Posts tagged ‘BPC’

The gender imbalance in AI is greater than in CS overall, and that’s a big problem

My colleague, Rada Mihalcea, sent me a copy of a new (April 2019) report from the AI Now Institute on Discriminating Systems: Gender, Race, and Power in AI (see link here) which describes the diversity crisis in AI:

There is a diversity crisis in the AI sector across gender and race. Recent studies found only 18% of authors at leading AI conferences are women, and more than 80% of AI professors are men. This disparity is extreme in the AI industry: women comprise only 15% of AI research staff at Facebook and 10% at Google. There is no public data on trans workers or other gender minorities. For black workers, the picture is even worse. For example, only 2.5% of Google’s workforce is black, while Facebook and Microsoft are each at 4%. Given decades of concern and investment to redress this imbalance, the current state of the field is alarming.

Without a doubt, those percentages do not match the distribution of gender and ethnicity in the population at large. But we already know that participation in CS does not match the population. How do the AI distributions match the distribution of gender and ethnicity among CS researchers?

A sample to compare to is the latest graduates with CS PhDs. Take a look at the 2018 Taulbee Survey from the CRA (see link here).  19.3% of CS PhD’s went to women. That’s terrible gender diversity when compared to the population, and AI  (at 10%, 15%, or 18%) is doing worse. Only 1.4% of new CS PhD’s were Black. From an ethnicity perspective, Google, Facebook, and Microsoft are doing surprisingly well.

The AI Now Institute report is concerned about intersectionality. “The overwhelming focus on ‘women in tech’ is too narrow and likely to privilege white women over others.” I heard this concern at the recent NCWIT Summit (see link here).  The issues of women are not identical across ethnicities. The other direction of intersectionality is also a concern. My student, Amber Solomon, has published on how interventions for Black students in CS often focus on Black males: Not Just Black and Not Just a Woman: Black Women Belonging in Computing (see link here).

I had not seen previously a report on diversity in just one part of CS, and I’m glad to see it. AI (and particularly the sub-field of machine learning) is growing in importance. We know that having more diversity in the design team makes it more likely that a broader range of issues are considered in the design process. We also know that biased AI technologies are already being developed and deployed (see the Algorithmic Justice League). A new Brookings Institute Report identifies many of the biases and suggests ways of avoiding them (see report here). AI is one of the sub-fields of computer science where developing greater diversity is particularly important.

 

June 3, 2019 at 7:00 am 1 comment

The systemic factors that limit Black participation in the Tech sector

I learned a lot from Kamau Bobb’s recent Atlantic article, “The Black Struggle for Technology Jobs.”  In it, he details the systemic factors that limit Black participation in the Tech sector.  He uses the possibility of Amazon’s HQ2 going to Atlanta as a framing.

After Atlanta made the shortlist of cities vying for Amazon’s second global headquarters, HQ2, it submitted a multibillion-dollar investment to try to seal the deal. (Other cities’ proposals were even bigger.) At stake is nothing less than the city’s economic future: HQ2 promises more than 50,000 high-tech jobs with an average salary of more than $100,000. With the tech industry looking like the future of all industry, Atlanta landing Amazon’s HQ2 would be a dream come true.

But a dream for whom? Highly educated people, particularly those with technical skills, are the ones who are really eligible for these prized jobs. People without that kind of education risk becoming even more marginalized in an increasingly tech-driven economy. In Atlanta, one of the most segregated cities in the United States, history has already largely determined who gets to benefit from the potential of Amazon.

In 2016, there was only one census tract in Atlanta where the population was more than 65 percent black, and where more than half the population age 25 or older had a bachelor’s degree or higher. In 2000, there were 10. Here, many black and brown students, and poor students of all backgrounds, receive a substandard education that does not prepare them for entry to the select colleges and universities tech companies draw their workforces from. Consequently, with or without Amazon’s investment, the city’s black population likely won’t land stem jobs unless they can gain access to the rigorous educational paths required to compete for them. In Atlanta and the many other American cities still scarred by decades of racist education policies, the future of work is still largely defined by a past from which their residents of color can’t seem to break free.

I’m biased in favor of this article because one of the students he interviews in this piece is my daughter, Katie. I learned from Katie’s comments, too.  I knew that the public high school where we sent all three of our children was unusually diverse, yet it was a family conversation how the gifted/accelerated classes were almost all white and Asian.  Because of what Barb and I do, we kept an eye on the AP CS class at that high school, and were surprised every year at how few Blacks ever entered the class, despite the significant percentage of Black students in the school. I’m glad that, years later, Katie still thinks about those issues and why so few Black students made it into her AP classes.

