While Europe is facing an ever widening gap between e-skills and IT-related employment opportunities, girls are still largely under-represented in computer science studies. Why? Which are the barriers that withhold girls from studying a career in technology?
This article is written to support the proceedings of the UniteIT Gender Equality workgroup and uses a scientific approach  to explain how a number of mechanisms are working together in preventing girls from pursuing a career in technology.
Societal belief about computing as masculine
Any assumption about women being inherently less adept in science, engineering & technology has been repeatedly dismissed by research. Cognitive or biological differences are not at work in preventing girls from participating in IT . Numerous studies indicate that when gender discrimination is low, girls have the same performance in mathematics as boys .
However, many teachers , parents and other adults hold the societal belief about computing as masculine and reinforce stereotyped views that the sector is better suited to men. Girls are often actively discouraged by families, teachers and career advisors from pursuing further studies or careers in the field .
Stereotypes are a type of brain-enforced categorical thinking that describe the characteristics of a group and lead us to think all members of a group are similar to each other. They can be both positive (e.g. German are serious) and negative (e.g. French are chauvinists) and next to describing are often prescribing.
Especially gender stereotypes are extremely prescribing: men are (and should be) ‘adventurous’, ‘sure of themselves’, ‘independent’, ‘brave’ and are (and should be) good mechanics; while women are (and should be) ‘sensitive’, ‘sweet’, ‘emotional’, ‘social’ and are (and should be) good nurses.
Historically, the computer evolved around engineering and mathematics, two disciplines that are viewed as cold, rational and logical - characteristics that gender stereotypes attribute to a masculine role. Moreover, the person involved with informatics is viewed as antisocial and sloppy, the opposite of what gender stereotypes describe a woman should be and look like.
And thus: a girl interested in informatics “transgresses” her gender and receives disapproval, not only from society, but also from herself, as it moves her away from her own femininity .
Stereotyped media representations
The way in which computing and technology are portrayed in magazines, the internet, television and movies impacts our ideas of whom we see as qualified for computing work when we see certain kinds of people doing certain kinds of jobs .
In the late 1990s, Sanders (1998) analyzed computer magazines for educators and found that approximately 75% of people portrayed or mentioned were men. Similarly, Knupfer & Nelson (1998) found rampant gender stereotypes about people in technical roles.
More recent research finds that women are still represented stereotypically in popular culture, such as holding little power or understanding of technology, occupying marginal roles in organizations, and being passive individuals .
Additionally, media images often still present the stereotype of computer professionals as geeks without social skills doing boring and solitary jobs .
Good progress has been made in media portrayals of other previously male-dominated areas such as medicine, law and forensic science, where women are now portrayed in powerful positions .
Research found that among girls aged 14-18, forensic scientist (popularized in recent crime dramas such as CSI) was girls’ 6th most popular job choice, while computer engineer and software engineer were girls’ 15th and 18th choice, respectively .
This hints at the power of popular culture to raise awareness and influence youth perceptions about occupations. Still, few movies or prime time television shows take place in a technology setting  and even fewer have a powerful female lead character .
Absence of female role models
At a very early age in life children understand their gender belonging and start the process of gender-differentiated modeling by observing and adopting the behaviors, tastes and attitudes of persons of their gender. In this way, female role models generally exert strong influence on girls making decisions about further studies or careers .
But where can a girl find such tech-savvy female role models? At home, fathers are more likely to be seen as computer experts than mothers .
What about school? A Greek study showed that female teachers have more negative attitudes towards computers and greater anxiety about them, thus affecting a girl’s perspective of women and informatics .
On the workfloor? Neither. The absence of female role models working in IT has been identified as an important deterrent for women considering a role in sectors like technology, not traditionally viewed as ‘female friendly’ .
Lack of early experiences and gendered gaming
Studies have found that early usage of computers improves success in future computing classes . Indeed: significantly more males report early exposure to computers at home: 63% male versus 37% female . And when it comes to creating with technology rather than just use, studies showed that boys had more early experience with programming than girls .
Many see gaming as a particularly promising way of fostering interest in computing at very early ages . While in the past boys spent more time gaming, recent findings suggest that this divide is narrowing .
As girls have begun to start gaming in equal number to boys, evidence does suggest that gaming can be an engaging way to introduce computing for girls .
Irrelevant curriculum of computer courses
Sound learning theories have long emphasized the importance of connecting instruction to students’ interest and prior knowledge, and of using active and collaborative learning pedagogies . This approach is important not only for improving learning for girls and other underrepresented students, but for all students.
