for girls were more
strongly endorsed by boys than by girls. Moreover, this study
has shown that students with stereotype-consistent interest in
STEM-related school subjects were particularly likely to endorse
gender-science stereotypes. Consequently, especially boys who
were highly interested and girls who were relatively uninterested
in STEM-related school subjects were more likely to believe that
STEM school subjects constitute a male domain (BlaŽev et al.,
2017). In line with this, a study among high school students has
shown that girls reported lower self-eﬃcacy in math and science
compared to boys (Hand et al., 2017). Finally, a study among
ﬁrst-year university students indicated that negative stereotypes
of women’s engineering and mathematical ability were more
strongly endorsed among male students, whereas female students
were more likely to report higher perceptions of their engineering
abilities (Jones et al., 2013).
With respect to the perception of diﬀerent STEM disciplines,
studies among adolescent youth have shown that female students
show a more pronounced gender stereotype for math compared
to male students, who are less likely to exhibit implicit gender-
stereotypic associations (Steﬀens et al., 2010). In line with these
ﬁndings, a study by Nosek et al. (2002, p. 44) reported that even
women who had selected math-intensive majors had diﬃculties
in associating math with themselves because they associated
math with the male gender. Also, studies that analyzed the
gender stereotype of physics found that, among high school
students, being interested in physics was associated with the
male gender (Kessels, 2005; Kessels et al., 2006)andthat,
among girls, being interested in physics endangered their self-
identiﬁcation with the female gender (Kessels et al., 2006).
Furthermore, a typical teacher of mathematics and physics was
imagined to be a man (Kessels and Taconis, 2012). Finally, a
study among secondary school students in Switzerland showed
that, among female students, the semantic proﬁle of math and
physics correlated negatively with the semantic proﬁle of the
female gender, whereas the semantic attributes of chemistry were
signiﬁcantly related neither to the male nor to the female gender.
From the male students’ point of view the semantic proﬁle
of math correlated negatively with the semantic proﬁle of the
female gender, whereas the semantic attributes of chemistry and
physics were positively related to the semantic proﬁle of the
male gender. Whereas, the female gender was strongly associated
with traits such as soft, playful, soulful, dreamy, lenient, frail,
and ﬂexible, among the semantic traits associated with math
and physics were attributes such as hard, serious, distant, sober,
strict, robust, and rigid. Overall, this study has shown that
among the three school subjects analyzed in the study, math and
physics were either negatively associated with female or positively
associated with male gender. In contrast, chemistry was the least
gender stereotyped because among female students there were no
signiﬁcant associations of the term chemistry with either gender
term and among male students no negative association with the
term woman (Makarova and Herzog, 2015). These ﬁndings are
interesting in light of students’ preference for their subject of
specialization in secondary schools in Switzerland (FSO, 2019b)
Frontiers in Education | www.frontiersin.org 3July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
showing that chemistry is chosen almost equally often by boys
and girls, whereas math and physics are largely avoided by girls as
subjects of specialization. Accordingly, students’ gender-related
perception of diﬀerent science subjects may diﬀerently impact
their preferences of STEM subjects at school and vice versa.
To summarize, we can state that female and male students
indicate diﬀerent patterns of gender-science stereotype. It seems
that male participants show more endorsement of the gender-
science stereotype by regarding STEM subjects as more suitable
for boys and attributing less abilities in the STEM disciplines
to the female gender compared to the male gender. At the
same time, female participants are more likely to associate math
and science more strongly with the male gender and masculine
traits than with the female gender and feminine traits. Finally,
previous research has shown that school science subjects diﬀer
with respect to their gender-related connotation, and indicating
that chemistry has the least pronounced masculine image among
secondary school students.
GENDER-SCIENCE STEREOTYPE AND
CAREER ASPIRATIONS IN STEM
The impact of the gender-science stereotype on students’ interest
in STEM subjects and their aspirations to pursue a career in
STEM ﬁelds has been addressed from diﬀerent perspectives.
Based on Eccles’ expectancy-value model, which highlights
the impact of culturally based stereotypes and identity-related
constructs on educational and occupational choices (Eccles, 1994;
Eccles and Wigﬁeld, 2002), a number of studies have shown that
academic self-concept and subject interests are among the most
relevant determinants in students’ selection of secondary school
majors (Nagy et al., 2008). Similar mechanisms seem to be crucial
for career choice or choice of a major in higher education (Nagy
et al., 2006). A recent study among female students in STEM
subjects with a low proportion of females revealed that gender
stereotypes have a negative impact on students’ STEM-speciﬁc
self-concept even among students with good grades in STEM
(Ertl et al., 2017).
According to the theoretical framework of Gottfredson (2002,
2005), occupational aspirations are incorporated in the individual
self-image developed during socialization from early childhood
through adolescence. The process of developing occupational
aspirations is embedded in the comparison of one’s self-image
with the image of an occupation and one’s judgment about the
match between the two. In this process, the gender image of
an occupation is especially crucial for career choice, because
the “wrong” sex type of an occupation is more fundamental to
self-concept than the prestige of an occupation or individual
interests. Applying Gottfredson’s theory, the signiﬁcant impact
of the gender image of an occupation on the process of career
choice was conﬁrmed in a number of studies (Ratschinski, 2009;
Bubany and Hansen, 2011). Moreover, research suggests that girls
are more likely to narrow their occupational choices because they
perceive particular occupations as inappropriate for their gender.
Accordingly, girls tend to shift their occupational aspirations to
gender-typical occupational expectations more strongly than do
boys. At the same time, boys’ perceptions of occupations appear
to be more gender-stereotypical (Hartung et al., 2005).