 

December 3, 2018 at 8:00 am 2 comments

African-Americans don’t want to play baseball, like women don’t want to code: Both claims are false

I listened to few of my podcasts this summer with our move, so I’m catching up on them now. I just heard one that gave me a whole new insight into Stuart Reges’s essay Why Women Don’t Code.

In Here’s Why You’re Not an Elite Athlete (see transcript here), they consider why:

In 1981, there was 18.7 percent black, African-American players in the major leagues. As of 2018, 7.8 percent.

Why was there such a precipitous drop? David Canton, a professor at Connecticut College, offers three explanations:

I look at these factors: deindustrialisation, mass incarceration, and suburbanization. With deindustrialisation — lack of tax base — we know there’s no funds to what? Construct and maintain ball fields. You see the rapid decline of the physical space in the Bronx, in Chicago, in these other urban areas, which leads to what? Lack of participation.

Suburbanization drew the tax base out of the cities. With fewer taxes in the cities, there were fewer funds to support ball fields and maintain baseball leagues.

The incarceration rates for African-American men is larger than for other demographic groups (see NCAA stats). Canton explains why that impacts participation in baseball:

I can imagine in 1980, if you were 18-year-old black man in L.A., Chicago, New York, all of a sudden, you’re getting locked up for nonviolent offenses. I’m going to assume that you played baseball. I’m arguing that those men — if you did a survey, and go to prison today, federal and state, I bet you a nice percentage of these guys played baseball. Now some were not old enough to have children. And the ones that did weren’t there to teach their son to play baseball, to volunteer in Little League because they were in jail for nonviolent offenses.

There is now a program called RBI, for Reviving Baseball in Inner cities, funded by Major League Baseball, to try to increase the participation in baseball by African-Americans and other under-served youth. There are RBI Academies in Los Angeles, New York, Kansas City, and St. Louis.

So, why are there so few African-Americans in baseball? One might assume that they just choose not to play baseball, just as how Stuart Reges decided that the lack of women in the Tech industry means that they don’t want to code.

I find the parallels between the two stories striking:

  • Baseball used to be 18.7% African-American.
  • Computer Science used to be 40% female.
  • There have been and are great African-American baseball players. (In 1981, 22% of the All-Star game rosters, were African-American, according to Forbes.) There is no inherent reason why African-Americans can’t play baseball.
  • There have been and are great female computer scientists. There is no inherent reason why women can’t code.
  • Today, baseball is only 7.8% African-American.
  • Today, computer science is only about 17% female (in undergraduate enrollment).
  • There are structural and systemic reasons why there are fewer African-Americans in baseball, such as deindustrialization, suburbanization, and a disproportionate impact of incarceration on the African-American community. (Some commentators say that the whiteness of baseball runs much deeper.)
  • There are structural and systemic reasons where there are fewer women in computer science. There are many others, like the thoughtful posts from Jen Mankoff and Ann Karlin, and the heartfelt personal blog post by Kasey Champion, who have listed these far better than I could.
  • Major League Baseball recognizes the problem and has created RBI to address it.
  • The Tech industry, NSF (e.g., through creation of NCWIT), and others recognize the problem and are working to address it. Damore and Reges are among those in Tech who are arguing that we shouldn’t be trying to address this problem, that there are differences between men and women, and that we’re unlikely to ever reach gender equity in Tech.

Maybe there are people pushing back on the RBI program in baseball, who believe that African-Americans have chosen not to play baseball. I haven’t seen or heard that.

If we accept that we ought to do something to get more African-Americans past the systemic barriers into baseball, isn’t it just as evident that we should do something to get more females into Computing?

November 26, 2018 at 8:00 am 1 comment

The Backstory on Barbie the Robotics Engineer: What might that change?

Professor Casey Fiesler has a deep relationship with Barbie, that started with a feminist remix of a book.  I blogged about the remix and Casey’s comments on Barbie the Game Designer in this post. Now, Casey has helped develop a new book “Code Camp with Barbie and Friends” and she wrote the introduction. She tells the backstory in this Medium blog post.

