Posts tagged ‘computing for everyone’

The state of women in computer science: An investigative report, featuring Barbara Ericson

The new TechRepublic report on women in computing is short but touches on a lot of important themes. Barb Ericson figures prominently in the report.

At Georgia Tech, every student is required to take one of three computer science intro courses: One for engineering majors, one for computer science majors, and one for all other students.

In the past, computer science was not taught in a very interesting way, Ericson said. And getting professors to change their habits after so much time proved difficult, she added.

Further, “a lot of instructors believe in the ‘geek gene’—that you’re born to do it or you’re not, and they often think women are not,” Ericson said. “Women can face an uphill climb from some of their professors or friends or family who are like, ‘Wait, what? Why are you doing this?'”

Intro courses should be interesting, creative, and social, and offer plenty of help, especially for women who tend to come in with less experience and less confidence, Ericson said.

Source: The state of women in computer science: An investigative report – TechRepublic

October 11, 2017 at 7:00 am Leave a comment

Unpacking models of what the $USD1.3B might achieve in Computing Education: We need long-term vision and will

I wrote my Blog@CACM post for September on the massive investments in CS Education announced last week (see post here): $200M/year from the US Department of Education announced by the White House on Monday, then $300M over five years from the Tech industry announced on Tuesday. I have read analyses saying that the money isn’t really promised or isn’t new (see concerns in this post), and others are shunning the initiative because of White House policies (see link here). I took the promises at face value. My post starts congratulating Hadi Partovi and Cameron Wilson of Code.org and Ivanka Trump who were behind these initiatives, then I offered two back-of-the-envelope models of what $1.3B in five years could do:

  • I extrapolated the New York City model (of a significant computing education experience to every child in every school within grade bands) to the whole of the US, which would likely take more than a magnitude more funding.
  • The funding is enough to pay for a CS teacher in every school, but I argued that it wouldn’t really work. We face a shortage of STEM teachers, and those few are the teachers that we can most likely recruit to CS. CS teacher attrition is so high that we couldn’t keep up with the losses, since we have so few mechanisms of pre-service CS teacher preparation.

I received many responses, queries, and criticisms of that blog post (from email, Facebook, and Twitter).  I am explaining and unpacking the CACM blog post here. I am not going to delete or change the CACM blog post. My mentor, Janet Kolodner, told me once not to dwell on any paper, trying to make it a masterpiece before publishing it. Rather, she suggested that we should just keep publishing. Explore lots of ideas in lots of papers, and publish as a way of thinking with a community. It’s okay to publish something you thought was right, and later find that it’s wrong — it documents the explored trails.

What I learned about the effort in NYC

I said that NYC was aiming to provide a quality computing learning experience for every student in every grade in every school, as I learned last October (and blogged about it here). I learned that the goal is now mandating a computing learning experience in every grade band, so not every year. It’s still a markedly different model than one teacher per school, and doesn’t change the costs considerably.

I learned that (as one might expect) that the effort in NYC is in both the NYC Department of Education and in CSNYC. It’s great that there are many people in the NY DoEd working on CS education! I was told on Twitter that some of what I attributed to CSNYC is actually in NY Department of Education. I don’t know what I mis-attributed, but I’m sure that it’s because I get confounded over “CSNYC” representing “the effort to provide CS education across NYC” and “the organization that exists to provide CS education across NYC.” I don’t understand the split between NYC DoEd and the CSNYC organization, and I’m not going to guess here. I am sure that it’s important for the people involved, but it’s not so important for the model and national analysis.

Explaining my Estimates in Contrast to Code.org’s

Code.org has made their model of the one-time cost of expanding access to K-12 computer science (CS) available at this Google doc. According to their model, it’s clear that the $1.3B is enough to make CS education available in every elementary and secondary school. They have more empirical data than anyone else on putting CS in whole districts, and their data suggest that costs are decreasing as they gain more efficiencies of scale.