Recent research found how curriculum and teaching in science-related fields do not employ these pedagogies . Specifically computer science courses still routinely fail to make computing curriculum relevant for students .
Focus group interviews with girls indeed revealed that they perceive IT as boring due to their experiences in earlier secondary school IT courses, often being taught by teachers with limited preparation and consisting of “mundane, repetitive tasks” .
Computing is also taught in the abstract, preventing students from recognizing how technology can help address relevant societal problems. This kind of ‘abstract’ curriculum reinforces a view of computing as a lonely, isolated, machine-focused set of tasks .
The lack of relevance of computing curriculum is troubling because making relevant connections is particularly important for increasing girls’ interest in computing courses and careers, as they enable girls to correct their misperceptions and change their attitude about computing careers.
Stereotype threat is the fear or anxiety that our actions will confirm negative stereotypes about our group or about ourselves as members of a group. A wealth of research has illustrated that these fears and anxieties drastically reduce feelings of competence and trust, and can negatively affect performance, confidence, and risk-taking behavior .
This can be the case if girls often find themselves in all or mostly-male environments as this can increase discomfort and activate stereotype threat. In interviews, girls indicated that their interest in computing classes was influenced by social factors like experiencing the computer lab as an unwelcoming environment, dominated by boys and where they would feel uncomfortable being the only girl .
One of the most consistent findings in the relationship between gender, confidence and computing is that girls express less confidence and rate their ability lower than boys, even when actual achievement levels are similar . These findings suggest that it is very important to limit the “posturing” of male students in classrooms, as this can be particularly damaging to the confidence levels of female students, especially those with less prior experience .
Recognizing stereotype threat is important; otherwise educators, peers, parents and others might incorrectly assume that lack of confidence or reduced performance are the result of personal characteristics of the girls themselves.
Not recognizing stereotype threat would leave the conditions that create it unaddressed, ensuring girls are not able to live up to their full potential and most likely will leave or never choose to pursue computing.
Lack of understanding of what ICT jobs entail
Girls (and often boys) still have limited knowledge or inaccurate perceptions about what computing careers involve. Generally, girls perceive IT careers as having little or no interaction with others and that IT workers are obsessed with computers .
Also teachers and parents are poorly educated about what ICT really entails. Neither girls nor role models see ICT roles offering them chances to travel, to help others or to work independently . Another study of 320 junior girls in top-level math classes found that a lack of knowledge about computer science and computing careers were top reasons for not choosing a career in Computer Science .
The above paragraphs identify the key societal and structural factors that influence girls' participation in computing, often deterring them from choosing future education or careers in technology.
It is though important to remember that girls do not develop their perceptions, interests, confidence and career decisions in a vacuum, but are shaped by the larger society and local environments in which they learn about computers and technology.
Due to the multiple contexts in which the barriers occur, it is clear that there is no single, easy answer to increasing girls' participation in computing. Reform requires multiple kinds of change agents and a multi-faceted approach. In a follow-up article, we will give an overview of how change can be implemented.
 This was also the approach of Girls in IT: The Facts, published by the National Center for Women & Information Technology (NCWIT) on which most of this article is based (Ashcraft et al., 2012)
 Hyde & Linn, 2006
 Guiso et al., 2008
 Teachers often have biases in terms of who they believe has “innate” talent or a “flair” for computing (AAUW, 2000; Margolis, et al., 2008; Voyles et al., 2007).
 OECD, 2006.