In her essay, Casey considers her relationship with Barbie growing up:

I’ve also thought a lot about my own journey through computing, and how I might have been influenced by greater representation of women in tech. I had a lot of Barbies when I was a kid. For me, dolls were a storytelling vehicle, and I constructed elaborate soap operas in which their roles changed constantly. Most of my Barbies dated MC Hammer because my best friend was a boy who wasn’t allowed to have “girl” dolls, and MC was way more interesting than Ken. I also wasn’t too concerned about what the box told me a Barbie was supposed to be; otherwise I’d have had to create stories about models and ballerinas and the occasional zookeeper or nurse. My creativity was never particularly constrained, but I can’t help but think that even just a nudge — a reminder that Barbie could be a computer programmer instead of a ballerina — would have influenced my own storytelling.

I’ve been thinking about how Barbie coding might influence girls’ future interest in Tech careers.  I doubt that Barbie is a “role model” for many girls. Probably few girls want to grow up to be “like Barbie.” What a coding Barbie might do is to change the notion of “what’s acceptable” for girls.

In models of how students make choices in academia (e.g., Eccles’ expectancy-value theory) and how students get started in a field (e.g., Alexander’s Model of Domain Learning), the social context of the decision matters a lot. Students ask themselves “Do I want to do this activity and why?” and use social pressure and acceptance to decide what’s an appropriate class to take.  If there are no visible girls coding, then there is no social pressure. There are no messages that programming is an acceptable behavior.  A coding Barbie starts to change the answer to the question, “Can someone like me do this?”

September 24, 2018 at 7:00 am 3 comments

Why Don’t Women Want to Code? Better question: Why don’t women choose CS more often?

Jen Mankoff (U. Washington faculty member, and Georgia Tech alumna) has written a thoughtful piece in response to the Stuart Reges blog post (which I talked about here), where she tells her own stories and reframes the question.

Foremost, I think this is the wrong question to be asking. As my colleague Anna Karlin argues, women and everyone else should code. In many careers that women choose, they will code. And very little of my time as an academic is spent actually coding, since I also write, mentor, teach, etc. In my opinion, a more relevant question is, “Why don’t women choose computer science more often?”

My answer is not to presume prejudice, by women (against computer science) or by computer scientists (against women). I would argue instead that the structural inequalities faced by women are dangerous to women’s choice precisely because they are subtle and pervasive, and that they exist throughout a woman’s entire computer science career. Their insidious nature makes them hard to detect and correct.

Source: Why Don’t Women Want to Code? Ask Them! – Jennifer Mankoff – Medium

September 21, 2018 at 7:00 am 2 comments

US National Science Foundation increases emphasis on broadening participation in computing

The computing directorate at the US National Science Foundation (CISE) has increased its emphasis on broadening participation in computing (BPC).  (See quote below and FAQ here.) They had a pilot program where large research grants were required to include a plan to increase the participation of groups or populations underrepresented or under-served in computing. They are now expanding the program to include medium and large scale grants. The idea is to get more computing researchers nationwide focusing on BPC goals.

CISE recognizes that BPC requires an array of long-term, sustained efforts, and will require the participation of the entire community. Efforts to broaden participation must be action-oriented and must take advantage of multiple approaches to eliminate or overcome barriers. BPC depends on many factors, and involves changing culture throughout academia—within departments, classrooms, and research groups. This change begins with enhanced awareness of barriers to participation as well as remedies throughout the CISE community, including among principal investigators (PIs), students, and reviewers. BPC may therefore involve a wide range of activities, examples of which include participating in professional development opportunities aimed at providing more inclusive environments, joining various existing and future collective impact programs to helping develop and implement departmental BPC plans that build awareness, inclusion, and engagement, and conducting outreach to underrepresented groups at all levels (K-12, undergraduate, graduate, and postgraduate).

In 2017, CISE commenced a pilot effort to increase the community’s involvement in BPC, by requiring BPC plans to be included in proposals for certain large awards [notably proposals to the Expeditions in Computing program, plus Frontier proposals to the Cyber-Physical Systems and Secure and Trustworthy Cyberspace (SaTC) programs]. By expanding the pilot to require that Medium and Large projects in certain CISE programs [the core programs of the CISE Divisions of Computing and Communication Foundations (CCF), Computer and Network Systems (CNS), and Information and Intelligent Systems (IIS), plus the SaTC program] have approved plans in place at award time in 2019, CISE hopes to accomplish several things:

  • Continue to signal the importance of and commitment to BPC;
  • Stimulate the CISE community to take action; and
  • Educate the CISE community about the many ways in which members of the community can contribute to BPC.

The long-term goal of this pilot is for all segments of the population to have clear paths and opportunities to contribute to computing and closely related disciplines.