Hadi challenged several points in my blog post on Facebook. I won’t replicate all of our exchange, and only include three points here:

  • I argue that we will probably have to pay future CS teachers more in the future, at least as teacher stipends. That prediction is based on trends I see in the states I work with and economics. States are facing teacher shortages, especially in STEM. Aman Yadav shared an article (see link here) that students studying to be teachers fell by 40% from the 2010-2011 academic year to the 2014-2015 academic year. If the supply of teachers is growing more slowly than the rate at which we’re trying to grow CS, we will have to provide incentives to make CS more attractive. Lijun Ni’s dissertation explored the barriers for teachers to become CS teachers (e.g., it’s a lot easier and more pleasant to stay a math teacher). Costs are likely to grow as the labor shortage increases.
  • Some of my costs are too high, e.g., I estimated the cost to develop a high school CS teacher as $10K, where NSF’s studies found it was closer to $8.6K. I used a ballpark 50% of high school CS teacher development for the costs of elementary school CS teacher development.  Since it’s clear that there is enough to prepare one CS teacher per school, I think my numbers are close enough.
  • I believe that extrapolating the NYC model across the country would be even more expensive than it is in NYC. Travel costs in NYC are much less than in rural America. While NYC is very diverse, the rest of the United States is just as diverse. I got to see Ann Leftwich at Indiana University on Saturday. She told me that some of the schools she works with resist teaching science at all! It’s really hard to convince them to teach CS. I expect that there is a similar lack of will to teach CS across the US.

Not all of my estimates are research-based. We don’t have research on everything. Changing all US schools happens so rarely that we do not have good models of how it works. I don’t think that the empirical data of what we have done before in CS Ed is necessarily predictive of what comes next, since most of our experience with CS Ed at-scale is in urban and suburban settings. Getting everywhere is harder. I have observed about “Georgia Computes!” — 1/3 of the high schools in GA got someone that Barbara trained in CS, and that’s likely the easiest 1/3. The next 2/3 will be harder and more expensive.

What I Missed Entirely

As Hadi correctly called me on, the biggest cost factor I missed is the development of curriculum. Back in July, I blogged about Larry Cuban’s analysis that suggested that we need to re-think how we are developing and disseminating CS curriculum in the United States (see link here). We have to develop a lot more curriculum in collaboration with schools, districts, and states nationwide. The US will never adopt a single curriculum nationwide for any subject — it’s not how our system was developed, and it’s why Common Core did not reach all 50 states. The US education system is always about tailoring, adapting, and working with local values and politics. Curriculum is always political.

Mike Zamansky just posted a blog post critiquing some of the curriculum he’s seeing in NYC (see post here). I don’t agree with Mike’s post, but I wholeheartedly agree with his posting. We should argue about curriculum, negotiate what’s best for our students, and create curriculum that works for local contexts.  There is going to be a lot of that nationwide as we take steps towards providing computing education to all students. The iteration and revision will be expensive, but it’s a necessary expense for sustainable, longterm computing education.

What should we do with the money

At a talk I gave at Indiana University on Friday, Katie Siek asked me my opinion. What do I want to see the funding be used for?

It would be great if some of that funding could start more pre-service CS teacher preparation programs. I have argued that we should fund chairs of CS Education in top Schools of Education (see post here). Germany uses this model — they create CS Education professors who will be there for a career, producing CS teachers, supporting local communities of CS teachers, and serving as national models. An endowed chair is $1-3M at most universities. That is not very expensive for a longterm impact.

I prefer an NYC-like model of reaching every student to the model of a teacher for every school. The data I’ve seen from our ECEP states suggests that most CS teachers teach only a single computing class, and that class is typically mostly white/Asian and male. One CS  teacher per school doesn’t reach all the female and under-represented minority students. Equity has to be a top priority in our choices for these funds, since CS education is so inequitable.

