Posts tagged ‘NCWIT’

Ever so slowly, diversity in computing jobs is improving: It’ll be equitable in a century

A great but sobering blog post from Code.org. Yes, computing is becoming more diverse, but at a disappointingly slow rate. Is it possible to go faster? Or is this just the pace at which we can change a field?

According to the Bureau of Labor Statistics, yes, but very slowly. We’ve analyzed the Current Population Survey data from the past few years to see how many people are employed in computing occupations, and the percentage of women, Black/African American, and Hispanic/Latino employees.

What did we find? There are about 5 million people employed in computing occupations, 24% of whom are women, and 15% of whom are Black/African American or Hispanic/Latino.

Since 2014, the trends in representation, although small, have been moving in the right direction — all three groups showed a tiny increase in representation. However, changes would need to accelerate significantly to reach meaningful societal balance in our lifetimes. If the current pace of increases continue, it would take over a century* until we saw balanced representation in computing careers.

Source: Is diversity in computing jobs improving? – Code.org – Medium

May 4, 2018 at 7:00 am 1 comment

What can the Uber Gender Pay Gap Study tell us about improving diversity in computing?

The gig economy offers the ultimate flexibility to set your own hours. That’s why economists thought it would help eliminate the gender pay gap. A new study, using data from over a million Uber drivers, finds the story isn’t so simple.

Source: What Can Uber Teach Us About the Gender Pay Gap? – Freakonomics

A fascinating Freakonomics podcast tells us about why women are paid less than men (by about 7%) on Uber.  They ruled out discrimination, after looking at a variety of sources.  They found that they could explain all of that 7% from three factors.

They found that even in a labor market where discrimination can be ruled out, women still earn 7 percent less than men — in this case, roughly 20 dollars an hour versus 21. The difference is due to three factors: time and location of driving; driver experience; and average speed.

The first factor is that women choose to be Uber drivers in different places and at different times than men.  Men are far more often to be drivers at 3 am on Saturday morning. The second factor is particularly interesting to me.  Men tend to stick around on Uber longer than women, so they learn how to work the system. The third factor is that men drive faster, so they get more rides per hour.

When someone from Uber was asked about how they might respond to these results, he focused on the second factor.

But for example, you could imagine that if we make our software easier to use and we can steepen up the learning curve, then if people learn more quickly on the system, then that portion of the gap could be resolved via some kind of intervention. But that’s just an example. And we’re not there yet with our depth of understanding, to just simply write off the gender gap as a preference.

Improving learning might help shrink the gender pay gap.  Obviously, I’m connecting this to computing education here.  What role could computing education play in reducing gaps between males and females in computing?  We have reason to believe that our inability to teach programming well led to the gender gap in computing.  Could we make things better if we could teach computing well?

Here are two thoughts exploring that question.

  1. We know (e.g., from Unlocking the Clubhouse) that men tend to sink more time into programming, which can give them a lead in undergraduate education (what Jane Margolis has called ‘preparatory privilege‘).  What if we could teach programming more efficiently?  Could we close that gap?  If we had a science of teaching programming, we could improve efficiency so that a few hours of focused effort in the classroom might lead to more effective learning of tens of hours of figuring out how to compile under Debian Linux.
  2. When I first started thinking about the “phonics of computing education” and our ebooks, I was inspired by work from Caroline Simard that suggested that helping female mid-level managers keep up their technical skills could help them to progress in the tech industry.  Female mid-level managers have less time to invest in technical learning, and at the mid-level, technical education still matters.  If you have a project that needs a new toolset, you’ll more likely give it to the manager who knows that toolset.  If we could teach female mid-level technical managers more effectively and efficiently, could they make it into the C-suite of tech companies?

Maybe better computing education could be an important part of improving diversity, along multiple paths.

March 5, 2018 at 7:00 am 6 comments

SIGCSE 2018 Preview: Black Women in CS, Rise Up 4 CS, Community College to University CS, and Gestures for Learning CS

While I’m not going to be at this year’s SIGCSE, we’re going to have a bunch of us there presenting cool stuff.

On Wednesday, Barb Ericson is going to this exciting workshop, CS Education Infrastructure for All: Interoperability for Tools and Data Analytics, organized by Cliff Shaffer, Peter Brusilovsky, Ken Koedinger, and Stephen Edwards. Barb is eager to talk about her adaptive Parsons Problems and our ebook work.

My PhD student, Amber Solomon, is presenting at RESPECT 2018 (see program here) on a paper with Dekita Moon, Amisha Roberts, and Juan Gilbert, Not Just Black and Not Just a Woman: Black Women Belonging in Computing. They talk about how expectations of being Black in CS and expectations as a woman in CS come into conflict for the authors.

