Posts tagged ‘computing for all’

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

What Universities Must Do to Prepare Computer Science Teachers: UTeach leads a multi-university group to grow computing education

Kimberly Hughes, Director of the UTeach Institute at The University of Texas at Austin has written a blog post about a multi-university effort to grow CS education. They have an interesting set of recommendations. I look forward to seeing the white paper that the blog post promises!

In-service teacher professional development has been key to the explosive growth of K–12 CS education offerings, but the role of universities in the preparation of computer science teachers is absolutely critical if we are going to address the current shortage of CS teachers at scale and with any kind of lasting impact. Yet there are precious few exemplars on which to model new programs. Partly this has been a chicken and egg problem. For example, the UTeach program at UT Austin has had an undergraduate pathway to CS certification for more than ten years. But with so little demand for CS teachers at secondary schools throughout the state, very few students were recruited and prepared. Now that the demand for CS teachers is increasing, UTeach Austin and other UTeach partner universities are ramping up and expanding their efforts.

Source: What Universities Must Do to Prepare Computer Science Teachers: Networked Improvement in Action

February 23, 2018 at 7:00 am 5 comments

Governor of Rhode Island explains why we should teach programming to everyone

Gina Raimondo, the governor of Rhode Island, was on Freakonomics Radio a few weeks ago. Stephen Dubner challenged their plans to offer computing education at all grade levels in every district.  She had a strong response. Dubner’s question is good. We still don’t have the empirical evidence for the value of teaching computing to everyone. We should do that research — not to figure out if Raimondo made the right bet, but to tune what we’re doing to make sure that we get the maximum benefit for the investment.

I recommend the whole interview.

DUBNER: So, I hear about this kind of thinking a lot, and I certainly understand the appeal and the resonance. But I do also wonder if there’s a proven upside of having everyone learn computer science or programming. It strikes me a little bit like the equivalent of having every student in America during the boom of the internal combustion engine learn to take apart a carburetor. And then I think, if you look at the history of economics and progress, that one of the main strengths of economic progress is the division of labor and specialization, rather than everybody chasing after the latest trends. So I’m curious what the evidence was that inspired that move of yours.

RAIMONDO: I think of it as access and exposure, and also just providing people with a basic level of essential skills. So, everyone has to take math. They may become a writer, they may become an actor, but they ought to have a certain basic level of math skills. First of all, because it’s an essential skill to function. And by the way, they might like math. I think digital skills are the same thing. No matter what job you have, you have to have some basic familiarity with computer skills and digital skills. And so it is as essential in this economy as any other skill that we teach. But also, we know — and there’s loads of data on this girls, people of color, and low-income folks are less likely to go into I.T. fields, which tend to be higher-paying. However, if they’re exposed to some computer training, they’re much more likely to go into the field and do well at it.

Source: How to Be a Modern Democrat — and Win – Freakonomics

February 16, 2018 at 7:00 am 1 comment

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

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 should we teach programming (Hint: It’s not to learn problem-solving)

This is a revision of the original post. Several readers pointed out on Twitter that my original post was insensitive. It read like an attack on Brenda, a woman of color, from a senior white guy (me). That was not my intent, and I apologize for that. I am grateful to Joseph P. Wilson who helped me understand how to avoid that impression. I can’t change the post that went out yesterday, but I will be more careful in future blog posts.


At the CS for All Consortium Celebration Tuesday, Brenda Wilkerson gave the closing keynote. The full livestream of the CS for All Summit is available here, and it includes Brenda’s talk. I’m a huge fan of Brenda, and she’s done fabulous work in Chicago. She is a leader in bringing CS to All.

I have not seen Brenda’s talk or any of the livestream. My experience of the Consortium Celebration was through reading the Twitter stream as I found time during the day. Brenda had one slide (which you can see in the tweet linked here) that I disagreed with, and because it’s an important point, I’m going to respond to it here.

It says, “Computer science builds the mental discipline for breaking down problems, and solving them.” There are few studies that test this claim as “computer science,” but there have been lots of studies looking for transfer from teaching programming to general problem-solving skills. Probably the first study investigating this claim is Roy Pea and Midian Kurland’s paper On the cognitive effects of learning computer programming. You can find this claim in a paper by Henry Walker to which I responded in this blog. You can see it in posts all over the Internet, from this blog post to this article from a teacher in England. There is a strong belief out there that learning computer science, and programming called out specifically, leads to new problem-solving and “a new way to think.”

There is simply not evidence in support of these claims. I talk about these in my book, I reference the Palumbo meta-review in this blog post, and NYTimes wrote about it this last spring. Like “learning styles” and “Latin teaches thinking,” this is a persistent myth that learning computing leads to problem-solving skills, and we have no support the claim.