Research focusing on self-to-prototype similarity suggests that
the lack of similarity between the self and an academic subject is
linked to a lower probability of liking this subject or choosingthis
academic subject as a major (Kessels, 2005; Kessels et al., 2006;
Taconi s a n d Kessel s , 2 009). Moreover, the perceived closeness
between the self and a school subject was predictive for youths’
career choice intentions (Hannover and Kessels, 2004; Kessels
et al., 2006). In the same vein, a study among ninth and tenth-
grade students by Neuhaus and Borowski (2018) investigated
whether the greater self-to-prototype similarity impacts students’
interest in coding courses. This study revealed that, under the
condition that course descriptions were related to communal
goals, girls showed greater interest in learning to code compare
to the agentic-goal condition of the course description (Neuhaus
and Borowski, 2018, p. 233).
Likewise, a study among students and faculty reported that
agentic traits are more strongly associated with success in science
than communal traits, discouraging women from pursuing a
science career (Ramsey, 2017). Another study among ﬁrst-year
undergraduate students illustrated that implicit stereotypesof
science completely accounted for a gap in male and female
students’ interests to pursue science. Especially the academic
aspirations of women who strongly identiﬁed as female were
aﬀected by the gender stereotypic image of science (Lane et al.,
2012). In line with this, a study among ﬁrst-year women
engineering students reported that engineering identiﬁcation
was a signiﬁcant predictor of persistence in engineering, and
that this relationship was stronger for women than men (Jones
et al., 2013). Finally, a study among undergraduate science
majors demonstrated that a stronger gender-science stereotype
has a diminishing eﬀect on identiﬁcation with science and
science career aspirations among women, whereas, among men,
a stronger gender-science stereotype boosts their identiﬁcation
with science and their career aspirations in science ﬁelds (Cundiﬀ
et al., 2013).
To summarize, we can state that gender-science stereotyping
has been shown to hinder the self-identiﬁcation of young women
with STEM academic subjects and ﬁelds and also to negatively
aﬀect their self-concept and their subject interests. These, in turn,
hinder female students from opting for a science major and
pursuing a career in science. For male students, gender-science
stereotyping seems to have the opposite eﬀect and, thus, boosts
their career aspirations in STEM.
FOCUS OF THE STUDY
Given that previous research has often focused on gender-
science stereotypes of science in general or on stereotypical
beliefs about single STEM disciplines, our study contributes
to previous research by simultaneously analyzing the gender
stereotype of diﬀerent school science subjects—chemistry, math,
and physics—among female and male students. These three
science subjects were chosen because females are strongly
underrepresented in math and physics within the educational
Frontiers in Education | www.frontiersin.org 4July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
sector and career ﬁelds, whereas chemistry has a more balanced
gender ratio. This allows us to investigate the impact of gender-
science stereotypes of diﬀerent science subjects on students’
aspirations to study STEM. In view of the theoretical and
empirical framework of the study, we deﬁne the gender
stereotype of three school subjects as the extent of association
of each school subject with masculine traits (see section
Measurements; masculinity index).
In terms of hypotheses, we ﬁrstly expected diﬀerences with
respect to the degree of masculinity which students attributeto
chemistry, math, and physics. We hypothesized that chemistry
would be ascribed the lowest degree of masculinity compared to
math and physics.
Secondly, we expected gender diﬀerences among secondary
school students in the association of chemistry, math, and physics
with male gender. We hypothesized that this association of the
three science subjects with masculine traits would be stronger
among female students.
Thirdly, we expected that the gender stereotype of math
and science would aﬀect female and male secondary school
students’ aspirations to enroll in a STEM major at university.
We hypothesized that to the extent students conceive of STEM-
school subjects as masculine they would be less inclined to aspire
to enroll in a STEM major at university. We further hypothesized
that stereotyping science subjects as masculine would have a
greater negative impact on the STEM aspirations of female than
The study presented was part of the research project Gender
atypical career choices of young women, a project embedded in
the Swiss National Science Foundation’s Research Program on
“Gender Equality” (NRP 60). The study is based on quantitative
data which originated from a standardized survey of 1,364
students in Swiss-German-speaking secondary schools. The
study was carried out following the ethical principles and codes
of the Faculty of Humanities at the University of Bern, which
are based on international ethics codes (e.g., of the American
Sociological Association and of the American Psychological
Association). Accordingly, approval by an ethics authority was
not required. Students were informed about the research project
and participated in the survey voluntarily. Participants? Informed
consent was implied through survey completion; therefore, they
were not required to provide written consent to participate.
Written parental consent was not necessary either, because all
students had reached legal adulthood and could decide for
themselves. After the survey all data were anonymized.
The surveyed students were close to obtaining their
matriculation diploma (i.e., school leaving certiﬁcate), which
in Switzerland permits entry into tertiary education. The
participants were on average 19 years old (SD =1.0). With regard
to sex, the percentage of female students (54.1%) was somewhat
higher than that of male students (45.9%).
Data on students’ perception of the gender image of the
school subjects chemistry, math, and physics were collected
using semantic diﬀerentials (Makarova and Herzog, 2015). The
semantic diﬀerential is one of the most popular techniques of
explicit attitude assessment (Millon et al., 2003). An explicit
measurement of the gender stereotype of science subjects was
chosen over an implicit stereotype test, because the study focuses
on the salient gender stereotypes of those subjects (Millon et al.,
2003, p. 356). The semantic diﬀerential uses bipolar scales with
contrasting adjectives at each end to measure people’s reactions
to stimulus words and concepts (Heise, 1970, p. 235). The
methodological advantage of the semantic diﬀerential scale is
that it highly adaptable in assessing respondents’ connotative
association with any concept (Osgood et al., 1957; Heise, 1970).