Read more at https://www.nsf.gov/pubs/2018/nsf18101/nsf18101.jsp

August 31, 2018 at 7:00 am 1 comment

In last five years, little progress in increasing the fraction of American CS BS degree recipients who are African Americans

Keith Bowman published a series of blog posts this summer on African American undergraduate degrees in engineering.  In July, he wrote one on computer science – linked here. It’s interesting, careful, and depressing. I’m quoting the conclusion below, but I highly recommend clicking on the link and seeing the whole report. What’s most interesting is the greater context — Bowman is comparing across different engineering programs, so he has a strong and data-driven sense of what’s average and what’s below average.

There has been little progress in increasing the fraction of American CS BS degree recipients who are African Americans. Progress will likely only take place through a concerted effort by industry, professional societies, academia and government to foster change, including stronger efforts in graduate degrees. CS undergraduate programs fare poorly compared to many other engineering disciplines in the context of gender diversity and slightly worse than engineering overall in the fraction of African Americans earning undergraduate degrees. Many of the largest CS programs in the US are strikingly behind the national averages for CS BS degrees earned by African Americans.

 

August 24, 2018 at 7:00 am 5 comments

High school students learning programming do better with block-based languages, and the impact is greatest for female and minority students

I learned about this study months ago, and I was so glad to see it published in ICLS 2018 this last summer.  The paper is “Blocks or Text? How Programming Language Modality Makes a Difference in Assessing Underrepresented Populations” by David Weintrop, Heather Killen, and Baker Franke.  Here’s the abstract:

Broadening participation in computing is a major goal in contemporary computer science education. The emergence of visual, block-based programming environments such as Scratch and Alice have created a new pathway into computing, bringing creativity and playfulness into introductory computing contexts. Building on these successes, national curricular efforts in the United States are starting to incorporate block-based programming into instructional materials alongside, or in place of, conventional text-based programming. To understand if this decision is helping learners from historically underrepresented populations succeed in computing classes, this paper presents an analysis of over 5,000 students answering questions presented in both block-based and text-based modalities. A comparative analysis shows that while all students perform better when questions are presented in the block-based form, female students and students from historically underrepresented minorities saw the largest improvements. This finding suggests the choice of representation can positively affect groups historically marginalized in computing.

Here’s the key idea as I see it. They studied over 5,000 high school students learning programming. They compared students use block-based and text-based programming questions.  Everyone does better with blocks, but the difference is largest for female students and those from under-represented groups.

Here’s the key graph from the paper:

Weintrop-blocks-text-icls18a-sub1402-i7_pdf__page_5_of_8_

So, why wouldn’t we start teaching programming with blocks?  There is an issue that students might think that it’s a “toy” and not authentic — Betsy DiSalvo saw that with her Glitch students. But a study with 5K students suggests that the advantages of blocks swamp the issues of inauthenticity.

The International Conference on the Learning Sciences (ICLS) 2018 Proceedings are available here.

August 20, 2018 at 7:00 am 15 comments

Visiting NTNU in Trondheim Norway June 3-23

Barbara and I are just back from a three week trip to NTNU in Trondheim, Norway. Katie Cunningham came with us (here’s a blog post about some of her work). Three weeks is enough time to come up with a dozen ideas for blog posts, but I don’t have the cycles for that. So let me just give you the high-level view, with pictures and links to learn more.

We went at the beginning of June because Barb and I (and the University of Michigan) are part of the IPIT network (International Partnerships for Excellent Education and Research in Information Technology) that had its kick-off meeting June 3-5. The partnership is about software engineering and computing education research, with a focus student and faculty exchange and meetings at each others’ institutions: NTNU, U. Michigan, Tsinghua University, and Nanjing University. I learned a lot about software engineering that I didn’t know before, especially about DevOps.

If you ever get the chance to go to a meeting organized by Letizia Jaccheri of NTNU, GO! She was the organizer for IPIT, co-chair of IDC 2018, and our overall host for our three weeks there. She has a wonderful sense for blending productivity with fun. During the IDC 2018 poster session, she brought in high school students dressed as storybook characters, just to wander around and “bring in a bit of whimsy.” For a bigger example, she wanted IPIT to connect with the NTNU campus at Ålesund, which just happens to be near the Geiranger fjord, one of the most beautiful in Norway. So, she flew the whole meeting to Ålesund from Trondheim! We took a large cruise-ship like boat with meeting rooms down the fjord. We got in some 5-6 hours of meetings, while also seeing amazing waterfalls and other views, and then visited the Ålesund campus the next day before flying home. We got work done and WOW!

