The researcher will be looking at women in technology, focusing on women in computer science. Specifically, the under representation of women in universities studying this field will be looked at. The researcher will look at numbers, statistics, and solutions to why there is such a discrepancy. The researcher will look at the ratio of men in computer science compared to women, and even look outside of the United States and see if there are countries where the ratio isn’t as un-proportial, or proportioned at all. Various techniques and findings people have and suggest are to be seen, to help more women study computer science.
In the article, Community College Men and Women: A Test of Three Widely Held Beliefs About Who Pursues Computer Science, the authors look at how to increase the number of computer and information sciences at universities, particularly women. The researchers conducted a longitudinal study that collected from 741 women and men from fifteen different community college in California who were enrolled in introductory programming classes. The results for men showed the importance of preparation and interaction with professors. For women, it was the significance of motivational, relation, and behavioral factors. A specific factor: peer support and expectations for success in computing and computer games.
Sylvia Beyer wrote Why Are Women Underrepresented In Computer Science? Gender Differences In Stereotypes, Self-Efficacy, Values, And Interests And Predictors Of Future CS Course-Taking And Grades. The study looks at why women are underrepresented in Computer Science. Sylvia Beyer obtained data from 1,319 American, first-year college students that indicated that there exists a gender difference in computer self-efficacy, stereotypes, interests, values, interpersonal orientation, and personalities. A student having a positive experience in their first computer science was more likely to take another one. Beyer suggests that this underrepresentation is not inevitable. To make changes, we need a clear understanding of the reasons they are not as high in numbers. She suggests social psychological variables that can be observed. She also saw that having a terrific instructor influences students to continue with CS also.
In the article, Classrooms Matter: The Design Of Virtual Classrooms Influences Gender Disparities In Computer Science Classes, the author conducted three experiments examining if the design of virtual learning environments influences undergraduates’ enrollment intentions and anticipated success in introductory computer science classes.
The work was specifically done on whether the design of 3-D VLEs influence gender disparities in computer science. They found that changing the design of a virtual classroom from one that portrays current computer science stereotypes to one that does not, significantly increases women’s interest and potential success in computer science.
Men’s interest and anticipated success was not changed from environmental changes. Statistical analysis showed that the stereotypical virtual classroom brought on a lower sense of belonging for women. There was a lack of “ambient belonging” in the stereotypical room. The researchers want to study why objects stereotypically involved with computer science steer away. They argue that re-designing VLEs may help underrepresentation of women in computer science. The researchers mentioned a potential limitation of the study was that the stereotypical room was presented first to the participants in the experiment.
In Enduring Influence Of Stereotypical Computer Science Role Models On Women’s Academic Aspirations, the paper examines whether small exposure to a stereotypical computer science role model has a lasting influence on women’s interest for computer science. One hundred undergraduate women, non-computer science majors met a male or female peer role model who fit computer science stereotypes, or they met a role model with no stereotypes. The interaction lasted two minutes.
Exposure to the stereotypical role model had an immediate and negative effects on women’s interest in computer science. This result was because of women’s reduced sense of belonging. Whether the role model was male or female had no effect. The researchers hypothesized that women’s interest in computer science would be compromised by exposure to a stereotypical role model. It would lead to a lower sense of belonging. They were right in their hypothesis. Non-stereotypical male role models were more effective in increasing women’s interest than female role models who fit the stereotype.
The researchers found that sharing a unique similarity or emphasizing values helps women into the field. They also found that gender of a role model does not only matter, but whether a potential role model conveys to women a sense of belonging in the field.
The article, The Stereotypical Computer Scientist: Gendered Media Representations As A Barrier To Inclusion For Women examines undergraduates’ stereotypes of people in computer science, and whether the media can change the stereotypes to have more women. Two studies were done. Women who read that computer science no longer fit the stereotypes, express more interest than those who read otherwise. A stereotype in computer science that mentioned is that computer scientists are technology-oriented, with strong interests in programming and electronics. The perception is that they are less likely to help others compared to people with different careers.
This stereotype was held by both male and female students. The stereotype may cause women to express less interest in the field than men. A second stereotype: computer scientists are so focused on technology that they are obsessed with computers and programming: to the exclusion of others. This stereotype deters more women than men. Another stereotype is that computer scientists lack interpersonal skills and are socially awkward.
The evidence suggests that male undergraduates are more likely to endorse this stereotype than females, although women may be deterred by it. The computer ‘nerd’ or ‘geek’ stereotype discourages women from pursuing computer science. The researchers also argue that these stereotypes are not compatible with characteristics women are expected and may wish to possess, like working with and helping others.