The basic assumption of the semantic diﬀerential is that attitudes
toward two associated concepts tend to converge and toward two
dissociated (contrasted) constructs tend to diverge (Heise, 1970,
p. 249). In our study attitudes toward gender and science were
measured using semantic diﬀerentials consisting of 25 pairs of
adjectives with semantically opposite meanings (e.g., hard—soft,
strong—weak, robust—frail) to assess the connotations of the
four terms man, chemistry, math, and physics on a seven-point
scale (1 =greatly, 2 =fairly, 3 =somewhat, 4 =neither, 5 =
somewhat, 6 =fairly, 7 =greatly). This instrument is based on
the original scale (Osgood et al., 1957) which was initially adapted
to the German language by Hofstätter (1973) and then validated
in Switzerland in two studies on the gender stereotype of school
subjects (Herzog et al., 1998; Makarova and Herzog, 2015).
The student sample was divided into groups, with each
group completing the semantic diﬀerential for one subject term
and for the man term: chemistry and man (n=406), math
and man (n=512) and physics and man (n=446). In
order to avoid response bias, the semantic diﬀerential of the
subject was introduced at the beginning of the questionnaire
and the semantic diﬀerential of the term man at the end of
the questionnaire. On the basis of these data we calculated
proﬁle from the corresponding items of each subject proﬁle and
summing them up to a sum score for each student. At the end
of this procedure one value for each student was calculated. For
easier interpretation, this value was reversed; a negative value
was transformed into a positive value and a positive value into
a negative value. Accordingly, the masculinity index expresses
the diﬀerentiation between high masculinity (low discrepancy
between the proﬁles man and subject; max. =+6) and low
masculinity (high discrepancy between the proﬁles man and
subject; min. =−6). For example, a score of 5 on the masculinity
index, indicates that the semantic proﬁle of the respective subject
(chemistry, math, or physics) and the semantic proﬁle of the term
man are very similar, meaning that the discrepancy between the
two semantic proﬁles is low. Figure 1 illustrates our calculation.
Moreover, the masculinity index is approximately normally
distributed (Kurtosis =2.09, SE =0.13; Skewness =0.47, SD =
0.07) (George and Mallery, 2016).
Frontiers in Education | www.frontiersin.org 5July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
FIGURE 1 | Masculinity index of chemistry, math, and physics.
STEM Field Study Choice
To assess the ﬁeld of study choice, the secondary school
students were asked about their subject preference for study at a
university or at a university of applied sciences after the successful
completion of secondary school. The answers were coded by the
gender-type of the ﬁeld of study, based on the gender distribution
of master’s degrees obtained at Swiss universities in the year
2010 (FSO, 2012). A ﬁeld of study was labeled as female-atypical
(male-typical) when the proportion of women who received a
master’s degree in that ﬁeld was below 30 per cent. In our sample,
Mathematics, Statistics, IT, the Natural Sciences and Engineering
fall into this category. Since all listed ﬁelds of study can be
assigned to the STEM area, the category is henceforth labeled
STEM study choice. All other ﬁelds of study were assigned to the
category “non-STEM study choice.” The multivariate analyses
were conducted with the dichotomous variable STEM ﬁeld study
choice (STEM ﬁeld study choice =category 1; non-STEM study
choice =reference category 0).
Attribution of Masculinity to Chemistry,
Math, and Physics Among Secondary
The attribution of masculinity to the three science subjects
among female and male students was subjected to a two-way
ANOVA (school subject and students’ sex). The overall model
yielded an F ratio of F(5, 1,355) =15.83,p≤0.001. With respect
to the degree of masculinity attributed to the three science
subjects, our analysis of variance indicated signiﬁcant diﬀerences
F(2, 1,355) =10.76, p≤0.001. Post-hoc comparisons (Bonferroni)
has shown that the attribution of masculinity diﬀers signiﬁcantly
between math and chemistry (p≤0.001) and between math
and physics (p≤0.05). There were no signiﬁcant diﬀerences
in the attribution of masculinity to chemistry and physics. The
TAB LE 1 | Descriptive statistics.
All Female Male
chemistry (min: −2.4,
Masculinity of math
(min: −1.76, max: 2.36)
Masculinity of physics
(min: −2.08, max: 3.08)
M=mean, SD =standard deviation.
mean values indicated that math has the strongest attribution of
masculinity, followed by physics as second, and ﬁnally chemistry
with the lowest attribution of masculinity (see Tab l e 1 ). With
regard to the sex diﬀerences in the attribution of masculinity, our
analysis of variance yielded signiﬁcant diﬀerences between female
and male students F(1, 1,355) =63.20, p≤0.001. The ascription of
masculinity to the three science subjects turned out to be stronger
among female than among male students (see Tab le 1 ).
The interaction eﬀect between two factors school subject
and students’ sex was non-signiﬁcant F(2, 1,355) =2.34, p=
ns. Nevertheless, to explore the interaction term in more detail
we analyzed the attribution of masculinity to the three science
subjects within the group of female and that of male students.
For this purpose, the conﬁdence intervals for the three science
subjects were calculated. Within the group of female students,
the attribution of masculinity to the three school subjects
does not diﬀer signiﬁcantly, meaning that female students
rated all subjects similarly as strongly masculine [95% CIs:
chemistry [0.19, 0.36], math [0.30, 0.46], and physics [0.23, 0.39]].
Within the group of male students, however, the attribution of
masculinity to math and chemistry [95% CIs [0.12, 0.27], [−0.20,
0.02]] as well as to math and physics [[0.12, 0.27], [−0.07, 0.09]]
Frontiers in Education | www.frontiersin.org 6July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
TAB LE 2 | Study choice.
All Female Male Interaction
of gender ×
Study choice N=1,618 n=873 n=742 x2=58.26***
STEM choice 16.6% 10.1% 24.3%
NON-STEM choice 83.4% 89.9% 75.7%
The interaction of gender ×study choice is signiﬁcant at the ***p≤0.001 level, x2=
FIGURE 2 | Masculinity index of chemistry and career aspirations.
diﬀers signiﬁcantly, whereas the attribution of masculinityto
chemistry and physics does not [[−0.20, 0.02], [−0.07, 0.09]].
