FACTORS INHIBITING GIRLS FROM COMPUTER SCIENCE CAREER

Factors Inhibiting Girls From Choosing Computer Science as a Career

Kathleen Fisher

California State University, Fullerton

Abstract

The scarcity of women in computing science careers and girls choosing to study for computing careers is

a problem around the world. Research has been studying this problem for the last 30 years, yet the

numbers have continued to decline since the 1980s. This review has three areas of focus: stereotyping,

self-efficacy of girls, and gaming as an instructive tool to teach computing concepts. Thousands of

students have been studied across the world. The most significant finding in the research is that by using

gaming to teach computing concepts at an early age may be the best way to introduce girls to computer

science. Matching girls with mentors who have engineering and computer science careers can also help

girls understand the options they have within these careers. Many of the studies have not had the ability to

test for long-term results. Implications of this review can help with the design of gender equitable

curriculum and opportunities built in to the elementary and middle school years to learn computing

concepts.

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This review of literature focuses on the importance of building a strong collaboration between science and

education to overcome the underrepresentation of females in computer science. Vekiri (2013) states that,

women’s under-representation in computing perpetuates economic inequalities.[TG1]. It also deprives

technological fields from the breadth of perspectives that support scientific developments that lead

innovations that take into account social diversity (p.104). Plant, Baylor, Doerr, and Rosenberg-Kima

(2008) wrote that, girls [TG2] outscore boys in math and science at the high school level, yet the data on

females in careers and courses in computer science is at best unchanging and in some cases getting

worse[TG3] (p.209). According to Sainz (2010), women working in IT fell from 24% to 19% between

2001 and 2006.The jobs that these women hold in IT tend to be low in status, pay, and skill level. Only

14% hold positions of IT strategy and planning professionals (p.578). I will be addressing three themes

that are keeping females from pursuing computer science career paths. First, stereotyping in schools, the

workplace and pedagogy. Second, raising the self-efficacy and motivation of girl’s skills by introducing

career possibilities in computer science. Third, using gaming as a way to engage girl’s skills in computer

science.

I conducted a comprehensive review of the literature on gender issues, students’ attitudes, and gaming

programs. The purpose of this literature review was to collect reliable information on factors that are

keeping girls from pursuing computing careers and solutions to help change the downward trend of

women entering these fields. [TG4]

The literature review is organized into three themes. The first section will deal with stereotypes in general

that are affecting girl’s self-efficacy and motivation to take classes in high school that could lead them

into computer science careers. The second section is programs that have worked to raise self-efficacy and

interest. Lastly, raising the knowledge of students about actual jobs in the computing field. This review

will conclude with a summary and concluding discussion of the themes and gaps that emerged from this

review.

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Literature Search Strategy

For this review, I searched using ERIC, EBSCO, and Google Scholar. I also looked for references listed

in other research I was able to obtain on my topic. Keywords used in my searches: elementary education,

gender stereotypes, STEM, gender differences, attitudes toward computing, girl’s coding, and self-

efficacy. I limited the searches to full text, peer-reviewed journals and online articles. In my first round of

searches I looked at research from 2010-2016. My second round of searches was based on references

listed in articles I had found to be useful for my topic.

Stereotyping

The research I read found worldwide gaps between men and women about computer science careers.

According to Fleischmann, Sieverding, Hespenheide, Weir, & Koch (2015), in Germany in 2014, only

18% of university students in computer science, computing engineering and IT were women. In the

United States the findings are even lower. Only 13% of computing students in 2010 were women. (p.63).

The reason that stereotypes have been studied extensively is that stereotyping is a theory that can help

explain the fact that women are not choosing careers in computer-related fields. Computers and

technology seem to be perceived as incompatible with social skills, which are supposed to be important

requirements for woman to achieve professional and personal development, and intervention programs

with parents, teachers, and other influential individuals are necessary to promote girls’ attraction to

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computers and technologies and change the perception of computers as a male-dominated area. There is

still a strong correlation between girls and the parental and peer support they perceive, and their computer

self-efficacy and value beliefs. Boys reported more parental support from their parents and peers to use

computers and more positive self-efficacy and value beliefs than girls. The findings in Vekiri’s (2008)

research highlights the role of socialization in the gender gap in computing; focus needs to be on the

social practices that communicate gendered expectations to young boys and girls (pg.1392). The social

image of computer scientists as “geeks”, socially isolated people and computer science as a male-

dominated field seem to be a big factor in turning girls away from computing.  Bandura, (1997); Eccles,