 Seron, 2005
 Wolkowitz, 2006; Jenson & Brushwood Rose, 2003; Sanders, 2006
 Cozza, 2011; Jepson & Perl, 2002
 Klawe, 2002
 Jepson & Perl, 2002
 Boys’ top 3 choices were webmaster, computer engineer, software engineer. Miller & Hayward, 2006
 In 2001, British Emeritus Professor of Software Quality Margaret Ross won a national award for a TV soap idea that if televised could raise the profile of engineering and attract youngsters to computing and technology http://www.solent.ac.uk/faculties/martec/staff-profiles/ross-margaret.aspx
 Clayton et al. (2009) do highlight one recent positive example of a female in a computing role, Penelope Garcia, from the crime drama Criminal Minds. However, while her character is positively portrayed in many ways, her carácter also tends to reinforce many stereotypes as she is portrayed to be a somewhat “quirky” person, is obsessed with online gaming, wears glasses, dresses in what might be considered somewhat funky or “geeky” attire, and is often referred to as the “tech with glasses”. When she is shown actually working with computers, she also is usually shown working alone in a darkened room. An eerily similar pattern emerges in the carácter of Abby Sciuto, the femal carácter in a computing role in another crime drama, NCIS. In some ways, of course, these characters are very positive developments because they are very likable female characters and some girls are likely to identify with them, see themselves represented and have thes aspects of their identities validated. Girls in IT: The Facts, published by NCWIT (Ashcraft et al., 2012) p. 28-29
 Seron, 2005
 American Association of University Women, 2000; Moorman & Johnson, 2003
 Gras-Velazquez et al., 2009
 Mason et al., 2007
 Barker & Aspray, 2006
 Varma, 2009
 Barron, 2004; Bruckman et al., 2002
 Hayes, 2008; Hughes, 2008; Kafai et al, 2008; Kelleher, 2008
 Hayes, 2008; Dresang et al. 2007
 Denner, 2011; Hayes, 2008
 e.g. Vygotzky, 1978; Harel & Papert, 1990
 e.g. American Association of University Women, 2000; Clark Blickentstaff, 2005; NAPEEF, 2009
 e.g. Anderson et al., 2008; Goode, 2007; Margolis et al. 2008; Lasen, 2010
 Lasen, 2010
 Clayton et al.,2009; Margolis et al., 2008; Papastergiou, 2008
 Aronson et al.,1999; Spencer et al., 1999
 e.g. Goode et al., 2006; Jenson et al., 2003; Girl Scout Research Institute, 2012
 e.g. Moorman & Johnson, 2003
 Barker & Gavin-Doxas, 2004; Sieverding & Koch, 2009
 e.g. Grant & Payton, 2008; Lasen, 2010; Teague, 2002
 Gras-Velazquez et al., 2009
 Olivieri, 2005
AAUW. (2000). Tech-Savvy: Educating Girls in a New Computer Age. AAUW Educational Foundation Commission on Technology, Gender, and Teacher Education.
Anderson, N., Lankshear, C., Timms, C., & Courtney, L. (2008). “Because it’s boring, irrelevant and I don’t like computers’: Why high school girls avoid professionally-oriented ICT subjects. Computers & Education, 50(4), 1304-1318.
Aronson, J., Steele, C.M., Brown, J., Lustina, M.J., Good, C. & Keough, K. (1999). When white men can’t do math: Necessary and sufficient factors in stereotype threat. Journal of Experimental Social Psychology, 35, 29-46.
Barker, L. J., & Aspray, W. (2006). The state of research on girls and IT. In J.M. Cohoon & W. Aspray (Eds.), Women and Information Technology: Research on Underrepresentation, (pp. 3-54). Cambridge: MIT Press.
Barker, L. J., & Garvin-Doxas, K. (2004). Making visible the behaviors that influence learning environment: A qualitative exploration of computer science classrooms. Computer Science Education, 14, 119-145.
Barron, B. (2004). Learning ecologies for technological fluency: Gender and experience differences. Journal of Educational Computing Research, 31(1), 1-36.
Bruckman, A., Jensen, C., & DeBonte, A. (2002). Gender and programming achievement in a CSCL environment. Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community, CSCL, 119-127.
Gras-Velazquez, A., Joyce, A., Debry, M. (2009). Women and ICT. Why are girls still not attracted to ICT studies and careers? White paper published by Cisco & European Schoolnet
Clark Blickenstaff, J. (2005). Women and science careers: Leaky pipeline or gender filter? Gender and Education, 17(4), 369-386.
Clayton, K. L., von Hellens, L. A., & Nielsen, S. H. (2009). Gender stereotypes prevail in ICT: A research review. Proceedings of the Special Interest Group on Management Information System’s 47th Annual Conference on Computer Personnel Research, SIGMIS CPR, 153-158.
Cozza, M. (2011). Bridging gender gaps, networking in computer Science. Gender, Technology and Development, 15(2), 319-337.
Denner, J. (2011). What predicts middle school girls’ interest in computing? International Journal of Gender, Science and Technology, 3(1).
Dresang, E. T., Gross, M., & Holt, L. (2007). New perspectives: An analysis of gender, net-generation children, and computers. Library Trends, 56(2), 360-386.
Girl Scout Research Institute. (2012). Generation STEM: What Girls Say about Science, Technology, Engineering, and Math. Girl Scouts of USA. Authors: Modi, K., Judy, S., & Salmond, K.
Goode, J., Estrella, R., & Margolis, J. (2006). Lost in translation: Gender in high school computer science. In J. Cohoon & W. Aspray (Eds)., Women and Information Technology: Research on Underrepresentation. MIT Press.
Goode, J. (2007). If you build teachers, will students come? The role of teachers in broadening computer science learning for urban youth. Journal of Educational Computing Research, 36(1), 65-88.