For the next week and a half, we got to know the computing education research folks at NTNU. We were joined at the end of the first week by Elisa Rubegni from the University of Lincoln, and Roberto Martinez-Maldonado came by a couple days later. Barb, Elisa, and I held a workshop on the first Monday after IPIT. A couple days later, we had a half-day meeting with Michalis Giannakos’s group and Roberto, then Elisa led us all in a half-day design exercise (pictured below — Elisa, Sofia, Javi, and Katie). In between, we had individual meetings. I think I met with every one of the PhD students there working in computing education research. (And, in our non-meeting time, Barb and I were writing NSF proposals!)

Michalis’s group is doing some fascinating work. Let me tell you about some of the projects that most intrigued me.

  • Sofia (with Kshitij and Ilias) is lead on a project where they track what kids using Scratch are looking at, both on and off screen. It’s part of this cool project where kids program these beautiful artist-created robots with Scratch. It’s a pretty crazy looking experimental setup, with fiducial markers on notebooks and robots and screens.
  • Kshitij is trying to measure EEG and gaze in order to determine cognitive load in a user interface. Almost all cognitive load measures are based on self-report (including ours). They’re trying to measure cognitive load physiologically, and correlate it with self-report.
  • Katerina and Kshitij is using eye-tracking to measure how undergrads use tools like Eclipse. What I found most interesting was what they did not observe. I noticed in their data that they had no data on using the debugger. They explained that in 40 students, only five people even looked at the debugger. Nobody used data or control flow visualizations at all. I’m fascinated by this — what does it take to get students to actually look at the debuggers and visualizers that were designed to help them learn?
  • Roberto is doing this amazing work with learning analytics in physical spaces, where nurses are working on robot patients. Totally serious — they can gather all kinds of data about where people are standing, how they interact, and when they interact. For tasks like nursing, this is super important to understand what students are learning.

Then came FabLearn with an amazing keynote by Leah Buechley on art, craft, and computation. I have a long list of things to look up after her talk, including Desmos, computer controlled cutting machines (which I had never heard of before) which are way cheaper than 3-D printers but still allow you to do computational craft, and http://blog.recursiveprocess.com/ which is all about learning coding and mathematics. She made an argument that I find fascinating — that art is what helps diverse students reflect their identity and culture in their school, and that’s why students who get art classes (controlling for SES) are more likely to succeed in school and go onto post-secondary schooling. Can computing make it easier to bring art back into school? Can computing then play a role in engaging children with school again?

The next reason we were at NTNU was to attend the EXCITED Centre advisory board meeting. Barb and I were there for the launch of EXCITED in January 2017. It’s a very ambitious project, starting from students making informed decisions to go into CS/IT, helping students develop identities in CS, learning through construction, increasing diversity in CS, and moving into careers. We got to hang out with Arnold Pears, Mats Daniels, and Aletta Nylén of UpCERG (Upssala Computing Education Research Group), the world’s largest CER group.

Finally, for the last four days, we attended the Interaction, Design and Children Conference, IDC 2018. I wrote my Blog@CACM post for this month about my experiences there. I saw a lot there that’s relevant to people who read this blog. My favorite paper there tested the theory of concreteness fading on elementary school students learning computing concepts. Here’s a picture of a slide (not in the paper) that summarizes the groups in the experiment.

I’ll end with my favorite moment in IDC 2018, not in the Blog@CACM post. We met Letizia’s post-doc, Javier “Javi” Gomez at the end of our first week in Trondheim. Summer weather in Trondheim is pretty darn close to winter in Atlanta. One day, we woke up to 44F and rain. But we lucked out — the weekends were beautiful. On our first Saturday, Letizia invited us all to a festival near her home, and we met Javi and Elisa. That evening (but still bright sunlight), Javi, Elisa, Barb, and I took a wonderful kayaking trip down the Nidelva river. So it was a special treat to be at IDC 2018 to see Javi get TWO

awards for his contributions, one for his demo and an honorable mention for his note. The note was co-authored by Letizia, and was her first paper award (as she talks about in the lovely linked blog post). It was wonderful to be able to celebrate the success of our new friends.

On the way back, Barb and I stopped in London to spend a couple days with Alan Kay and his wife, Bonnie MacBird. If I could come up with a dozen blog post ideas from 3 weeks, it’s probably like two dozen per day with Alan and Bonnie, and we had two days with them. Visiting a science museum with an exhibit on early computers (including an Alto!) is absolutely amazing when you’re with Alan. But those blog posts will have to wait until after my blog hiatus.