My greatest wish is for computational literacy to be woven into other disciplines, especially across all of STEM. I devoted my career to computing education because I believe in the vision of Seymour Papert, Cynthia Solomon, Alan Kay, and Andrea diSessa. Computational literacy can improve learning in science, mathematics, art, language, and other disciplines, too.

I don’t argue that computer science is more important than other STEM subjects. Rather, computing makes learning in all the other STEM subjects better.

I want us to teach real computational literacy across subjects, not just in the CS class hidden away, and not just in an annual experience. I recognize that that’s a long-term, expensive vision — probably two orders of magnitude beyond the current initiative. We need more long-term thinking in CS education, like building up the CS teacher development infrastructure and making the case to people nationwide for CS education. We are not going to solve CS for All quickly.

When the K-12 CS Framework effort launched back in 2015, I told the story here about a conversation I had with Mike Lach (see post here). He pointed out that the last time we changed all US schools, it was in response to the Civil Rights movement. That’s when we started celebrating MLK Jr Day and added African-American History month. He asked me to think about how much national will it took to make those changes happen. We don’t have that kind of national will in CS education in this country — yet. We have a lot more groundwork to do before we can reach CS education for all students or all schools, and funding alone is not going to get us there.

October 4, 2017 at 7:00 am 9 comments

Developer Bootcamps and Computing Education: Tech Done Right Podcast

I was so excited to be invited to do this podcast with Noel Rappin (my first PhD student) and Jeff Casimir who runs the Turing Academy bootcamp. I learned a lot about bootcamps from Jeff, whom I was pleased to learn is a data geek and measures things pretty carefully.  Two of my favorite insights:

  • Female students are more likely to graduate from the bootcamp. They are more likely than male graduates to leave before six months on the job.
  • Students who skip college and go straight to bootcamp (as Peter Thiel encourages students to do) have a harder time graduating and getting a job. That latter part might be ageism, bias against younger job-seekers.

I recommend the podcast — we had a fun discussion.

How do people learn computing? Who learns best from traditional computer science education and who from bootcamps? How can we teach people who are not developers but who need to learn some programming to do their jobs? Jeff Casimir, the founder of Turing academy, and Georgia Tech’s Mark Guzdial, one of the founders of the International Computing Education Research conference, join Noel to answer these questions and also explain why Excel is both the best and the worst thing in the world.

Source: Tech Done Right Episode 20: Developer Bootcamps and Computing Education with Jeff Casimir and Mark Guzdia

September 29, 2017 at 7:00 am 3 comments

The Negative Consequences of Brown v Board of Education: Integrating Computing Education

The second season of Revisionist History has just finished.  This season didn’t have the same multiple episodes with tight ties to the issues of education as last season (as I described in this blog post), there was one standout episode that does relate to our issues: Miss Buchanan’s Period of Adjustment.  The podcast deals with the negative consequences of the Brown v Board of Education Supreme Court case that declared that separate was not equal and forced schools to integrate.  The well-documented consequence of the integration was the closing of the schools for African-Americans and the firing of Black school teachers.  Gladwell first considers what the Brown family (named in the case) and the other families in the case actually wanted, and about the longterm impact that even today, there are disproportionately few African-American teachers in the US are African-American — and that leads to impacts on students.

When I studied Brown v Board of Education when I was a graduate student at the University of Michigan, we were taught a negative consequence that Gladwell barely touches on.  Gladwell mentions that there were few jobs for an educated Black person at the time of Brown v Board.  The Supreme Court’s decision, and the consequent firing of Black teachers, was an enormous blow to the African-American middle class in the United States.  Employment was lost at a large scale, and longterm impacts on wealth and prosperity can be measured today.

The connection to computer science education is part of the question of how do we reach everyone and help everyone to succeed.  Today’s computing education is de facto segregated — not in the sense of colored vs white classes, but in terms of only certain demographics are in CS classes and other demographics are not.

