Posts tagged ‘women in computing’
A recent article in The Chronicle talked about just how white higher education faculty are — see article here. Most of the student protests about equity and diversity on college campuses this last year demanded more minority faculty.
In this graph, I found a different and fascinating story in just the first two bars in each set:
Professors are overwhelmingly male. Associate professors are only slightly more male. Assistant professors are slightly more female. Instructors are much more female.
It’s not surprising, but it’s interesting to see it. The women in academia have the lion’s share of the lower status jobs, and the men have the lion’s share of the higher status jobs. When you take into account the landed-gentry/tenant-farmer relationship between the tenure track faculty and the teaching track faculty (see previous blog post), the relationship between gender and academic power becomes much more stark.
Summarizing the Research on Designing Programming Languages to be Easier to Learn: NSF CS Ed Community Meeting
I’m at the NSF STEM+Computing and Broadening Participation in Computing Community Meeting. At our ECEP meeting on Saturday, we heard from White House Champion of Change Jane Margolis. She did a great job of getting our states to think about how to change their state plans to emphasize diversity and equity — more on that in a future blog post.
I moderated a panel yesterday on how to integrate computing education into schools of education. Here’s the description of the session — again, more later on this.
Integrating Computing Education into Preservice Teacher Development Programs
(Mark Guzdial (moderator), Leigh Ann DeLyser, Joanna Goode, Yasmin Kafai, Aman Yadav)For computing education to become ubiquitous and sustainable in US K-12 schools, we need schools of Education to teach computing.
- What should we be teaching to preservice teachers?
- Where should we teach CS methods in preservice teacherdevelopment?
- How do we help schools of Ed to hire and sustain faculty who focus on computing education?Panelists will talk about how CS Ed is being integrated into their preservice teacher development programs, and about alternative models for addressing these questions.
Yesterday, our other computing education research Champion of Change, Andreas Stefik presented a summary of the empirical evidence on how to design programming languages to make them easier to learn. Follow the link below to get to the two-page PDF pamphlet he produced for his presentation — it’s dense with information and fascinating.
This pamphlet is designed to provide an overview of recent evidence on human factors evidence in programming language design. In some cases, our intent is to dispel myths. In others, it is to provide the result of research lines.
Sarah Guthals, a CS Education Researcher, was identified by Forbes Magazine as one of the “30 under 30” scientists to watch in years to come. Congratulations to Sarah! She wrote an interesting blog post on imposter syndrome and the nomination.
I have suffered from imposter syndrome for at least a decade. I have worked hard, but it’s really hard for me to believe that I deserve what I have, or that the accomplishments that I’ve made are valid. I recognized my imposter syndrome when I was in my first year of grad school and since then I have been really trying to combat it — but I think instead I have just been ignoring it. Let’s see if I can explain it in the context of this weeks events.
When I found out I was nominated, I was very happy, but already feeling like a fraud. Am I really the one that should be nominated? What have I done to deserve it? I haven’t done anything alone (always had a team or partner).
Teenage boys are perhaps more known for playing computer games but girls are better at making them, a University of Sussex study has found. Researchers in the University’s Informatics department asked pupils at a secondary school to design and program their own computer game using a new visual programming language that shows pupils the computer programs they have written in plain English. Dr Kate Howland and Dr Judith Good found that the girls in the classroom wrote more complex programs in their games than the boys and also learnt more about coding compared to the boys.
Valerie Barr wrote a recent blog post about the state of the labor pool for STEM workers, especially in computing. I particularly liked her point about the need to provide learning opportunities to bring women back who have left the tech industry. Caroline Simard’s report on the needs of female mid-level tech managers (see blog post here) is what got me thinking about ebooks originally. Caroline’s female mid-level tech managers needed to learn about new technologies, while still balancing a demanding job and more family responsibilities than their male counterparts. That’s where I saw a need for something like our ebooks, to provide computing learning opportunities that fit into busy lives (see ebook post). I see Valerie calling for something similar — we need more pathways to learn about computing for adults (see blog post here), and those pathways might help us to broaden participation in computing.
It is true that the industry changes quickly in some ways, with new tools, new approaches, and new languages. But there is a rich pool of potential employees who are being completely overlooked. The many women who have left tech positions could be brought back in and given training to bring them up to speed on the newest languages and development practices. But this is a reasonable approach only if, at the same time, the tech industry makes a commitment to improving climate. There is no point in bringing back people who left tech if they are simply going to want to leave again in another 5 years. In fact, I imagine that bringing back a group of tech veterans who have greater maturity and experience could do wonders to improve climate in some of the tech companies. But the companies have to commit. And they have to recognize that you can still be a cutting edge agile company even if the average age of your employees ticks up a bit.
Lucy Sanders is one of my heroes, so I’m always happy to link to articles about her. The point she’s making below is particularly interesting, and relates to previous posts about “grit” (see link here), and to the “lean in” phenomenon.
NCWIT isn’t just about getting women into tech jobs. It’s about getting women to share their perspective and knowledge. It’s about making sure women are not avoiding those leadership jobs or shirking from innovation because of something called unconscious bias.”There’s a big conversation going on now with what we call ‘fixing women.’ You hear things like ‘If women were just more confident.’ Or ‘If women were only better risk takers.’ We don’t subscribe to that. And we don’t subscribe to men being the biased, evil ones because research shows that all of us have this bias about who does technology,” Sanders said. “The ultimate goal, of course, is to make sure women and men are innovating equally in technology.”
It’s an interesting and open question. Nathan Ensmenger suggests that we have no evidence that computer scientists need a lot of mathematics (math background has been correlated with success in CS classes, not in success in a CS career), but the emphasis on mathematics helped computing a male field (see discussion here). Mathematics has both been found to correlate with success in CS classes, and not correlate with success in object-oriented programming (excellent discussion of these pre-requisite skill studies in Michael Caspersen’s dissertation). It may be true that you don’t have to be good at mathematics to learn to code, but you may have to be good at mathematics to succeed in CS classes and to get along with others in a CS culture who assume a strong math background.
People who program video games probably need more math than the average web designer. But if you just want to code some stuff that appears on the Internet, you got all the math you’ll need when you completed the final level of Math Blaster. (Here’s a good overview of the math skills required for entry-level coding. The hardest thing appears to be the Pythagorean theorem.)