On Thursday, Barb is presenting her paper (with Tom McKlin) Helping Underrepresented Students Succeed in AP CSA and Beyond, which are the amazing results from the alumni study from her Project Rise Up effort to help underrepresented students succeed at Advanced Placement CS A. When Barb was deciding on her dissertation topic, she considered making Rise Up her dissertation topic, or adaptive Parsons problems. She decided on the latter, so you might think about this paper as the dissertation final chapter if she had made Rise Up her dissertation focus. Project Rise Up grew from Barb’s interest in AP CS A and her careful, annual analysis of success rates in AP CS A for various demographics (here is her analysis for 2017). It had a strong impact (and was surprisingly inexpensive), as seen in the follow-on statistics and the quotes from the students now years after Rise Up. I recommend going to the talk — she has more than could fit into the paper.

On Friday, my PhD student, Katie Cunningham, is presenting with her colleagues from California State University Monterey Bay and Hartnell College, Upward Mobility for Underrepresented Students: A Model for a Cohort-Based Bachelor’s Degree in Computer Science.  The full author list is Sathya Narayanan, Katie, Sonia Arteaga, William J. Welch, Leslie Maxwell, Zechariah Chawinga, and Bude Su. They’re presenting the “CSin3” program which drew in students from traditionally underrepresented groups and helped them earn CS degrees with remarkable success: A three year graduation rate of 71%, compared to a 22% four-year graduation rate, as well as job offers from selective tech companies. The paper describes the features of the program that made it so successful, like its multi-faceted support outside the classroom, the partnership between a community college and a university, and keeping a cohort model. The paper has been recognized with a SIGCSE 2018 Best Paper Award in the Curricula, Programs, Degrees, and Position Papers track.

On Friday, my colleague Betsy DiSalvo is going to present at the NSF Showcase some of the great work that she and her student, Kayla des Portes, have been doing with Maker Oriented Learning for Undergraduate CS.

On Saturday, my EarSketch colleagues are presenting their paper: Authenticity and Personal Creativity: How EarSketch Affects Student Persistence with Tom McKlin, Brian Magerko, Taneisha Lee, Dana Wanzer, Doug Edwards, and Jason Freeman.

Also on Saturday, Amber with her undergraduate researchers, Vedant Pradeep and Sara Li, are presenting a poster which is also a data collection activity, so I hope that many of you will stop by. Their poster is The Role of Gestures in Learning Computer Science. They are interested in how gesture can help with CS learning and might be an important evaluation tool — students who understand their code, tend to gesture differently when describing their code than students who have less understanding. They want to show attendees what they’ve seen, but more importantly, they want feedback on the gestures they’ve observed “in the wild.” Have you seen these? Have you seen other gestures that might be interesting and useful to Amber and her team? What other kinds of gestures do you use when explaining CS concepts? Please come by and help inform them about the gestures you see when teaching and learning CS.

February 21, 2018 at 7:00 am 1 comment

Georgia Tech Launches Constellations Center Aimed at Equity in Computing

 

The Constellations Center was launched at a big event on December 11.  I was there, to hear Executive Director Charles Isbell host the night, which included a great conversation with Senior Director Kamau Bobb (formerly of NSF).

 

Constellations is going to play a significant role in keeping a focus on broadening participation in computing in Georgia, and to serve as a national leader in making sure that everyone gets access to computing education.

Georgia Tech’s College of Computing has launched the Constellations Center for Equity in Computing with the goal of democratizing computer science education. The mission of the new center is to ensure that all students—especially students of color, women, and others underserved in K-12 and post-secondary institutions—have access to quality computer science education, a fundamental life skill in the 21st century.

Constellations is dedicated to challenging and improving the national computer science (CS) educational ecosystem through the provision of curricular content, educational policy assessment, and development of strategic institutional partnerships. According to Senior Director Kamau Bobb, democratizing computing requires a “real reckoning with the race and class divisions of contemporary American life.”

See more here.

January 12, 2018 at 7:00 am 1 comment

How the Imagined “Rationality” of Engineering Is Hurting Diversity — and Engineering

Just a few weeks ago, Richard Thaler won the Nobel prize in Economics. Thaler is famous for showing that real human beings are not the wholly rational beings that Economic theory had previously assumed.  It’s timely to consider where else we assume rationality, and where that rational assumption may lead us into flawed decisions and undesirable outcomes.  The below article from Harvard Business Review considers how dangerous the Engineering “purity” argument is.