Gender Stereotype of Chemistry, Math and
Physics and Students’ Study Aspirations
First, we analyzed career aspirations among the secondary school
students by carrying out x2-test (chi-square test)forthebinomial
dependent variable STEM study choice (see Tab l e 2). Overall, one
sixth of all students aspired to having a STEM major (16.6%).
However, aspirations to study STEM subjects were not equally
distributed between men and women. While among men every
fourth student (24.3%) planned to study STEM, among women
only every tenth student (10.1%) was interested in STEM studies.
Second, we analyzed the attribution of masculinity to school
subjects (chemistry, physics, and math) among secondary school
students who had chosen a STEM compared to those students
who had chosen a non-STEM major (Figures 2–4).
Our analysis reveals the following ﬁndings for each subject:
•Chemistry (Figure 2): With respect to career aspirations of
young women, our results show that female students who
opt for a non-STEM study major connotated chemistry
signiﬁcantly strongly as masculine compared to young women
with a STEM career choice (p≤0.01). Among young
men there were no signiﬁcant diﬀerences in the attribution
FIGURE 3 | Masculinity index of math and career aspirations.
FIGURE 4 | Masculinity index of physics and career aspirations.
of masculinity to the subject chemistry between students
who had chosen STEM and those who had chosen another
•Math (Figure 3): Our results show that among female and
male students who had potentially chosen a non-STEM major,
the attribution of masculinity to math was signiﬁcantly higher
compared to youth with a STEM career choice (female: p≤
0.05; male: p≤0.001).
•Physics (Figure 4): Considering female students who had
potentially chosen a non-STEM study major, physics was
signiﬁcantly more highly stereotyped as a masculine subject
compared to young women with a STEM career choice
(p≤0.001). Among young men there were no signiﬁcant
diﬀerences in the attribution of masculinity to the subject
physics between male students who had chosen STEM and
those who had chosen another study ﬁeld.
Frontiers in Education | www.frontiersin.org 7July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
To sum up, young women who aspire to study a STEM major
stereotype the three subjects as less strongly masculine compared
to young women who aspire to study non-STEM subjects.
Among young men, only math was rated as highly masculine
among those students who had chosen a non-STEM study
program. Thus, for young women as well as for young men
with a non-STEM career choice, math has a highly masculine
image. What is interesting is that even young women who opt
for a STEM ﬁeld rate the subjects—except physics—as masculine,
though only slightly.
Finally, Generalized Linear Models (GzLM) were estimated
(McCullagh and Nelder, 1989) to shed light on the impact
of the gender image of math and science on the likelihood
that female and male students aspire for a STEM ﬁeld of
study. The procedure modeled the choice of a STEM study
major as the response category, with all other study ﬁelds
as the reference category (non-STEM). We aggregated the
masculinity index for math and the two science subjects
for the model of female students, because separate models
showed nearly the same eﬀect for each individual subject,
and therefore we could increase the power of the model in
terms of cases. The model for male students included only
the masculinity index of math as a predictor, since there
was no signiﬁcant eﬀect for science subjects between young
men who had chosen STEM and non-STEM ones (see also
Figures 2,4). We report the Exp(β), which indicates the
likelihood of an occurrence of the tested eﬀect. If the value
is below 1, the likelihood decreases; if it is above 1, the
Table 3 shows the ﬁrst model estimated for female students
[Likelihood Ratio x2
(1,739) =17.09, p≤0.001, Pearson-Chi-
Square 60.95 (88, 739) =0.69]. The ﬁndings reveal that a strong
masculine image of math and science decreases the likelihood
of young women choosing a STEM study (Exp(β)=0.44; p≤
0.001). In other words, if young women do not perceive math and
science as predominantly masculine, they opt signiﬁcantly more
often for studying a STEM major.
The second model was estimated for male students
[Likelihood Ratio x2
(1,267) =9.22, p≤0.01, Pearson-Chi-
Square 73.90 (66, 267) =1.12]. The results show that the
masculinity of math is also a predictor of young men’s career
aspirations. The higher the masculinity image, the lower the
likelihood of a STEM study choice (Exp(β)=0.48; p≤0.01).
To conclude, both models show that the image of chemistry,
math and physics has an impact on students’ career intentions.
If the image of the three subjects has strong masculine
connotations, career choice is unlikely to be within the
This study contributes to the line of research on the gender
stereotype of science by analyzing the gender-related image
of three school subjects. It provides, moreover, more reﬁned
knowledge on the impact of gender stereotypical perception of
TAB LE 3 | Impact of the masculine image of math and science on secondary
students’ career aspirations.
Parameter βSE Wald-Chi-
Math and science model for female students
(Intercept) −1.98*** 0.12 253.81 0.14
Masculinity of math and
−0.82*** 0.17 24.30 0.44
Math model for male students
(Intercept) −1.17*** 0.15 59.88 0.31
Masculinity of math −0.73** −0.23 9.91 0.48
Generalized Linear Model (binomial/logit). Dependent variable: STEM career (response) vs.
Non-STEM Career (reference); aFixed at the displayed value; β=regression coefﬁcient;
SE =standard error; ***p≤0.001, **p≤0.01.
math and science on female and male secondary school students’
choice to enroll in a STEM university degree program.
In line with the ﬁndings of a study by Weinreich-Haste
(1981), our results reveal that students not only perceive
chemistry, math and physics as masculine, but also that there
is a considerable diﬀerence in the strength of the association
of each subject with the male gender. According to our
ﬁndings, math is most strongly perceived as a masculine
subject among female and male secondary school students,
followed by physics and then chemistry, which has the weakest
masculine connotations. The weak masculine connotations of
chemistry have also been reported by other studies (Archer
and MacRae, 1991; Makarova and Herzog, 2015). Consequently,
we could conﬁrm the ﬁrst hypothesis stating that chemistry is
accorded the lowest degree of masculinity compared to math
With respect to diﬀerences between female and male students
in the gender-stereotypical connotations of science, our ﬁndings
illustrate that female secondary school students perceive all three
subjects considerably more strongly as a male domain than do
male students. These ﬁndings are consonant with ﬁndings of
previous studies on strong associations of math and physics
with the male gender among female adolescents (Nosek et al.,
2002; Kessels, 2005; Kessels et al., 2006; Steﬀens et al., 2010).
