Posts tagged ‘NCWIT’
Following up on the brief that Google did last month on Blacks in CS, this month they’ve prepared a brief on the state of girls in CS.
Computer science (CS) education is critical in preparing students for the future. CS education not only gives students the skills they need to succeed in the workforce, but it also fosters critical thinking, creativity, and innovation. Women make up half the U.S. college-educated workforce, yet only 25% of computing professionals. This summary highlights the state of CS education for girls in 7th–12th grade during 2015–16. Girls are less likely than boys to be aware of and encouraged to pursue CS learning opportunities. Girls are also less likely to express interest in and confidence in learning CS.
Expanding the Pipeline: Characteristics of Male and Female Prospective Computer Science Majors – Examining Four Decades of Changes – CRN
Interesting report from CRA that offers a nuanced view about gender differences in goals for STEM education and how those interact with pursuing a degree in CS.
Another example of a variable becoming more salient over time relates to one’s scientific orientation. Students of either gender who express a stronger commitment to making a “theoretical contribution to science” are more likely to pursue a computer science major, but over time this variable has become a significantly stronger predictor for women while remaining a steady predictor for men. In other words, it is increasingly the case that computer science attracts women who see themselves as committed to scientific inquiry. While at face value that seems like positive news for the field of computer science, the fact is that women are much less likely than men to report having a strong scientific orientation upon entering college; thus, many potential female computing majors may be deterred from the field if they simply don’t “see” themselves as the scientific type.
Still, there is some positive news when it comes to attracting women to computing. The first relates to the role of mathematical self-concept. Specifically, even though women rate their math abilities lower than men do—and perceptions of one’s math ability is one of the strongest predictors of a major in computer science—the fact is that the importance of mathematical self-concept in determining who will pursue computer science has weakened over time. Thus, despite the fact that women tend to have lower math confidence than men do, this differential has become less consequential over time in determining who will major in computer science.
Carol Frieze and Jeria Quesenberry’s book on women in computing at CMU, Kicking butt in computer science, has been in my Kindle archive for several months now. Dan Zingaro’s review in this month’s ACM Inroads is moving it up my to-read queue.
For me, the edgy title of the book promised a fiery romp through the halls of Carnegie Mellon University (CMU), wherein the stories of butt-kicking women in computer science (CS) are told. Anecdotes of successful women in CS, chronicles of their rise to butt-kicking status—this is what I expected. This is not what I got. What I got was more useful—a careful academic treatise of women in CS at CMU, and a cache of food-for-thought for anyone hoping to improve the women and computer science (women-CS) fit at their schools.
The book’s thesis is simple, if contentious—a focus on gender differences does not work; a focus on culture does.
Source: ACM Inroads: Archive
One of my favorite papers is the analysis of Stayers vs Leavers in undergraduate CS by Maureen Biggers and colleagues. This new research published by the CRA explores similar issues.
We also looked at words associated (correlated) with these two sets of words to give us context for frequently cited words. When talking about thoughts about leaving, students were particularly likely to associate “weed-out” with “classes”. They were also likely to use words such as “pretty” and “extremely” alongside “hard” and “difficult”, which sheds light on computing students’ experiences in the major. When talking about staying in their major, students cited words such as “prospect”, “security”, “stable”, and “necessary” along with the top two most commonly used words: “job” and “degree”. For instance, one student said: “[I thought about changing to a non-computing major because of] the difficulty of computing. [But I stayed for] the security of the job market.” Yet another student noted: “The competitive culture [in my computing major] is overwhelming. [But] the salary [that] hopefully awaits me [helped me stay].” Furthermore, students used the words “friends”, “family”, and “support” in association with each other, suggesting that friends and family support played a role in students’ decision/ability to stay in their computing major. As a case in point, one student noted: “The material is hard to learn! I had to drop one of my core classes and must take it again. But with some support from friends, academic advisors, more interesting classes, and a more focused field in the major I have decided to continue.”
Thanks to Greg Wilson for sending this to me. It takes a while to get to the point about computing education, but it’s worthwhile. The notion is related to my post earlier in the month about engagement and motivation.
I’d been socialised out of using computers at high school, because there weren’t any girls in the computer classes, and it wasn’t cool, and I just wanted to fit in. I wound up becoming a lawyer, and spending the better part of twenty years masquerading as someone who wasn’t part of the “tech” industry, even though basically all of my time was spent online.
And I can’t begin to tell you how common it is. So what if your first experience of “code” is cutting and pasting something to bring back replies because Tumblr took them away and broke your experience of the site.
Is that any more or less valid than any dev cutting and pasting from Stack Exchange all day long?What if your first online experiences were places like Myspace and Geocities. Or if you started working with WordPress and then eventually moved into more complex themes and then eventually into plugin development? Is that more or less valid than the standard “hacker archetype”? Aurynn gave a great talk recently about the language we use to describe roles in tech. How “wizards” became “rockstars” and “ninjas”. But also, and crucially, how we make people who haven’t followed a traditional path feel excluded. Because they haven’t learnt the “right” programming language, or they haven’t been programming since they were four, or because, god forbid, they use the wrong text editor.
A really interesting set of proposals. I saw many that are applicable to improving diversity in higher-education CS, as well as the stated goal of improving workplace diversity.
Workplace diversity is probably the biggest factor inhibiting women in computing. We used to say that females avoided CS, not knowing what it is. I think we can now fairly say that many females avoid CS because they know what it is.
This is a great ending blog post of 2016. See you in January! Happy Holidays and a Great New Year!
Over the past few months, we and our colleagues at OSTP have had conversations with dozens of Federal agencies, companies, investors, and individuals about their science and technology workforces, and we have consistently heard people express a commitment to bringing more diversity, equity, and inclusion to their workplaces. They understand the strategic importance. Yet often we found that many of the same people who want to create high-performing, innovative teams and workforces do not know the steps and solutions that others are already effectively using to achieve their diversity, equity, and inclusion goals.
In order to help accelerate this work, we have compiled insights and tips into an Action Grid designed to be a resource for those striving to create more diverse, equitable, and inclusive science and technology teams and workforces, so that we can all learn from each other.
Diversity, equity, and inclusion work is not one size fits all. We hope this set of potential actions clustered by leadership engagement, retention and advancement, hiring, and ecosystem support provides ideas and a jumping off point for conversations within your team or organization on steps that you can take to increase diversity and to make your workforce more reflective of the communities you serve, customers you sell to, and talent pools you draw from.
I found these differences fascinating, though I’m not sure what to make of them. Once leaving computing, students head to different majors with a big gender difference. Only 5% of women go into an Engineering field after CS, while 32% of men go into some form of Engineering. Why is that?
As computing departments across the U.S. wrestle with increased enrollment, it is important to recognize that not everyone who becomes a computing major stays a computing major. In 2014, CERP collected data from a cohort of U.S. undergraduate students who agreed to be contacted for follow-up surveys in 2015. While most of the students surveyed remained computing majors (96%), some students changed to a non-computing major. As shown in the graphic above, students in our sample moved to a variety of majors, and the type of new major tended to differ by gender. Most men (69%) who left a computing major switched to engineering, math/statistics, or physical science majors. On the other hand, most women (53%) tended to move to social sciences, or humanities/arts. These data are consistent with existing social science research indicating women tend to choose fields that have clear social applications, such as the social sciences, arts, and humanities. CERP’s future analyses will explore why women, versus men, say they are leaving computing for other fields.