Barber, & Jozefowicz, (1999) have reached the conclusion that early adolescence is a critical time with

respect to how the adolescent perceives other people’s view of them, which influences choices they will

make concerning career plans and academic decisions. Cooper (2006) studied the area of achievement

motivation leading to the feeling of success in one’s skills. This is influenced by the stereotype that girls

and women are less interested in and skilled with computers which leads to lower self-efficacy, less

computer use, and lower participation in computer courses in school (pgs.121-124 ) According to Vekiri

(2013) in a study where males and females were in classes that taught computer science tasks that were

meaningful and personally relevant, both boys and girls expressed positive views about their computing

skills and the importance of information science (pgs. 16 & 17) . While boys expressed higher levels of

enjoyment at both reporting periods, it was also reported that the boys preferred to collaborate and

interact with others. These findings also show hope for breaking down the stereotype that males enjoy

working alone on computing projects. Both males and females positively reported that teachers are able to

inspire an interest in computing when they use tasks and pedagogical techniques that make academic

content more relevant. Najafi (2012) reports that, “ The learner is one of the elements that it believes have

the most important position in structure of curriculum (pg. 1). It should be advocated that all curriculum

emphasize the relevance of computing to people and the world. This may help educators create

curriculum for science and computer science that promotes pedagogical practices that are gender-

equitable.

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Mentoring.

Positive female role models in technical and scientific careers may help change society’s and girls’ idea

that this is a male dominated area. Najafi, Ebrahimitabass, Dehghani and Rezaei (2012) state that the lack

of women in technology can be seen as a public policy problem and it perpetuates gender inequities.

Stoeger, Duan,Schirner, Greindl, and Ziegler (2013)  wanting to change the lack of girls entering into

STEM careers researched the effects of using online mentoring for 11 to 18 year old female college-

preparatory students (pg. 208-210)[TG7].  Bloom in 1984 reported that, “Mentoring is potentially one of

the most effective promotional measures in pedagogy (pgs. 4-16).” The data collected from Stoeger’s

(2013) research, found when using a treatment group who had STEM mentors compared to students on

the waiting list, the treatment group showed greater levels of short-term and long-term developments

(pgs. 413-415). The use of online mentors helped to address the problem of finding mentors within a

highly specialized domain. Research attests to the importance of female role models in these fields, yet

there are a lack of women in most geographical areas to support the need. Current research has examined

environmental influences and the prevailing stereotype of men being better in STEM fields, which adds to

the problem of stereotype threat. Stout, Dasgupta, Hunsinger, and McManus (2011) study has shown that

female role models who are in STEM fields can promote change in: goal setting, success beliefs, self-

concepts, attitudes, and stereotypes Mentoring results positively correlated with six of the seven variables

considered (pgs. 255-260). According to Stoeger (2013) the results showed increases in the treatment

group compared to the control group in the areas of: STEM activities, knowledge about university studies

and jobs in STEM, and academic elective intentions. Effects were positive for prevention effects for

confidence in one’s own STEM competencies and self-assessment of one’s own STEM competencies.

Short-term and long-term effects were noted in STEM activities and awareness of university studies and

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jobs. This study’s results show that mentoring can lead to benefits in gender stereotypes and the impact

on personnel decisions.

Using interface agents.

There have been several studies using female interface agents to test for gender bias and attitudes. The

findings do agree that female agents can raise young women’s interest, but can it improve their

performance in engineering-related fields, especially mathematics through social modeling? Engineering

and mathematics are generally stereotyped as unfeminine, aggressive, and object–oriented rather than

people oriented. Combine these two problems and it can be inhibiting females from pursuing science and

technology careers. Trying to change these ideas at an early age is the idea under study. The findings of

Plant, Baylor, Doerr, and Rosenberg-Kima (2009) and Fleischmann, Sieverding, Hespenjeide, Weil, and

Koch (2016) found that using a female anthromorphic agent; in the short term effectively raised the

attitudes and beliefs about mathematics and hard sciences, as well as their actual mathematical

performances. Fleischmann (2016) claims the female agent was the most effective at raising the attitudes

with both male and females (pg.65). The reasoning for the increase in performance in attitude and

mathematics was due to influence on their self-efficacy. The boys’ beliefs about whether engineering

related fields were better suited for men than for woman were effected positively. While the agents were

not effective in changing the girls’ gender related perception of engineering-related fields.   Baylor and

Plant (2005) reported that the pervading messages that girls get over their childhood, indicates a lower

expectation held for them as to their abilities towards sciences and math. Both Plant and Fleischmann

reported that the computer-based anthromorphic interface can serve as an effective tool to build self-

efficacy and skill. This is a uniquely flexible device for helping students’ success and inclusiveness of

traditionally unfeminine fields.  The research of Fleischmann et al (2015) and Plant, Baylor, Doerr, and