In addition, our results illustrate that male students regardonly
math as strongly masculine, whereas physics and chemistry have
a comparably low score on the masculinity index. Thus, our
ﬁndings conﬁrm our second hypothesis by showing that the
association of the three science subjects with masculine traits are
stronger among female students.
With regard to the impact of the masculinity image of
math and science on secondary students’ career aspirations,the
ﬁndings of our study show that young women who potentially
chose STEM as a ﬁeld of study at university perceived all
three school subjects—math, physics, and chemistry—as less
masculine than did those young women who chose other majors.
Moreover, our results suggest that among female students a
strong masculine image of math and science decreases the
likelihood of choosing a STEM major at university. These
Frontiers in Education | www.frontiersin.org 8July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
ﬁndings propose that masculine traits associated with science
subjects at school constitute a major obstacle, particularly
for young women’s self-identiﬁcation with science (Nosek
et al., 2002; Cundiﬀet al., 2013) and for their aspirations to
become researchers (Šorgo et al., 2018). Regarding the career
aspirations of young women, our study supports the notion
that stereotypical beliefs about math and science prevent young
women from entering a STEM career (Lane et al., 2012;
Finally, our results on the career aspirations of young men
in relation to the stereotypical gender connotations of school
subjects show that young men with non-STEM career aspirations
perceived only math but not science subjects as signiﬁcantly
more strongly masculine than did young men who chose
with masculine traits negatively aﬀected male students’ STEM
career aspirations. These ﬁndings suggest that young men
who opted for non-STEM majors do not ﬁt the masculinity
stereotype and therefore the strong masculine connotations
of math may have an inhibiting impact on their career
aspirations similar to that on the STEM career aspirations
of young women. A possible interpretation of these ﬁndings
is that, among young women as well as among young
men, the lack of similarity between their self-image and the
image of an academic subject not only aﬀects their choice
of specialization in secondary school (Kessels, 2005; Kessels
et al., 2006; Taconis and Kessels, 2009)butalsoleadstoa
lower probability of choosing those subjects in their further
Overall, the ﬁndings of our study conﬁrm our third hypothesis
by illustrating that the higher the extent of association of STEM-
school subjects with masculine traits, the lower is the likelihood
to enroll in a STEM major at university—both for female and
male students. However, our ﬁndings also suggest that gender-
science stereotypes have a stronger negative impact on the
STEM aspirations of female than male students because a strong
masculine image of math and science signiﬁcantly decrease the
likelihood of choosing a STEM major among female students,
whereas only a strong masculine image of math signiﬁcantly
decrease the likelihood of enrollment in a STEM major among
Our ﬁndings have some implications for overcoming the
gender disparities in STEM. As the gender-related image of an
academic discipline has a considerable eﬀect on young people’s
career aspirations, a critical evaluation of the school subjects’
image might be one way to break through the gender-image-
driven limitations of the career horizons of female and male
students. For example, a study in Computer Science has shown
that women’s interest in studying Computer Science can be
increased through a change of image of this academic discipline
(Cheryan et al., 2013). The image of a school subject can, for
example, be depicted in school textbooks. An empirical analysis
of science textbooks in secondary education not only illustrated
the overrepresentation of male protagonists but also revealed
stereotypical portrayals of science and scientists (Makarova
et al., 2016a). Since stereotypic representations in textbooks
have an eﬀect on male and female secondary school students’
understanding of and anxiety about science (Good et al., 2010),
an eﬀort needs to be made to overcome stereotypical gender
representations in textbooks at all educational levels. Especially
since decisions to enroll in a ﬁeld of study or choose a ﬁeld of
work in vocational education are made relatively late, and since
gender images of school subjects have most likely by then been
internalized and settled, reﬂections about gender stereotypical
images of math and science subjects should preferably be
encouraged in early childhood. For example, a study by Archer
et al. (2010) suggested that although young children do not
have profound knowledge about science subjects, they attribute
masculine traits to science at an early age. Moreover, gender
stereotypical beliefs should be also tackled among teachers and
other gatekeepers who are potentially involved in the development
of vocational interests among children and secondary students.
As the study of Thomas (2017) showed, a teacher’s implicit
science-is-male stereotype can contribute to gender diﬀerences
in female students’ motivational beliefs and probably also their
gendered educational choices. Finally, Else-Quest et al. (2010)
suggest that proximal factors such as quality of teaching mediate
the eﬀect of gender inequality on math achievement. Thus,
rise in gender equity in education can also promote boys’
Our study is subject to a few limitations.Firstly,ourstudyhas
and youth career aspirations. Secondly,ourstudyassessesthe
career aspirations of secondary school students and not their
actual enrollment in particular majors at the university. Although
this operationalization of career choice has been applied by
other studies (Nagy et al., 2006; Watt, 2006), it does not exclude
the possibility that the anticipated choice of a study major
does not necessarily lead to the actual choice of the same
major after enrollment at university. Thirdly,weshouldnote
that our study applies an explicit assessment of masculinity
connotations of school subjects by using a semantic diﬀerential
with 25 opposite semantic meanings. Thus, we cannot rule out
that an open-ended questionnaire on masculinity image would
yield diﬀerent results on the semantic connotations and the
strength of masculinity of the target school subjects. Moreover,
we calculated the masculinity index based on the similarity of
the semantic proﬁles of the term man and the corresponding
subject term. As the present study does not include measures
of the semantic ratings of the term woman we cannot compare
the attribution of the feminine traits to chemistry, math and
physics and its impact on the STEM study choice. Finally,the
gender-related image of school subjects and their implications
are one of several determinants that aﬀect the career aspirations
of male and female secondary school students. Since we did
not control for other potential determinants in the explanatory
models (e.g., self-image of students, their abilities, or interest
in science), our results are limited to the investigation of the
impact of gender-science stereotype on students’ aspirations.
