Archive for October 18, 2017

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 Amy 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 28 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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