Just how common are the views on gender espoused in the memo that former Google engineer James Damore was recently fired for distributing on an internal company message board? The flap has women and men in tech — and elsewhere — wondering what their colleagues really think about diversity. Research we’ve conducted shows that while most people don’t share Damore’s views, male engineers are more likely to…

But our most interesting finding concerned engineering purity. “Merit is vastly more important than gender or race, and efforts to ‘balance’ gender and race diminish the overall quality of an organization by reducing collective merit of the personnel,” a male engineer commented in the survey. Note the undefended assumption that tapping the full talent pool of engineers rather than limiting hiring to a subgroup (white men) will decrease the quality of engineers hired. Damore’s memo echoes this view, decrying “hiring practices which can effectively lower the bar for ‘diversity’ candidates.”

Google and taxpayer money, Damore opines, “is spent to water only one side of the lawn.” Many male engineers in our survey agreed that women engineers are unfairly favored. “As regards gender bias, my workplace offers women more incentives and monetary support than it does to males,” commented one male engineer. Said another, women “will always be safe from a RIF [reduction in force]. As well as certain companies guaranteeing female engineers higher raises.”

Source: How the Imagined “Rationality” of Engineering Is Hurting Diversity — and Engineering

December 11, 2017 at 7:00 am 1 comment

Why Tech Leadership May Have a Bigger Race Than Gender Problem

The Wired article linked below suggests that race is an even bigger issue than gender in Tech industry leadership.  While Asians are over-represented in the Tech labor force, they are under-represented in Tech leadership, even more than women.  I was somewhat surprised that this article considers “Asians” so generally.  The most-often visited blog post I’ve written is the one that shows the differential success rates of different Asian populations in US educational attainment (see post here).

Gee says this study came about because an earlier report in 2015 that used EEOC data from companies like Google and LinkedIn ended up on the desk of Jenny Yang, the outgoing commissioner of the EEOC. Yang asked if the lower proportion of Asian executives was the result of discrimination and might be applicable for lawsuits, Gee says. He told her no. “We have never seen any overt discrimination or policies that create these disparities,” Gee explains. Rather, after conversations with 60 or 70 Asian executives, the authors say they noticed a pattern of cultural traits among some Asians that did not align with leadership expectations in Western corporate culture, such as risk-taking and being confrontational.

Gee gave the example of an executive who started the first Asian affinity group at Intel decades ago. He noticed that Chinese engineers were unhappy and not succeeding in Intel’s culture of “constructive conflict,” which involved heated debates during meetings.

“Some people call it unconscious bias. For Asians, it’s actually a very conscious bias,” says Gee. Studies show that assumptions that Asians are good at math, science, and technology make it easier for them to get in the door, but the same bias is reversed when it comes to leadership roles, he says.

Source: Why Tech Leadership May Have a Bigger Race Than Gender Problem | WIRED

October 23, 2017 at 7:00 am 1 comment

Study says multiple factors work together to drive women away from STEM

I wrote recently in a blog post that we don’t know enough why women aren’t going into computing, and I wrote in another blog post that CRA is finding that we lose women over the years of an undergraduate degree in CS.  Here’s an interesting study offering explanations for why we are not getting and keeping women:

The study analyzed a large, private university on the East Coast, using data from 2009-16, broken down semester-by-semester to track students’ changes in grades and majors in as close to real time as possible. While other studies have suggested that women came out of high school less prepared, or that increasing female STEM faculty could help provide women mentors, the Georgetown study didn’t support those findings.

“Women faculty don’t seem to attract more women into a field, and that was sort of sad news for us,” Kugler said. “We were hoping we could make more of a difference.”

One of the reasons women might feel undue pressure in STEM fields might actually be because of how recruiting and mentoring is framed. Many times, those efforts actually end up reinforcing the idea that STEM is for men.“Society keeps telling us that STEM fields are masculine fields, that we need to increase the participation of women in STEM fields, but that kind of sends a signal that it’s not a field for women, and it kind of works against keeping women in these fields,” Kugler said.

And while many STEM majors are male-dominated, the framing of recruitment and mentorship efforts can sometimes paint inaccurate pictures for STEM fields that aren’t male-dominated, and contribute to an inaccurate picture for STEM as a whole, the paper says:

While men may not have a natural ability advantage in STEM fields, the numerous government and other policy initiatives designed to get women interested in STEM fields may have the unintended effect of signaling to women an inherent lack of fit.

While computer science, biophysics and physics tend to be male-dominated, Kugler said, neurobiology, environmental biology and biology of global health tend to be female-dominated.

Source: Study says multiple factors work together to drive women away from STEM

October 13, 2017 at 7:00 am 1 comment

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