It has been demonstrated that further school-related factors,
such as the instructional design of science classes (Aeschlimann
et al., 2016), teachers’ support and encouragement (Aeschlimann
et al., 2015) as well as family-related factors, and also peers
can considerably inﬂuence the career-choice decisions of young
people (Makarova et al., 2016b).
Frontiers in Education | www.frontiersin.org 9July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
All authors listed have made a substantial, direct and
intellectual contribution to the work, and approved it
The authors gratefully acknowledge the Swiss National Science
Foundation for ﬁnancial support of the study Gender atypical
careers of young women (Grant no. 4060-129279).
Aeschlimann, B., Herzog, W., and Makarova, E. (2015). Frauen in MINT-Berufen:
Retrospektive Wahrnehmung des mathematisch-naturwissenschaftlichen
Unterrichts auf der Sekundarstufe I [Women in STEM professions:
retrospective perception of mathematics and science in secondary school
education]. Zeitschr. Bildungsfor. 5, 37–49. doi: 10.1007/s35834-014-0111-y
Aeschlimann, B., Herzog, W., and Makarova, E. (2016). How to foster students’
motivation in mathematics and science classes and promote students’STEM
career choice. A study in Swiss high schools.Int.J.Educ.Res.79, 31–41.
Archer, J., and MacRae, M. (1991). Gender perceptions of school
subjects among 10–11-year-olds. Br. J. Educ. Psychol. 61, 99–103.
Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., and Wong, B.
(2010). “Doing” science versus “being” a scientist: examining 10/11-year-old
schoolchildren’s constructions of science through the lens of identity. Sci. Educ.
94, 617–639. doi: 10.1002/sce.20399
BlaŽev, M., Karabegovi´
c, M., Buruši´
c, J., and Selimbegovi´
c, L. (2017). Predicting
gender-STEM stereotyped beliefs among boys and girls from prior school
achievement and interest in STEM school subjects. Soc. Psychol. Educ. 20,
831–847. doi: 10.1007/s11218-017-9397-7
Bubany, S. T., and Hansen, J. I. C. (2011). Birth cohort change inthevocational
interests of female and male college students. J. Vocat. Behav. 78, 59–67.
Chambers, D. W. (1983). Stereotypic images of the scientist: the draw-a-scientist
test. Sci. Educ. 67, 255–265. doi: 10.1002/sce.3730670213
Charles, M., and Bradley, K. (2009). Indulging our gendered selves? Sex
segregation by ﬁeld of study in 44 countries. Am. J. Sociol. 114, 924–976.
Cheryan, S., Plaut, V. C., Handron, C., and Hudson, L. (2013). The stereotypical
computer scientist: gendered media representations as a barrier to inclusion
for women. Sex Roles 69, 58–71. doi: 10.1007/s11199-013-0296-x
Cundiﬀ, J. L., Vescio, T. K., Loken, E., and Lo, L. (2013). Do gender–
science stereotypes predict science identiﬁcation and science career aspirations
among undergraduate science majors? Soc. Psychol. Educ. 16, 541–554.
Cvencek, D., Meltzoﬀ, A. N., and Greenwald, A. G. (2011). Math–gender
stereotypes in elementary school children. Child Dev. 82, 766–779.
Deaux, K., and LaFrance, M. (1998). “Gender,” in The Handbook of Social
Psychology, eds D.T. Gilbert, S.T. Fiske, and G. Lindzey (New York, NY: Mc
Eagly, A. H., and Wood, W. (2012). “Social role theory,” in Handbook of Theories of
Social Psychology, eds P. van Lange, A. Kruglanski, and E. T. Higgins (Thousand
Oaks, CA: Sage), 458–476. doi: 10.4135/9781446249222.n49
Eccles, J. S. (1994). Understanding women’s educational and occupational choices.
Psychol. Women Q. 18, 585–609. doi: 10.1111/j.1471-6402.1994.tb01049.x
Eccles, J. S., and Wigﬁeld, A. (2002). Motivational beliefs, values, and goals. Annu.
Rev. Psychol. 53, 109–132. doi: 10.1146/annurev.psych.53.100901.135153
Else-Quest, N. M., Hyde, J. S., and Linn, M. C. (2010). Cross-national patterns of
gender diﬀerences in mathematics: a meta-analysis. Psychol. Bull. 136, 103–127.
Ertl, B., Luttenberger, S., and Paechter, M. (2017 ).The impact of gender stereotypes
on the self-concept of female students in stem subjects with an under-
representation of females. Front. Psychol. 8:703. doi: 10.3389/fpsyg.2017.00703
Finson, K. D. (2002). Drawing a scientist: what we do and do not
know after ﬁfty years of drawings. Sch. Sci. Math. 102, 335–345.
Fort, D. C., and Varney, H. L. (1989). How students see scientists: mostly male,
mostly white, and mostly benevolent. Sci. Child. 26, 8–13.
FSO (2012). Abschlüsse der universitären Hochschulen und Fachhochschulen:
Basistabellen [University Diploma and University of Applied sciences
Diploma: Tables]. Available online at: https://www.bfs.admin.ch/bfs/de/
hochschulen/universitaere.assetdetail.5626778.html (accessed February 14,
FSO (2013). On the Way to Gender Equality. Current Situation and Developments.
Neuchâtel: FSO. Available online at: https://www.bfs.admin.ch/bfs/de/home/
(accessed October 10, 2018).
FSO (2019a). Students of Applied Universities (Basis Table). Available online
assetdetail.4762125.html (accessed November 11, 2018).