  • In many of the high schools we work with, even if white and Asian students are in the school population minority, the computer science classes are mostly white and Asian.
  • English CS classes are almost entirely male, maybe even more than in the US (described here).
  • US undergraduate CS classes don’t seem to be retaining women (blog post here).
  • Code.org classes have are almost half poor students (blog post here), and have excellent diversity (see their Medium post here). What are the rich students taking?  The diversity that Code.org is seeing is not reflected in undergraduate CS (see Generation CS report) which has little diversity and has mostly prosperous students. That’s important because undergraduate CS is the path that most students will take to the IT industry, which is mostly white/Asian and male.

How do we improve diversity in computing education?  Can we avoid a heavy-handed and expensive mandate like requiring CS for everyone? I side effect of requiring everyone to take CS might be that we get all the same kind of CS.  Can we provide equal access to everyone without the negative consequences that Gladwell describes from Brown v Board of Education?

Brown v Board of Education might be the most well-known Supreme Court decision, a major victory in the fight for civil rights. But in Topeka, the city where the case began, the ruling has left a bittersweet legacy. RH hears from the Browns, the family behind the story.

Source: Revisionist History Podcast

September 25, 2017 at 7:00 am 1 comment

British girls “logging off” from CS: What’s the real problem?

The BBC reports (in the article linked below) that the “revolution in computing education has stalled.”  The data from England (including the Roehampton Report, discussed in this blog post) do back up that claim — see the quotes at the bottom.

In this post, I’m reflecting on the response from the British Computer Society. “We need to do more with the curriculum to show it’s not just a nerdy boys’ subject. We’ve got to show them it’s about real problems like climate change and improving healthcare.”  There are some interesting assumptions and warrants in these statements.  Do girls avoid CS because they think it’s a boys’ subject, or because it’s not about real problems?  How does the curriculum “show” that it is (or isn’t) a “nerdy boys’ subject”?  If the curriculum emphasized “real problems,” would it no longer be a “nerdy boys’ subject”?  Are these at all connected? Would making CS be like “climate change and improving healthcare” attract more female students?

First, I’d like to know if the girls choosing ICT over CS are actually saying that it’s because CS is “a nerdy boys’ subject,” and if the girls know anything about the curriculum in CS.  In our research, we found that high school students know very little about what actually happens in undergraduate CS, and undergraduate students in CS don’t even know what’s in their next semester’s classes. Changing the curriculum doesn’t do much good if the girls’ decisions are being made without knowing about the curriculum.  The former claim, that CS is perceived by girls as a “nerdy boys’ subject,” is well-supported in the literature.  But is that the main reason why the girls aren’t enrolling?

Do we know that this a curriculum issue at all? The evidence suggests that there are other likely reasons.

  • Maybe it’s not the curriculum’s “problem” focus, but the “learning objective” focus. Do the girls percieve that the point of the course is to become part of the Tech industry as a professional programmer?  Maybe girls are more interested in broadening their potential careers and not limiting their options to IT?  ICT can be used anywhere.  CS might be perceived as being about being a software developer.
  • Are the girls seeing mass media depictions of programming and deciding that it’s not for them?  A 2016 ICER paper by Colleen Lewis, Ruth Anderson, and Ken Yasuhara explored the reasons why students might not feel that they have a good “fit” with CS (see ACM paper link here).  But are those the reasons why women might not even try CS? Maybe they have had experiences with programming and decided that they didn’t fit? Or maybe the decided that syntax errors and unit tests are just tedious and boring?
  • Are the girls seeing mass media depictions of the Tech industry and deciding that they’d rather not be a Googler or work at Uber? They are probably hearing about things like the Damore memo at Google. Whether they think he’s right or not, maybe girls are saying that they just don’t want to bother.
  • Do the girls have more choices, and CS is simply less attractive in comparison?  It may be that girls know that CS is about solving real problems, but they’d rather solve real problems in law, medicine, or business.
  • Do the girls perceive that wages are not rising in the Tech industry?  Or do the girls perceive that they can make more money (perhaps with fewer negative connotations) as a lawyer, doctor, or businessperson?