June 28, 2018 at 7:00 am 2 comments

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 4 comments

ECEP 2018: Measuring and Making Progress on Broadening Participation in Computing

The 2018 Annual Meeting of the Expanding Computing Education Pathways (ECEP) Alliance was at Georgia Tech January 26-27. ECEP is an NSF-funded alliance to broaden participation in computing. We had about 90 participants, state leaders from 16 states and Puerto Rico. Attendees were from a range of positions, from state departments of education, state boards of education, STEM centers, non-profits, Governor’s offices, University professors, and CS teachers from elementary or high school. The focus at this meeting was to define what it means to broaden participation in computing (BPC) education for each state. The state teams worked at defining what data variables they needed in order to inform their BPC goals, and how they would know (by looking at those data) if they were making progress towards those goals.  You can see the play-by-play with pictures via Twitter hashtag #ECEP2017.

I learned so much at this event. I’m still processing all of it, but here are some of the things that are standing out to me right now.

Caitlin Dooley from Georgia Department of Education gave a terrific talk about the challenges in Georgia.  She made the argument that CS is the equity issue of our age.  She said that the challenge of getting CS teachers into poorer (low-SES) and rural districts is that teachers are leaving when they have the skillsets. The challenge is to have good school leaders to retain teachers.

Anne DeMallie from Massachusetts gave a compelling talk about how they’re integrating CS across the curriculum, especially in elementary school. Massachusetts and New Jersey are two states that integrated their CS and Digital Literacy standards, trying to make it easier for schools to integrate CS education. I liked the framework she offered on how to think about integrating CS into other subjects: exist, enhance, and extend.

I was impressed by the states who are setting concrete, measurable goals. Alabama has set a goal of every high school student having access to CS education by 2022. South Carolina plans to provide access to CS education in every middle and high school in five years. Maryland has a detailed 15 year plan that gets every student access to high-quality CS education with certified high school teachers. (Seen below, presented by Megean Garvin.)

Kamau Bobb of Constellations gave our keynote (as a “fireside chat” with Debra Richardson). His talk was exciting and challenging.  He pointed out that high school CS isn’t going to get kids into University. Pushing CS instead of math and science isn’t helping students get admission to higher education.  Schools aren’t held accountable for CS — they’re being held accountable for math, science, and language arts learning. CS has to play a role in meeting student and school needs.

Kamau pointed out that “Segregation is an immutable truth.”  One of the stories he told was to about textual literacy.  During Reconstruction (starting 1865), leaders realized the critical need for all African-Americans to learn to read.  The Georgia Literacy Project to address the dramatic literacy gap was just started in 2010 — 145 years later.  How long will it take us to achieve equitable access to computing education?

Most of the time was spent in working meetings — state teams sitting down with data reports, developing plans for broadening participation in CS, and grounding the plans in what data they have and what trends they expect to see in those data. The challenges of gathering data on the ground are huge.  I was sitting with one state where a CS teacher on the team pointed out that she had 85 students this year. The Department of Education person from that state did a search, and found that none of those students showed up in their database.  Other states pointed out how hard it is to compare data across states.  We use AP CS data for these kinds of comparisons, but in some states (like Arkansas), all AP exams are paid for by the state. That means that more kids are taking the exam, which means that the pass rates have a different context.

The amount of support for CS Education from each state varies dramatically. Many states have no one in the Department of Education who is informed about CS. Here in Georgia, we have one full-time CS coordinator, which is terrific. In Arkansas, they have nine full-time CS specialists to help teachers.

It was energizing to be with so many passionate leaders who are working to improve computing education in their state.  It’s also amazing to see how much work there is to go to reach everyone with high-quality computing education.

This was the last ECEP meeting organized by this group of NSF Principal Investigators. Rick Adrion, Renee Fall, Barbara Ericson, and I are done when the existing ECEP grant runs out at the end of September.  We’ve worked with a new team of PI’s to help them build a proposal for ECEP 2.  The amazing Sarah Dunton, the manager of our state and territory alliance, will continue in ECEP 2. The PIs for ECEP 2 are Carol Fletcher, Anne Leftwich, Debra Richardson, Maureen Biggers, and Leigh Ann DeLyser.  We’re hoping that they get funded and continue to help states make progress on implementing and broadening computing education.

January 29, 2018 at 7:00 am 3 comments

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

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