Posts tagged ‘women in computing’
After my post claiming that Georgia Tech’s Computational Media program is the most gender-balanced, ABET-accredited computing undergraduate degree program in the United States, I had several people ask, “But that’s enrollment. Do the women graduate? Do they stick with the program?” My sense was that they did, but I asked our College data person, Elijah Cameron, and he sent me the below. Last year, BS in Computational Media graduates were over 40% female. Pretty good.
Fascinating analysis! It turns out that the number of women getting degrees in CS actually rose in the early 2000’s, but the percentage shared dropped because so many men women were taking CS, too.
Here’s the number of women getting CS degrees:
Here’s the percentage view:
The gains by women actually weren’t keeping up with the overall increase in the population of CS grads. More men were filling those seats than women. As a share of all CS bachelor’s degrees granted that year, females had slipped almost 10 points, from 37% in 1984/1985 to 27% in 2003. The overall trendline was clearly downward, as seen below.
Interesting question: When do toys lead to changes in stereotypes, and when don’t they?
Why is including female scientists in toys for young kids so important? Because children begin making stereotypical assumptions of what a scientist looks like early in elementary school, and these stereotypes become more firmly implanted year-by-year. Starting in 1957, several research groups have asked school children to “draw a scientist” in order to probe these stereotypes. Normally, when someone is asked to draw a generic person they will draw a person of their own gender. This is not true when children are asked to draw scientists. In study after study, the vast majority of students of both genders draw a scientist as a white man in a lab coat.What is really fascinating is that several studies—although not all—have found that these stereotypes can be changed by simply exposing children to female and/or minority scientists. After interacting with diverse examples of scientists, children made more realistic images of scientists—portraying them without dangerous, smoking test tubes for example—and were more likely to draw female and minority scientists.
Of course, I buy into the argument here about the importance of context. Beyond that, this article does a nice job of tying context to success of women in computing (with quotes both from Barbara Ericson and Valerie Barr, formerly at NSF).
“Boys fall in love with computers as machines; girls see them as tools to do something else,” said Barbara Ericson, a senior research scientist at the Georgia Institute of Technology who tracks the AP exam. “Then girls think, ‘maybe I don’t belong because I don’t love them like the boys do.’”
In her position as a professor of computer science at Union College, Barr found contextualizing computer science classes led to an increase in female enrollment. “We said, ‘let’s show them that computer science can be useful by giving themes to the introductory CS courses, so students can see their relevance,’” she said. “For us, it’s been enormously successful. Ten years ago we taught the introductory course to 29 students, and 14% of them were women. This year there were over 200 students, and 39% of them were women.” Beyond college, Barr said, she’d also like to see “a bigger funnel into the corporate world and the tech industry, with people coming from many other majors. It doesn’t have to be just CS majors.”
10 Reasons Why America Needs 10,000 More Girls in Computer Science: Need to change girls’ minds about girls
Nice article from Ruthe Farmer on why we need more girls in CS. The point quoted below is particularly interesting to me, and relates to a recent Blog@CACM post: student perceptions matter. It’s not just the males who need to realize that females are good at math. Girls sometimes take themselves out of the competition.
The idea that girls can’t do math or succeed in science is a silly myth that needs to be put to rest. Girls made up 63 percent of the 2013 Intel ISEF finalists in biochemistry, accounted for 46 percent of all Advanced Placement AP Calculus test-takers in 2013 (See http://ncwit.org/bythenumbers), and contributed 47 percent of the winning projects in the Google Science Fair. But it’s not only boys who need to get the message about girls’ abilities: According to the Atlantic, female test-takers around the world reported feeling “helpless” while doing a math problem, although they scored within striking distance of their male counterparts. In other words, there is an abundance of girls who are good at math and science, but a lack of girls who know it.
Jennifer Whitlow here at the College of Computing at Georgia Tech just posted enrollment statistics about our undergraduate degrees, BS in Computer Science and BS in Computational Media (a joint degree between Computing and the School of Literature, Media, and Communications in our Ivan Allen College of the Liberal Arts). (You can read student impressions about CM here.) We’re now at 1665 undergraduate majors, the largest ever.
This is a huge table — click on it to make it bigger.