I tweeted in response to Brenda’s slide, and several CS teachers asked me, “So why teach programming or computing at all?”  That’s a great question!  Here are some of my top reasons:

  1. To understand our world. The argument that Simon Peyton Jones made in England for their computer science curriculum is that Computer Science is a science like all the others. We teach Chemistry to students because they live in a world with chemical interactions. We teach Biology because they live in a world full of living things. We teach Physics because they live in a physical world. We should teach Computer Science because they live in a digital world.
  2. To study and understand processes. Alan Perlis (first ACM Turing Award laureate) argued in 1961 that everyone on every campus should learn to program. He said that computer science is the study of process, and many disciplines need people to know about process, from managers who work on logistics, to scientists who try to understand molecular or biological processes. Programming automates process, which creates opportunities to simulate, model, and test theories about processes at scale. Perlis was prescient in predicting computational science and engineering.
  3. To be able to ask questions about the influences on their lives. C.P. Snow also argued for everyone to learn computing in 1961, but with more foreboding. He correctly predicted that computers and computing algorithms were going to control important aspects of our lives. If we don’t know anything about computing, we don’t even know how to ask about those algorithms. It shouldn’t be magic.  Even if you’re not building these algorithms, simply knowing about them gives you power. C.P. Snow argues that you need that power.
  4. To use an important new form of literacy. Alan Kay made the argument in the 1970’s that computing is a whole new medium. In fact, it’s human’s first meta-medium — it can be all other media, and it includes interactivity so that the medium can respond to the reader/user/viewer. Computing gives us a new way to express ideas, to communicate to others, and to explore ideas.  Everyone should have access to this new medium.
  5. To have a new way to learn science and mathematics. Mathematics places a critical role in understanding our world, mostly in science. Our notation for mathematics has mostly been static equations. But code is different and gives us new insights. This is what Andy diSessa has been saying for many years. Bruce Sherin, Idit Harel, Yasmin Kafai, Uri Wilensky, and others have shown us how code gives us a powerful new way to learn science and mathematics. Bootstrap explicitly teaches mathematics with computing.  Everyone who learns mathematics should also learn computing, explicitly with programming.
  6. As a job skill. The most common argument for teaching computer science in the United States is as a job skill.  The original Code.org video argued that everyone should learn programming because we have a shortage of programmers. That’s just a terrible reason to make every school child learn to program. That’s what Larry Cuban was arguing this last summer. Tax payers should not be funding a Silicon Valley jobs program. Not everyone is going to become a software developer, and it doesn’t make any sense to train everyone for a job that only some will do. But, there’s some great evidence from Chris Scaffidi (that I learned about from Andy Ko’s terrific VL/HCC summary) showing that workers (not software developers) who program make higher wages than those comparable workers who do not. Learning to program gives students new skills that have value in the economy. It’s a social justice issue if we do not make this economic opportunity available to everyone.
  7. To use computers better. This one is a possibility, but we need research to support it. Everyone uses computers all the time these days. Does knowing how the computer works lead to more effective use of the computer?  Are you less likely to make mistakes? Are you more resilient in bouncing back from errors? Can you solve computing problems (those that happen in applications or with hardware, even without programming) more easily?  I bet the answer is yes, but I don’t know the research results that support that argument.
  8. As a medium in which to learn problem-solving. Finally, computer programming is an effective medium in which we can teach problem-solving. Just learning to program doesn’t teach problem-solving skills, but you can use programming if you want to teach problem-solving. Sharon Carver showed this many years ago. She wanted students to learn debugging skills, like being able to take a map and a set of instructions, then figure out where the instructions are wrong. She taught those debugging skills by having students debug Logo programs. Students successfully transferred those debugging skills to the map task. That’s super cool from a cognitive and learning sciences perspective. But her students didn’t learn much programming — she didn’t need much programming to teach that problem solving skill.But here’s the big caveat: They did not learn enough programming for any of the other reasons on this list!  The evidence we have says that you can teach problem-solving with programming, but students won’t gain more than that particular skill. That is a disservice to students.

Certainly there are more reasons than these, and I’ve seen several in the response to this blog post, and some in the comments below.

This was just one slide in Brenda’s talk. Her overall point was much more broader and more significant. I strongly agree with Brenda’s key point: CS for All is a social justice issue. Learning computing is so important that it is unjust to keep it from some students. Currently, CS is disproportionately unavailable to poorer students, to females, and to minority ethnic groups. We need CS for All.

October 18, 2017 at 12:30 pm 13 comments

More Teachers, Fewer 3D Printers: How to Improve K–12 Computer Science Education 

A nice summary of where we’re at with CS Ed in the United States, where additional funding and effort should go, and where it shouldn’t.

Addressing the teacher shortage should be the number one use for the new funds allocated by the Trump administration, says Mark Stehlik, a computer science professor at Carnegie Mellon University. A lack of qualified teachers is the biggest barrier to CS education in the U.S., he says, and he thinks the problem is going to get worse. An earlier generation of CS educators has started to retire, and he says younger CS graduates “aren’t going into education because they can make twice or more working in the software industry.”

One solution could be to expand the reach of each CS educator through online classes. But “online curricula aren’t going to save the day, especially for elementary and high school,” Stehlik says. “A motivated teacher who can inspire students and provide tailored feedback to them is the coin of the realm here.”

Where the money should not be spent? On hardware and equipment. Laptops, robots, and 3D printers are important, says Code.org’s Yongpradit, “but they don’t make a CS class. A trained teacher makes a CS class. So money should be focused on training teachers and offering robust curriculum.”

Source: More Teachers, Fewer 3D Printers: How to Improve K–12 Computer Science Education – IEEE Spectrum

October 18, 2017 at 7:00 am 8 comments

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