Rosenberg-Kima (2009) both held the belief that the activation of gender stereotypes may lead to a

negative attribution pattern for women’s success or failure on computer tasks. These studies wanted to

research how this activation of gender affected both males’ and females’ attitudes.  It was found that the

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outfit of the evaluated women played an important role in the judgement of both the male and females

computer skills, and the success or failure of completing a computer task.  Fleishmann and Plant both

reported  that males participants expected to be much more successful with computers than female

participants. These findings supported existing evidence on gender differences. Plant (2009) found that

using an animated female interface agent raised women’s interest, self-efficacy, and math performance

compared to the control group. The males in the study using a female agent actually led to a decrease in

stereotyping (pg. 209). When participants in a study conducted by Sieverding and Koch (2009) were

asked to observe a target person on a video, results showed that no gender-based judgment was made of

the success of the target in the video performing a computer task. Though, when participants were asked

to self-report their own competencies, women self-evaluated their own skills lower than males, and when

males judged themselves compared to women they related their competence to be higher than females

(pg. 269-271). This speaks to the fact that systemic double standards are still persisting in society.

The findings in Sainz and Eccles (2012) research verified other studies’ results that girls have lower

positive computer attitudes than their male counter parts(p.486). Future research can build on the fact that

even though girls have lower attitudes towards computing, it cannot be concluded that they have negative

attitudes. Both Fuller, Turbin, and Johnston (2013) and Vekiri  (2013) advocated for gender homogenous

trainings as an effective practice so that girls and women don’t suffer from negative comparisons and

stereotype threats of males. According to Vekiri (2013), “Gender segregated instruction still shows girls

work better with girls” (pp. 16-23[TG6] ). Fuller’s (2013) research results supported a single sex approach

to encouraging girls in computers. In the surveys that were filled out by the members of a girl-only

computing club 85% of the girls reported that it was a very important factor for them staying in the club.

The reasons given for this was, “boys mess around”, and it was a calmer and more sociable environment

(pg. 504-506).

GamingMuch of the research focuses on psychological and educational factors hindering females in choosing

computer science academics and careers. This section of the findings looks at using programming

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constructs in students prior to graduating from high school. This could answer the question of how we

develop innovative curriculum models that promote female participation in computer sciences. According

to Carbonaro, Szafron, Cutumisa, and Schaeffer (2010) even though boys spend more time playing

computer games, girls are equally as skilled at creating complex computer games (pg.1110).  Carbonaro

(2010) found that the affinity for liking to play computer games doesn’t correlate to competence in

building computer programs (pg. 1098). Girls were found to be as good or better than boys in building

games. This finding contradicts what most people think, since boys play computer games at a much

higher rate than girls, they must be better at creating computer games. Carbonaro’s (2010) observation is

profound because the research found that game constructing, not playing, led to higher-order thinking

skills that are essential for science (pg. 1109). This was important because females exercised higher-order

thinking skills at a significantly higher level than boys.  Both Carbonaro (2010) and Denner’s (2012)

findings found that gender-neutral attractors may get girls into computer science. Papastergiou (2009)

reported that in teaching computer science through gaming was not only an effective way to learn

computing concepts, but very motivating. Denner, Werner, and Ortiz (2010) had similar findings, that

their research showed high levels of enjoyment and motivation among their participants (pg. 248).

According to Denner (2010), Carbonaro (2010) and Denner (2012) by creating a shareable project, girls

reported high levels of enjoyment in the process. Carbonaro (2010) reported another major finding that

they found it enjoyable in a setting where both boys and girls were having fun collaborating together

(pgs.1106-1109). This is a positive indication that given the right tools and instruction, inter-active

gaming would be a well-received pedagogical intervention in schools that would support the learning of

computer science.

Building on the idea that gaming is motivating, Denner (2012) wanted to study the actual skills involved

in programming and if it actually supported computer science skills (pg. 240). This research held the

constructionist theory that people learn by making a meaningful product. Denner’s (2012)  study followed

the games made by 59 low-income, Latina girls with no prior computing experience.  It was reported that

they were able to create games with moderate levels of usability and low levels of code organization and

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documentation (pg. 248). This supported Denner’s (2012) hypothesis that gaming can be used to teach

computer science concepts.

Self-efficacySelf-efficacy is a person’s belief in his/her ability to succeed in a particular situation. If you don’t have a

strong belief in your skills you are most likely not going to choose to pursue a career in that area of study.