FSO (2019b). High School Diploma s Accordin g to Main Subject, School
Canton, Canton of Residence and Gender (Interactive Tables). Available
online at: https://www.pxweb.bfs.admin.ch/pxweb/de/px-x-1503020200_102/
px-x- 1503020200_102/px-x- 1503020200_102.px (accessed December 1, 2018).
George, D., and Mallery, P. (2016). IBM SPSS Statistics 23 Step by Step: A
Simple Guide and Reference. New York, NY: Routledge. doi: 10.4324/97813155
Good, J. J., Woodzicka, J. A., and Wingﬁeld, L. C. (2010). The eﬀects of gender
stereotypic and counter-stereotypic textbook images on science performance.
J. Soc. Psychol. 150, 132–147. doi: 10.1080/00224540903366552
Gottfredson, L. S. (2002). Gottfredson’s theory of circumscription, compromise,
and self-creation. Career Choice Dev. 4, 85–148.
Gottfredson, L. S. (2005). “Applying Gottfredson’s theory of circumscription and
compromise in career guidance and counseling,” in Career Development and
Counselling: Putting Theory and Research to Work, eds S.D. Brown, and R.W.
Lent (Hoboken, NJ: John Wiley and Sons), 71–100.
Greenwald, A. G., McGhee, D. E., and Schwartz, J. L. (1998). Measuring individual
diﬀerences in implicit cognition: the implicit association test. J. Pers. Soc.
Psychol. 74, 1464–1480. doi: 10.1037/0022-3518.104.22.1684
Hand, S., Rice, L., and Greenlee, E. (2017). Exploring teachers’ and students’ gender
role bias and students’ conﬁdence in STEM ﬁelds. Soc. Soc. Psychol. Educ. 20,
929–945. doi: 10.1007/s11218-017-9408-8
Hannover, B., and Kessels, U. (2004). Self-to-prototype matching as a strategy
for making academic choices. Why high school students do not like
math and science. Learn. Instr. 14, 51–67. doi: 10.1016/j.learninstruc.2003.
Hartung, P. J., Porfeli, E. J., and Vondracek, F. W. (2005). Child vocational
development: a review and reconsideration. J. Vocat. Behav. 66, 385–419.
Heise, D. R. (1970). “The semantic diﬀerential and attitude research,” in Attit ude
Measurement, ed. G.F. Summers (Chicago: Rand McNally), 235–253.
Herzog, W., Labudde, P., Neuenschwander, M. P., Violi, E., and Gerber, C. (1998).
Koedukation im physikunterricht.Schlussbericht [Coeducation in Physics Class.
Final report]. Universität Bern: Abteilung für Pädagogik/Abteilung für das
Höhere Lehramt, Bern.
Hofstätter, P. R. (1973). Einführung in die Sozialpsychologie [An Introduction in
Social Psychology]. Stuttgart: Kröner.
Huber, R. A., and Burton, G. M. (1995). What do students think scientists
look like? Sch. Sci. Math. 95, 371–376. doi: 10.1111/j.1949-8594.1995.tb1
Jones, B., Ruﬀ, C., and Paretti, M. (2013). The impact of engineering
identiﬁcation and stereotypes on undergraduate women’s achievement
and persistence in engineering. Soc. Soc. Psychol. Educ. 16, 471–493.
Frontiers in Education | www.frontiersin.org 10 July 2019 | Volume 4 | Article 60
Makarova et al. The Gender Gap in STEM Fields
Kessels, U. (2005). Fitting into the stereotype: how gender-stereotyped perceptions
of prototypic peers relate to liking for school subjects. Eur. J. Psychol. Educ. 20,
309–323. doi: 10.1007/BF03173559
Kessels, U., Rau, M., and Hannover, B. (2006). What goes well with physics?
Measuring and altering the image of science. Br. J. Educ. Psychol. 76, 761–780.
Kessels, U., and Taconis, R. (2012). Alien or alike? How the perceived
similarity between the typical science teacher and a student’s self-image
correlates with choosing science at school. Res. Sci. Educ. 42, 1049–1071.
Koenig, A. M., and Eagly, A. H. (2014). Evidence for the social role theory of
stereotype content: observations of groups’ roles shape stereotypes. J. Personal.
Soc. Psychol. 107:371. doi: 10.1037/a0037215
Lane, K. A., Goh, J. X., and Driver-Linn, E. (2012). Implicit science stereotypes
mediate the relationship between gender and academic participation. Sex Roles
66, 220–234. doi: 10.1007/s11199-011-0036-z
Makarova, E., Aeschlimann, B., and Herzog, W. (2016a). “Wenn FraueninMINT-
Studiengängen fehlen: mathematisch-naturwissenschaftlicher Unterricht und
die Studienwahl junger Frauen [When women lack from STEM courses:
teaching mathematics and Natural sciences and Young Women’s Study
Choices],” in Berufsorientierung und Geschlecht [Vocational orientation and
gender], ed. H. Faulstich-Wieland (Weinheim: Juventa-Verlag), 39–57.
Makarova, E., Aeschlimann, B., and Herzog, W. (2016b). Ich tat es ihm gleich
– Vorbilder junger Frauen mit naturwissenschaftlich-technischer Berufswahl
[“I did it like he did” – role models of young women with science and
technical vocational choices]. Berufs- und Wirtschaftspädagogik online. Spezial
12, Berufsorientierung im Lebenslauf – theoretische Standortbestimmungen
und empirische Analysen [Career orientation in the life course - theoretical
approaches and empirical analyses], 1–19.
Makarova, E., and Herzog, W. (2015). Trapped in the gender stereotype?The
image of science among secondary school students and teachers. Equal. Diver.
Inclu. Int. J. 34, 106–123. doi: 10.1108/EDI-11-2013-0097
McCullagh, P., and Nelder, J. (1989). Generalized Linear Models, 2nd Edn. Boca
Ration, FL: CRC Press. doi: 10.1007/978-1-4899-3242-6
Mead, M., and Metraux, R. (1957). Image of the scientist among high-school
students. Science 126, 384–390. doi: 10.1126/science.126.3270.384
Miller, D. I., Eagly, A. H., and Linn, M. C. (2015). Women’s representation in
science predicts national gender-science stereotypes: evidence from 66 nations.