The gender diversity in the BS in CS is improving significantly — from 9% in 2004, up to 19.91% this year. But it’s the CM major that I find most intriguing. It’s gone from the 25-30% female up to 45.32%. At 45% female, I believe that it may be the most gender-balanced ABET-accredited computing undergraduate major at any US state university. (Private schools with more control over admissions could be higher.) That’s really something — dramatic and important. CM graduates are getting good jobs (in the top starting salaries coming out of Georgia Tech undergrad, well into six figures). My son just graduated with a CM degree in May, and has now started a CS PhD — evidence that the degree is getting respect at CS departments too.
But there’s an interesting research question in here, too. CM is shrinking.
CM was at its largest in 2010 with 300 majors. Today it has only 214 majors. The number of women in CM has continued to increase every year until this last. It’s obvious what’s going on: we’re losing men.
Computational Media at Georgia Tech may be the only computing program in the country that is wondering, “Where did the men go?” CM is clearly doing the right things to recruit, engage, and retain women. Why are we losing men? What is having a differential impact in terms of gender, that started about 2010?
One hypothesis is that it’s because of competition with the BS in CS, and in particular, with our threaded curriculum with threads available like Media and People. But Threads started in 2005, same as the CM major, and CM grew while CS shrank from 2005-2011. While the faculty know from hiring statistics that CS and CM are neck-and-neck in terms of starting salaries and jobs offered, it’s not clear that the students know this. It’s not clear why any competition with CS would suddenly rise in 2010, and then impact men more than women.
Another hypothesis is that CM is perceived as being easy — it’s “CS lite.” You can see that perspective in the student comments I linked to earlier. The hypothesis has two parts (a) that CM is perceived as easy, and (b) that men are more dissuaded by a degree being labeled easier than women. Both are empirical questions, and I don’t know the answers to either. If we’re looking for changes in the CM program that might have triggered change, it is true that we recently made CM harder. Two years ago, we found that CM students were struggling too much in graphics, so we added a new requirement: a challenging course in data structures and algorithms — the same one that the CS majors take. CS and CM are virtually identical for the first two years. Did making CM harder drive away men without driving away women? Seems unlikely, but it’s possible.
Here’s yet another hypothesis: CM has become “feminized.” See http://brookekroeger.com/the-road-less-rewarded-as-professions-become-female-dominated-status-and-pay-seem-to-slip-now-researchers-are-asking-why-and-turning-up-some-surprising-conclusions/ for some discussion of what happened in psychology as it became female-dominant, a UNESCO report on the feminization of education, or see a more detailed and academic consideration here:
When a field becomes feminized, it is perceived as “softer” and less-desirable by men. CM enrollments started declining in 2011, after the percentage of females in CM passed 30%.
So here’s this wonderful result, that CM is nearly at gender-parity, with this strange additional observation — men are less interested in CM now. We’d rather have gender balance and stable (or preferably, growing) numbers of both genders. The success of CM is the major story here, and we want to keep women in CM. It’s an interesting question of where the men went. Can we keep the successes of CM, and get men interested, too?
Matthew Guzdial, Jane Margolis, and Lecia Barker reviewed earlier drafts of this post and gave me very useful comments that I have incorporated. My thanks to all of them! I did not however use all of their comments, so hold me alone responsible for these comments.
Below is the article on Facebook’s diversity figure release. (Google really did lead the pack here.) Here’s Twitter’s, LinkedIn’s, and EBay’s. For those of us doing this work, these are not surprising results. But they are super important for showing us where we are now. We have very little diversity in the computing industry. This gives us a sense of what we need to work on, and how to measure progress.
Sadly, Facebook’s numbers look a lot like the other four. I’ll let the figures speak for themselves:Globally the company is 69 percent male, 31 percent female. In terms of ethnicity the company is 57 percent white, 34 percent Asian, 4 percent Hispanic, 3 percent two or more races, 3 percent black and 0 percent other.Scrutinized further, in the tech force of Facebook, 85 percent are male and 15 percent are female. In terms of ethnicity in the tech division 53 percent are white, 41 percent are Asian, 3 percent are Hispanic, 2 percent are two or more races, 1 percent is black and 0 percent is other.