Grant, D. M., & Payton, F. C. (2008). Career staging for girls moving toward (away) from computing careers. Proceedings of the 2008 ACM SIGMIS CPR Conference on Computer Personnel Doctoral Consortium and Research, SIGMIS CPR, 43-49.
Guiso L, Monte F, Sapienza P, Zingales L. Culture, gender, and math. Science. 2008;320:1164–1165
Harel, I., & Papert, S. (1990). Software design as a learning environment. Interactive Learning Environments, 1(1), 1-32.
Hayes, E. (2008a). Girls, gaming and trajectories of IT expertise. In Y.B. Kafai, C. Heeter, J. Denner, & J.Y. Sun (Eds.), Beyond Barbie and Mortal Kombat: New Perspectives on Gender and Gaming, (pp. 217-230). Cambridge: MIT Press
Hayes, E. R., & Games, I. A. (2008b). Making computer games and design thinking. Games and Culture, 3(3-4), 309-332.
Hughes, K. (2008). Design to promote girls’ agency through educational games: The click! Urban adventure. In Kafai, Y. B., Heeter, C., Denner, J., & Sun, J.Y. (Eds.). Beyond Barbie and Mortal Kombat: New Perspectives on Gender and Gaming, pp. 231-246. Cambridge: MIT Press.
Hyde, J. S., & Linn, M. C. (2006). Gender similarities in mathematics and science. Science, 314(5799), 599-600.
Jenson, J., de Castell, S., & Bryson, M. (2003). “Girl talk”: Gender, equity, and identity discourses in a school-based computer culture. Women’s Studies International Forum, 26(6), 561-573.
Jepson, A., & Perl, T. (2002). Priming the pipeline. SIGCSE, 36-39.
Kelleher, C. (2008). Using storytelling to introduce girls to computer programming. In Y.B. Kafai, C. Heeter, J. Denner, & J.Y. Sun (Eds.). Beyond Barbie and Mortal Kombat: New Perspectives on Gender and Gaming (pp. 247-264). Cambridge: MIT Press.
Klawe, M. Girls, boys and computers, Inroads (the SIGCSE Bulletin), vol. 33, no. 2, 2002.
Lasen, M. (2010). Education and career pathways in information communication technology: What are schoolgirls saying? Computers & Education, 54(4), 1117-1126.
Margolis, J., Estrella, R., Goode, J., Holme, J., Nao, K., (2008). Stuck in the Shallow End: Education, Race and Computing. Cambridge, MA: MIT Press.
Mason, R., Cooper, G., & Comber, T. (2011). Girls get it. ACM Inroads, 2(3), 71-77.
Moorman, P., & Johnson, E. (2003). Still a stranger here: Attitudes among secondary school students towards computer science. SIGCSE, 35, 193-197.
NAPEEF. (2009). Nontraditional Career Preparation: Root Causes & Strategies. National Alliance for Partnerships in Equity Education Foundation.
OECD. Evolution of Student Interest in Science and Technology Studies, 2006.
Olivieri, L. M. (2005). High school environments and girls’ interest in computer science. SIGCSE, 37(2), 85-88.
Papastergiou, M. (2008). Are computer science and information technology still masculine fields? High school students’ perceptions and career choices. Computers & Education, 51(2), 594-608.
Sanders, J. (2006). Gender and technology: What the research tells us. In C. Skelton, B. Francis, & L. Smulyan (Eds.), The SAGE Handbook of Gender and Education (pp. 307-322). Thousand Oaks: Sage.
Seron, E. (2005). La socialisation différenciée. Pourquoi si peu de femmes? Au creux de la famille… http://www.ada-online.org/frada/spip36bd.html?rubrique135
Sieverding, M., & Koch, S. C. (2009). (Self-)Evaluation of computer competence: How gender matters. Computers & Education, 52(3), 696-701.
Spencer, S., Steele, C. & Quinn, D. (1999). Stereotype threat and women’s math performance. Journal of Experimental Social Psychology, 35, 4-28
Teague, J. (2002). Women in Computing: What brings them to it, what keeps them in it? SIGCSE, 147-158.
Varma, R. (2009). Gender differences in factors influencing students towards computing. Computer Science Education, 19(1), 37-49.
Voyles, M. M., Haller, S. M., & Fossum, T. V. (2007). Teacher responses to student gender differences. SIGCSE, 39(3), 226-230.
Vygotzky, L.S. (1978) Mind in Society. New York: Cambridge University Press
Wolkowitz, C. (2006). Bodies at Work. Thousand Oaks: Sage.
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