Not feeling good about your skills also effects your motivation to take more classes in that area.  All of

the research that I studied which dated from 2008 to 2016, showed that common gender stereotypes still

persist that women assume to have lower computer skills than men. Consistently, women self-rate their

computing skills lower than males. Though in a study by Aesaert and van Braak (2015) they found that

girls when tested were found to have better technical skills and higher-order ICT competencies than boys

(pg.23-25).  Bandura (1982) reported that efficacy beliefs are not static; they change depending on prior

experiences and environmental experiences (pg. 122). Bandura states,” There are four self-efficacy

beliefs; mastery experiences, vicarious experiences, encouragement, and stress related to the experience.

The most powerful of these four is mastery experience, this relates to prior successes or failures

(pg.122).” It has been reported that the ages between twelve and thirteen can be one of the most

influential times in self-perception of one’s skills. Many of the studies target students at this age frame,

hoping to change their beliefs to not exclude their competency at computing. Technology fields are held

with prestige because of the work opportunities, and high intellectual capacities, and while girls have

good academic performance they are not pursuing these challenging and highly prestigious studies. Sainz

(2012) reported that when 12 & 13 year old boys and girls were in a 2 year study analyzing gender

differences in self-concept related to math and computer science skills, boys self-reported higher in both

math and computing at both year 1 and year 2 reporting periods. Girls not only reported lower self-

efficacy in both areas, their scores were lower after 2 years than after the first year of study(pgs. 496-

497). This was surprising since girls had scored higher than boys in math after the first year. Sainz in both

(2010 and 2012) had findings that females had a negative and significant correlation between their self-

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efficacy of computer skills and strong math skills. For girls, the higher the math skills, the lower the

computing self-efficacy.  Unfortunately, Sainz’(2010) also found that having strong math performances

did not predict pursuing future computing careers. One problem with this study is that self-reporting one’s

math performance is not the same as actual math performance. According to a study done by Huffman,

Whetten, and Huffman (2013), when university students were asked to complete a survey dealing with

gender roles and technology self-efficacy; gender roles, specifically masculinity,was the source of

difference. Previous research has studied gender differences not gender roles. Huffman (2013) supported

the findings that masculinity predicted self-efficacy more than any other factor reported. This finding

supports gender role theory and provides the link between gender role theory and technology self-

efficacy. Steele, and Aaronson’s (1997) research had previously  pointed to possible explanations given

by stereotype threat theory and emotion theory regarding how genders react to technology (pg. 1780).

Stereotyping: Summary

    

It is proposed that a gender gap in computer use still exists across all age groups and cultures. By

encouraging girls to have contact with computers from an early age could reduce gender differences in

computer attitudes. Intervention programs with parents, educators and other influential individuals is

necessary to promote girls’ attraction toward computers and to change the image as a male-dominated

field. Girls’ confidence in computing was enhanced when the computing task allowed them to use their

academic strengths in other curriculum areas. Yet, girls and women continue to self-rate their skills lower

than men even though studies have shown them to have higher computing skills when tested. Society

needs to de-bunk the stereotypes surrounding scientists as geeks and socially isolated individuals. An

important finding that was also reported is gender homogenous trainings so that girls and women can

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have the opportunity to build higher self-efficacy of computer use and not suffer from comparisons and

stereotype threats.

Teachers’ pedagogical practices had effects on all students’ motivation. All students benefited from the

social interaction and applications of computing. Both boys and girls expressed very positive views when

taught in a gender-equitable way that brought relevance to their learning. When teachers use activities

that highlight the benefits of technology and relevance to real-life, and assignments that were perceived to

create connections between computing and other subjects, the level of girls’ motivation and value beliefs

increased. Girls’ confidence in computing was enhanced when the computing task allowed them to

exploit their academic strengths in other curriculum areas. Teachers must address content in ways that

make it personally relevant and meaningful to the students.

Using gaming to teach computing concepts emphasizes the importance of making a product for and with

others. This can be extremely useful for engaging students in targeted computing concepts. Incorporating

female agents to teach computing concepts highlights the importance of self-efficacy on motivation and

performance and that these interventions can aid in targeting self-efficacy. If girls are introduced to

gaming before high school they have a much higher chance of pursuing a computer science course of

study in both high school and college.

Finally, the fact that younger women do not have positive role models in computer science is a problem.

Online mentoring is an appropriate measure for promoting girls’ development in academic STEM choices

and participation in these careers.

A brief summary of the research literature establishes the relevance of the problem. This is a problem that

has been researched throughout the world and yet very few gains have been found in changing the

problem. There are some conflicting findings, but the pervasive problem is how to raise girls’ motivation

and self-efficacy towards their own computer science skills. Putting the research together that pertains to

stereotyping, gaming, and self-efficacy can help guide future research and pedagogical practices in

schools. [TG1]

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