The authors in Diversity Or Difference? New Research Supports The Case For A Cultural Perspective On Women In Computing argue that looking at gender difference for participation of women in computing, doesn’t explain women’s declining interest. They focus on culture. They show the significance of cultural factors by describing a case study examining attitudes of computer science majors at Carnegie Mellon University.
They found no difference in attitude between genders. They describe culture as belonging to everyone, being part of our everyday experiences, and being “made and remade.” The authors use this term for culture defined as referring to the complex and broad set of relationships, values, attitudes, and behaviors binding a specific community ‘consciously’ and ‘unconsciously.’
The authors argue that gender is often constructed differently in different cultures, so taking a cultural approach allows us to see more clearly and convincingly that many characteristics considered natural to men and women are actually produced in specific cultures. Cultural factors like faculty approachability, environment, social fit, academic fit, and ingredients for success were observed.
They found that inclusive culture still exists, and that a women-CS “fit” has been sustained without accommodating presumed gender differences. They argue that attitudes toward CS aren’t deeply rooted, nor specific to one gender, which makes it very disjointed. They found that it’s determined by factors within culture and the environment.
Catherine Ashcraft, in Technology And Sexuality –What’s The Connection? Addressing Youth Sexualities In Efforts To Increase Girls’ Participation In Computing, Learning, Media And Technology says that a lot of programs looking at under representation of women in technology take a narrow view of their purpose, ignoring important factors that shape identities and education/career choices. The paper focuses on the issue of sexuality. The author explains how sexuality discourses are shaping a diverse range of girls’ experiences with technology, their perception of themselves and their ultimate choices in their educational and professional life.
The author emphasizes sexuality in technology education. She says there a connection between youth sexuality and technology. Also, says that sexuality influences two barriers to girls’ and women’s participation in computing: by stereotypes and work-life conflicts in technology workplaces. Ashcraft argues that progressive sexuality education and increasing acceptance of and funding for this education will lead to increasing effectiveness of computing programs.
This article, by Roli Varma Why So Few Women Enroll In Computing? Gender
And Ethnic Differences In Students’ Perception examines reasons behind low enrollment of women in computer science and computer engineering education. It’s based on 150 in-depth interviews of female and male undergraduates in the major. The interviews included whites, African-Americans, Hispanics, Asian-Americans, and Native Americans students
The study found bias in early socialization and anxiety toward technology as being two reasons. There was significant gender and ethnic differences in student responses on why enrollment for women is so low. The students’ statements suggest that society, including family members, have higher expectation for boys than girls. Also, children are taught by teachers with a bias that girls are good in fields not technology related, why boys are.
Most of the female students interviewed said that they found anxiety in technical fields either due to lack of exposure/use of computers or because of an outcome of gendered socialization. There was significant gender and ethnic differences on students’ perception about why women’s representation is so low.
Female students point to gendered socialization and technical anxiety. White students, more so, blamed only gendered socialization. Asian Americans lean towards role played by technical anxiety. There were ethnic differences in women, but not men. Native American females feel some other reason is to blame other than gendered socialization or technical anxiety. There was also a divide between Whites and African-Americans.
Varma says that the study suggests that teachers in elementary, middle, and high school need to improve their style of teaching to not be, so stereotypical in focusing on math and science for boys. Another suggestion is that girls’ math and programming skills should be developed and/or improved by the time they reach university. Also, having classrooms in universities (Virtual or actual) that are gender neutral, or even female-friendly can help helpful. For example, not having a classroom filled with video games posters, but instead art could be considered neutral as video games are stereotypically associated with males.
The article, See Feminine Think Incompetent? The Effects Of A Feminine Outfit On The Evaluation Of Women’s Computer Competence the authors look at whether the outfit of a woman leads to a stereotype of women’s lower computer skills. The study was done in Germany, it includes 162 participants (105 women, fifty seven men). It evaluated the same women competing for an information technology-related student job. The women wore either a neutral outfit, or a feminine one, and that was the only difference.
It was found that the feminine outfit had higher ratings of femininity, but lower ratings of computer skills. Also, unfavorable attributions of success and/or failure in computer tasks. There was found to be a high attribution of success to luck and failure to lack of skills. The women wearing the feminine outfit was rated to be less intelligent, less competent, and less likeable. And, males rated themselves to have higher computer skills than females.
Ulf Mellström, in his paper The Intersection Of Gender, Race, And Cultural
Boundaries, Or Why Is Computer Science In Malaysia Dominated By Women? investigates how and why computer science is dominated by women in Malaysia. The author aims to open up more culturally situated analyses of gendering of technology or technology of gendering. He critiques analytical asymmetry in process of co-production in gender and technology studies. He critiques the western bias, advocating more context sensitivity and focus on cultural embeddedness of gender and technology relations.