J. Educ. Psychol. 107, 631–644. doi: 10.1037/edu0000005
Miller, D. I., Nolla, K. M., Eagly, A. H., and Uttal, D. H. (2018). The development
of children’s gender-science stereotypes: a meta-analysis of 5 decades of
US draw-a-scientist studies. Child Dev. 89, 1943–1955. doi: 10.1111/cdev.
Millon, T., Lerner, M. J., and Weiner, I. B. (2003). Handbook of Psychology:
Personality and Social Psychology, Vol. 5. Mishawaka: Wiley and Sons.
Nagy, G., Garrett, J., Trautwein, U., Cortina, K. S., Baumert, J., and Eccles, J. S.
(2008). “Gendered high school course selection as a precursor of gendered
careers: the mediating role of self-concept and intrinsic value,” in Gender and
Occupational Outcomes, eds H. M. G. Watt and J. S. Eccles (Washington, DC:
American Psychological Association), 115–143. doi: 10.1037/11706-004
Nagy, G., Trautwein, U., Baumert, J., Köller, O., and Garrett, J. (2006).
Gender and course selection in upper secondary education: eﬀectsof
academic self-concept and intrinsic value. Educ. Res. Eval. 12, 323–345.
Neuhaus, J., and Borowski, A. (2018). Self-to-prototype similarity as a mediator
between gender and students’ interest in learning to code. Int. J. Gen. Sci.
Technol. 10, 233–252.
Nosek, B. A., Banaji, M. R., and Greenwald, A. G. (2002). Math=male,
me=female, therefore math̸=me. J. Pers. Soc. Psychol. 83:44.
Nosek, B. A., Smyth, F. L., Sriram, N., Lindner, N. M., Devos, T., Ayala, A., et al.
(2009). National diﬀerences in gender-science stereotypes predict national sex
diﬀerences in science and math achievement. Proc. Natl. Acad. Sci. U. S. A.106,
10593–10597. doi: 10.1073/pnas.0809921106
OECD (2006). Evolution of Student Interest in science and Technology Studies.
Policy Report. Available online at: www.oecd.org/dataoecd/16/30/36645825.pdf
(accessed October 10, 2018).
OECD (2012). Closing the Gap. Act Now. Paris: OECD Publishing.
OECD (2017). The Pursuit of Gender Equality: An Uphill Battle. Paris: OECD
Publishing. doi: 10.1787/9789264281318-en
Osgood, C. E., Suci, G. J., and Tannenbaum, P. H. (1957). The Measurement of
Meaning. Urbana: University of Illinois Press.
Ramsey, L. R. (2017). Agentic traits are associated with successin
science more than communal traits. Pers. Individ. Dif. 106, 6–9.
Ratschinski, G. (2009). Selbstkonzept und Berufswahl. Eine Überprüfung der
Berufswahltheorie von Gottfredson an Sekundarschülern [Self-concept and career
choice. A review of Gottfredson’s career choice theory among secondary school
students]. Münster: Waxmann.
Renfrow, D. G., and Howard, J. A. (2013). “Social psychology of gender and race,”
in Handbook of Social Psychology, eds. J. DeLamater, and A. Ward (Dordrecht:
Springer), 491–531. doi: 10.1007/978-94-007-6772-0_17
Rosser, S. V. (2012). Breaking Into the Lab: Engineering
Progress for Women in Science. New York, NY: NYU Press.
Scherz, Z., and Oren, M. (2006). How to change students’ images of
science and technology. Sci. Educ. 90, 965–985. doi: 10.1002/sce.
Šorgo, A., Dojer, B., Golob, N., Repnik, R., Repolusk, S., Pesek, I., et al. (2018).
Opinions about STEM content and classroom experiences as predictorsof
upper secondary school students’ career aspirations to become researcher or
teachers. J. Res. Sci. Teach. 55, 1–21. doi: 10.1002/tea.21462
Steﬀens, M. C., Jelenec, P., and Noack, P. (2010). On the leaky math
pipeline: comparing implicit math-gender stereotypes and math withdrawal
in female and male children and adolescents. J. Educ. Psychol. 102:947.
Taconis, R., and Kessels, U. (2009). How choosing science dependsonstudents’
individual ﬁt to the “science culture.” Int. J. Sci. Educ. 31, 1115–1132.
Thomas, A. E. (2017). Gender diﬀerences in students’ physical science
motivation: are teachers’ implicit cognitions another piece of the
puzzle? Am. Educ. Res. J. 54, 35–58. doi: 10.3102/0002831216
Watt, H. M. G. (2006). The role of motivation in gendered educational and
occupational trajectories related to maths. Educ. Res. Eval. 12, 305–322.
WEF (2017). The Global Gender Gap Report. WEF. Available online at:
https:www3.weforum.org/docs/WEF_GGGR_2017.pdf (accessed November
Weinreich-Haste, H. (1981). “The image of science,” in The Missing Half: Girls and
Science Education, ed A. Kelly (Manchester, UK: Manchester University Press),
Worell, J. (2001). Encyclopedia of Women and Gender: Sex Similarities
and Diﬀerences and the Impact of Society on Gender.SanDiego,CA:
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.
Copyright © 2019 Makarova, Aeschlimann and Herzog. Thisis an open-access article
distributed under the terms of the Creative Commons Attribution License (CC BY).
The use, distribution or reproduction in other forums is permitted, provided the
original author(s) and the copyright owner(s) are credited and that the original
publication in this journal is cited, in accordance with accepted academic practice.
No use, distribution or reproduction is permitted which doesnotcomplywiththese
Frontiers in Education | www.frontiersin.org 11 July 2019 | Volume 4 | Article 60