I have heard from some colleagues in England that the real problem is a lack of teachers.  I can believe that having too few teachers does contribute to the problem, but that raises the same questions at another level.  Why don’t teachers teach computer science?  Is it because they don’t want to be in the position of being “vocational education,” simply preparing software developers?  Or are teachers deciding that they are dis-interested in software development, for themselves or for their students?  Or are the teachers looking at other areas of critical need for teachers and decide that CS is less attractive?

Bottom line is that we know too little, in the UK or in the US (see Generation CS), about what is influencing student and teacher decisions to pursue or to avoid classes in computing. The reality doesn’t matter here — people make decisions based on their perceptions.

In England, entries for the new computer science GCSE, which is supposed to replace ICT, rose modestly from 60,521 in 2016 to 64,159 this year. Girls accounted for just 20% of entries, and the proportion was a tiny bit lower than last year.

ICT entries fell from 84,120 to 73,099, which you would expect as the subject is disappearing from the national curriculum. But it had proved more attractive to girls. Even there, the proportion of female entries fell from 41% to 39%.

Combine the two subjects, and you find that the number studying either subject has fallen by over 7,000 in the past year. Back in 2015 more than 47,000 girls were getting some kind of computing qualification, and that has fallen to about 41,000 – just 30% of the total.

Source: Computer science: Girls logging off – BBC News

September 15, 2017 at 7:00 am 9 comments

Learning Programming at Scale: Philip Guo’s research

I love these kinds of blog posts.  Philip Guo summarizes the last three years of his research in the post linked below.  I love it because it’s so important and interesting (especially for students trying to understand a field) to get a broad explanation of how a set of papers relate and what they mean.  Blog posts may be our best medium for presenting this kind of overview — books take too long (e.g., I did a book to do an overview of 10-15 years of work, but it may not be worth the effort for a shorter time frame), and few conferences or journals will publish this kind of introspection.

My research over the past three years centers on a term that I coined in 2015 called learning programming at scale. It spans the academic fields of human-computer interaction, online learning, and computing education.

Decades of prior research have worked to improve how computer programming is taught in traditional K-12 and university classrooms, but the vast majority of people around the world—children in low-income areas, working adults with full-time jobs, the fast-growing population of older adults, and millions in developing countries—do not have access to high-quality classroom learning environments. Thus, the central question that drives my research is: How can we better understand the millions of people from diverse backgrounds who are now learning programming online and then design scalable software to support their learning goals? To address this question, I study learners using both quantitative and qualitative research methods and also build new kinds of interactive learning systems.

Source: Learning Programming at Scale | blog@CACM | Communications of the ACM

September 11, 2017 at 7:00 am Leave a comment

Google study on the challenges for rural communities in teaching CS

Google continues their series of reports on the challenges of teaching CS, with a new report on rural and small-town communities in the US.  This is an important part of CS for All, and is a problem internationally.  The Roehampton Report found that rural English schools were less likely to have computing education than urban schools.  How do we avoid creating a computing education divide between urban and rural schools?

This special brief from our Google-Gallup study dives into the opportunities and challenges for rural and small-town communities. Based on nationally representative surveys from 2015-16, we found:

  • Students from rural/small-town schools are just as likely as other students to see CS as important for their future careers, including 86% who believe they may have a job needing computer science.

  • Rural/small-town parents and principals also highly value CS, with 83% of parents and 64% of principals saying that offering CS is just as or more important than required courses.

  • Rural/small-town students are less likely to have access to CS classes and clubs at school compared to suburban students, and their parents are less likely to know of CS opportunities outside of school.

  • Rural/small-town principals are less likely to prioritize CS, compared to large-city or suburban principals.

Source: Google for Education: Computer Science Research

September 4, 2017 at 7:00 am 1 comment

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