Mellström suggests that more attention should be paid to spatial practices and body politics in regard to race, class, and gender. He also opposes the western positional notions of gender configuration that opens up for more fluid constructions of gender identity. The study wants to look at relational and positional definitions of femininity and masculinity. He says there is a western bias of gender and technology studies, and argues for cross-cultural work and intersectional understandings.
The author did a 150 student questionnaire survey. It included 111 women, and thirty nine men. The women comprised of sixty eight Malays, thirty eight Chinese, and five Indians. For the men, there were twenty Malays, seventeen Chinese, and two Indians. The questionnaire focused on gender, ethnicity, family structure, educational choice, and career plans. The author also noticed that Malay women are studying engineering, science, and management fields in large numbers. While, the men are studying for government positions and studying in fields like Bahasa Malaysia, Islamic Studies, and Social Sciences.
In the article, Gender Gap in Computer Science Does Not Exist in One Former Soviet Republic: Results of a Study,” the authors look at Armenia. They says countries of the former Soviet Union are different from America’s in society, culture, and educational system. This could be a large reason why there is a big amount of women in computer science in Armenia. Throughout all of the 1980’s and 1990’s in Armenia, the percentage of women in computer science never fell below 75%, even though Armenia traditionally is a male-dominating culture.
The study looks to compare and contrast what attracts or doesn’t attract women to computer science in America or former Soviet Union countries. There were three different surveys done with 23 questions for three different groups of people. it included people majoring in computer science, non-computer science majors, and graduate professionals in other fields.
The survey was 538 individuals (240 males and 226 females). 85 people were also interviewed. Looking at Armenia, 31% of women consider computer science recently. The author says that factors leading to the under-representation of women in computing is because CS is male dominated, girls get intimidated, and feel isolated. Further, there aren’t role models for young women, and women don’t get the same respect as men, not the same opportunity, or success.
In Armenia, surveys show said that men are only bothered if there is a low number of women, not men. There are not role models in Armenia also. Unequal treatment for women happens in computer science, and others fields. Though, when both young Armenian men and women choose the CS major, they have the same mindset (motivation, goals, and influences). Young people are very mature in planning their futures. In Armenia, computer science is more considered math than engineering. Male dominating fields aren’t intimidating to women, and not having role models is not a concern.
In this proposal the researcher aimed to see why there is such an under representation of women in studying computer science in the United States. The researcher wanted to see various techniques and findings researchers have and/or suggest increase women in computer science. The researcher also wanted to look outside of America and see how the ratio of men to women in computer science is. From the research done, the researcher saw that factors to increase the number of women in computer science include: having a great instructor/professor, peer support, expectation for success, limiting stereotypes, sharing a unique similarity and emphasizing values for role models, progressive sexual education, encouragement by teachers in elementary/middle/high school, improved style of teaching to not be stereotypical, girls’ math and programming skills developed and/or improved by university, and having user friendly female classrooms.
Understanding why there is such an under-representation can come from having a bad experience in your first computer science class, stereotypes, stereotypical role models (Which reduces a sense of belonging), cultural factors, environmental factors, early bias in socialization, anxiety toward technology, family influence, grade school teachers influence, and lack of exposure/ use of computers.
The researcher looked at three different countries: Germany, Armenia, and Malaysia. Germany and Armenia are both western countries, but produced different results. In Germany, a study was done where it was found that feminine outfits worn by females, opposed to neutral ones, led to stereotypes of women’s computer skills. In Armenia, a former Soviet Union country, is said to be different from America is society, culture, and educational system. There are a lot more women in computer science, compared to the States. In this article it was argued that there is an under-representation of women in computer science in America was it is male dominated, intimidating to women, women don’t get the same respect, opportunity, or success as man; and there are few role models for women.
Seeing these two countries, it would be argued that countries in the west, generally have under representation of women in computer science. A country like Armenia being different because the Soviet Union’s culture was different, and isolated from the rest of Europe. The argument could go more so to Western Europe. Additional research would have to be done to make conclusive findings. A last country, Malaysia, is not North America or Europe, so it was intriguing to see the vast difference there. Malay women study in technology in large numbers, while the men do not. The article argued there is a western bias of gender and technology studies, and called for cross-cultural work and intersectional understanding. Seeing these results, you can see that countries in Asia, possibly others, don’t have this under representation. There are other countries that have high number of women in technology like India or China, and more research would have to be done to compare and contrast western to non-western countries.
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