Posts tagged ‘NCWIT’
“I had so many advantages, and I barely made it”: Stanford alumna and Pinterest engineer on Silicon Valley sexism
I’m a believer in empirical evidence, and I worry about getting a representative sample. Sometimes, the right size sample for the question is one. CS is now the biggest major among women at Stanford (see article here). Do the issues that Jane Margolis and Alan Fisher described in Unlocking the Clubhouse still exist there?
As the article linked below describes, women don’t always feel welcome in CS at Stanford. It’s hard to address the issues of classroom culture described. Having separate classes for different groups of students with different backgrounds/interests (as at Harvey Mudd does) might help.
I know of even worse experiences at other CS departments. The Stanford CS teachers actively encourage women. There are still CS teachers who discourage women in their classes. It’s hard to get administrators to focus on broadening participation in computing in the face of overwhelming enrollment. It’s even harder to push better teaching from the top down. “Teachers have academic freedom,” is a common response to requests to change teaching (see my efforts to incentivize active learning) — we allow teachers teach anyway they want. It isn’t clear that still makes sense when there are empirically better and worse ways to teach. That’s like letting modern doctors use bloodletting or not wash their hands (see NPR piece making that argument).
At Stanford, I took two introductory computer science classes. I soon became convinced that I was much too behind my male classmates to ever catch up. I was surrounded by men who’d breezily skipped prerequisite courses. As freshmen, they’d signed up for classes that I was intimidated to take even as a sophomore. They casually mentioned software engineering internships they had completed back in high school, and declared they were unfazed by any of the challenges professors might throw our way. My classmates bragged about finishing assignments in three hours. I told myself that they were quantifiably five times better me. I remember the first “weeder” computer science course I took–meant to discourage the unworthy from pursuing the major. My classmates bragged about finishing assignments in three hours. Listening to them chat, I felt mortified: the same work had taken me 15 hours of anguish at the keyboard to complete. They are quantifiably five times better than I am, I told myself.
So what does convince people about a need to change? Stories? Personal experiences? Poking around on the Web, you can find lots of pages about motivating change and salesmanship, but I’m more interested in the question of how do we get people to recognize the Platonic cave. What they think is true is measurably and provably not true.
Now, a new study published by the Proceedings of the National Academy of Science (PNAS) shows another level of bias: Many men don’t believe this is happening.When shown empirical evidence of gender bias against women in the STEM fields, men were far less likely to find the studies convincing or important, according to researchers from Montana State University (MSU), the University of North Florida, and Skidmore College.
Betsy DiSalvo and I did a study of women in computing who chose not to participate in our OMS CS program. One of the reasons we heard was that these women were experienced with computing education. They all had undergraduate degrees in computing. Every one of them talked about the sexism rampant in their classes and in the industry. They were unwilling to be in a mostly-male online program.
We used to talk about getting the word out to women about the great job available in the tech industry, and about how that would attract more women. I fear that women today who are choosing not to go into the tech industry are doing so because they do know what it’s like.
A new study finds that sexism is rampant in the tech industry, with almost two-thirds of women reporting sexual harassment and nearly 90 percent reporting demeaning comments from male colleagues.The study, called “Elephant in the Valley,” surveyed 200 women who work at tech companies, including large companies like Google and Apple as well as start-ups. The study focused on women who had 10 years of experience in the industry, and most worked in Silicon Valley.
The basic facts of this infographic were things I knew. Some of the details, particularly at the end were new for me — like I didn’t know that the quit-rate gap between men and women increased with age. (Thanks to Deepak Kumar who pointed to this infographic on Facebook.)
SIGCSE 2016 Preview: Parsons Problems and Subgoal Labeling, and Improving Female Pass Rates on the AP CS exam
Our research group has two papers at this year’s SIGCSE Technical Symposium.
Subgoals help students solve Parsons Problems by Briana Morrison, Lauren Margulieux, Barbara Ericson, and Mark Guzdial. (Thursday 10:45-12, MCCC: L5-L6)
This is a continuation of our subgoal labeling work, which includes Lauren’s original work showing how subgoal labels improved learning, retention and transfer in learning App Inventor (see summary here), the 2015 ICER Chairs Paper Award-winning paper from Briana and Lauren showing that subgoals work for text languages (see this post for summary), and Briana’s recent dissertation proposal where she explores the cognitive load implications for learning programming (see this post for summary). This latest paper shows that subgoal labels improve success at Parson’s Problems, too. One of the fascinating results in this paper is that Parson’s Problems are more sensitive as a learning assessment than asking students to write programs.
Sisters Rise Up 4 CS: Helping Female Students Pass the Advanced Placement Computer Science A Exam by Barbara Ericson, Miranda Parker, and Shelly Engelman. (Friday 10:45-12, MCCC: L2-L3)
Barb has been developing Project Rise Up 4 CS to support African-American students in succeeding at the AP CS exam (see post here from RESPECT and this post here from last year’s SIGCSE). Sisters Rise Up 4 CS is a similar project targeting female students. These are populations that have lower pass rates than white or Asian males. These are examples of supporting equality and not equity. This paper introduces Sisters Rise Up 4 CS and contrasts it with Project Rise Up 4 CS. Barb has resources to support people who want to try these interventions, including a how-to ebook at http://ice-web.cc.gatech.edu/ce21/SRU4CS/index.html and an ebook for students to support preparation for the AP CS A.
Dan is one of the best computer science teachers I know, and I strongly agree with the goals he describes below. I’m not sure how much intro courses can do to recruit more diverse students. At Georgia Tech, Media Computation has been over 50% female since we started in 2003, but that’s because of what majors are required to take it and the gender distribution in those majors. I know that Harvey Mudd, Stanford, and Berkeley have grown their percentage of females, but their undergraduates get to choose their majors while on-campus. At schools like Georgia Tech, where students have to choose their major on the application form, the decision is made off-campus.
One clear thing we can do in undergraduate courses is retain more diverse students. In our BS in CS, we graduated 16% female BS in CS students in Spring 2015, which is pretty good. Taulbee Survey says that the national average is only 14.1% (see report here). But our enrollment in CS is 25% female. We lose a LOT of women who decide to try CS. I’ve talked about some of the reasons in past blog posts (see post here about bad teaching practices and here about my daughter’s experience in CS at Georgia Tech).
Dan Garcia says there’s another important issue: Once courses are created, educators must make sure they’re reaching a diverse audience. Women and minorities are grossly under-represented, not just in tech fields, but also in computer science classes.Teachers should shake the trees and reach out to more kinds of students, not just the student who’s doing well in math. And, he says, connect computer science to bigger, more controversial topics, Garcia says, because coding and data are connected to issues of power. With the persistent digital divide, he says, educators must ask, “What does that mean for equity? What does that mean for fairness? Privacy issues? Hopefully the curriculum brings equity as part of it,” he says.
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.