Growing CS Ed through Schools of Ed, and CT is Unlikely: Report from Oldenburg

July 13, 2015 at 7:31 am 11 comments

I’ve written a couple times now about the workshop I attended at the University of Oldenburg the first week of June. (See the post where I talked about my two weeks in Germany.)  For Blog@CACM, I wrote a post about teaching as collective practice and the workshop I took with Barbara Hofer (see post here). I wrote about learning about teacher beliefs and self-efficacy from Helenrose Fives here (see post).

Before we left for the workshop, I got to spend time with Ira Diethelm at the University of Oldenburg and one of her students.  Ira is one of at least 16 (that Ira could count) CS Education professors in Germany.  Ira works with pre-service teachers, in-service teachers, and graduate students.  Her graduate students build outreach efforts and curricula as part of their research, then roll them out and provide resources to teachers.  It’s remarkable what Ira is doing, and I understand that the other German CS Ed professors do similar things.  I came away with a new insight: If we want to bootstrap and sustain CS Education in the United States, we should fund several endowed chairs of CS Education at top Schools of Education.  Eventually, we have to have pre-service computing education programs if we want to make CS education sustainable (see that post here).  Creating these endowed chairs gives us the opportunity to create positions like Ira’s in the United States.

Overall, the workshop was a terrific experience.  The PhD student work was fascinating, and I enjoyed discussing their research with them. It was great to hear about German research perspectives that I hadn’t previously, like the Model of Educational Reconstruction that informs science education (see paper here). Barbara and Helenrose were only two of a several outstanding international education researchers who attended.  As I mentioned to Pat Alexander (who has a lengthy Wikipedia page of her accomplishments), I enjoyed being able to wallow in educational psychology for a week, because I so rarely get to do that.  I gave a talk on three of our projects related to the theme of developing teachers: on Lijun Ni’s work on teacher identity, on the Disciplinary Commons for Computing Education, and on our ebook for preparing CS teachers.  (See Slideshare here.)


The response to my talk was fascinating.  Some of the German mathematics education researchers are deeply opposed to computing education in schools. (I suspect that more than one of them completely skipped my talk because they are so opposed.)  “Computing education keeps stealing from mathematics teachers, and learning mathematics is more important.”  At my talk, Pat Alexander asked me the same question that Peter Elias asked Alan Perlis in 1961, “Won’t the computer eventually just understand us?  Doesn’t the computer just become invisible and not need to be programmed?”  I told the story about Alan Perlis’s talk and about Michael Mateas’s argument, “There will always be friction.” From the computing educators, I heard a lot of anger. The German computing education researchers feel that other fields squeeze CS out because the they are not willing to allow computing education to take up any time or budget in the curriculum.

Probably the most interesting pushback was against computational thinking.  The educational psychologists thought it was unbelievable that learning computing would in any way impact the way that people think or problem-solve in everyday life.  “Didn’t we believe that once about Latin? and Geometry?” asked Gavin Brown.  The psychologists at the workshop I attended saw a clear argument that we need to introduce computing in high school so that students can see if it’s for them, but not to teach general problem-solving skills. If we really want algorithmic thinking, they can design easier ways to achieve that goal than teaching programming.

We can probably help students to learn about computing in such a way that it might influence problem-solving on the computer. That’s part of Jeanette Wing’s model of Computational Thinking (see her 2010 paper). It’s the “Computational Thinking in Daily Life” part that the psychologists weren’t buying.  That learning about computation helps with computational X is quite reasonable. If you understand what IP addresses are, we can help you to understand DNS problems and to realize that it’s not really that big of a deal if Wikipedia stores your IP address (see story about Erika Poole’s research).  There is evidence that learning one programming language will likely transfer to another one (see Michal Armoni’s paper on transfer from Scratch to a text-based language).  Learning to program is unlikely to influence any problem-solving in everyday life.

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11 Comments Add your own

  • 1. Neil Brown  |  July 13, 2015 at 7:41 am

    I am open to the idea that computational thinking is overhyped, and unlikely to have the impact that everyone hopes on thinking. But one small challenge to the final sentence: my understanding was that problem solving skills could transfer when you hit mastery level. It seemed to me that a lot of professional programmers see the benefits of computational thinking because they have mastered programming and thus do see transfer to the rest of their life, but that this argument does not hold for all schoolchildren, because they will not achieve mastery.

    • 2. Mark Guzdial  |  July 13, 2015 at 10:26 am

      A very interesting question, Neil, for which I don’t have an answer. We know that increased mastery makes transfer more likely, but that’s not the same as happens spontaneously. Years ago, I remember discussions at the Learning Sciences conferences about whether expertise led to improved learning a new domain. For example, does a chess grandmaster learn programming faster than a novice, because the grandmaster knows how to learn? I don’t know of empirical evidence on this point. The predictions we had back then were “might happen, might not.” Becoming a chess grandmaster doesn’t require someone to think about how chess connects to other parts of life or learning anything else. Similarly, a master programmer might look for ways to connect programming to other kinds of problem-solving. I know of no empirical studies that show that this happens regularly.

  • 3. Raul Miller  |  July 13, 2015 at 7:56 am

    These sound like some good arguments against most forms of education.

    Then again, I suspect Sturgeon’s Law applies, here.

    • 4. Raul Miller  |  July 13, 2015 at 8:14 am

      P.S… a perhaps related thought train:

      Imagine that a computing system fails. Given the amount of malware on the internet can we say anything definitive about the country of origin for the likely cause of the failure? Can we say anything statistical about that? Throw in personal responsibility, how does that change things? Does the malware issue retain any significance? Do robust systems overly mask the malware issue? Can we trust what we encounter in this environment? Why or why not? How or how not?

  • 5. Dan Lessner  |  July 13, 2015 at 5:36 pm

    Mark, did any of those maths ed researchers elaborate on why exactly is mathematics more important? Or perhaps which topics, specifically? I don’t think many people would argue that computing is more important than arithmetics, fractions or percentages. But some of the more advanced maths chapters do not win over basic computing in my eyes.
    Not to mention that I find this hostility silly especially in the case of M and CS, which can brilliantly support each other.
    Nevertheless, we often see similar sentiments in Czech Republic, so I am interested in details from elsewhere.

    • 6. Mark Guzdial  |  July 13, 2015 at 6:19 pm

      Nope, no details. I was listening and trying to understand. I did try to respond to some of those issues in my talk. But the mathematics education researchers I hoped to speak to weren’t there.

      • 7. Dan Lessner  |  July 20, 2015 at 7:50 am

        Mark, regardless of how sad it is, thank you for your answer.

  • […] start teacher education programs, and hire education faculty who will focus on CS education.  I pointed out previously that that’s how Germany is bootstrapping CS education. They’re making the investment in CS ed faculty who will keep programs running for decades. […]

  • […] that will happen. Many studies investigating this kind of impact have not found that effect. (I’ve reported in the past how educational psychologists find computational thinking implausible.)  Sure, there other definitions of computational […]

  • […] rigor looks like – and it’s possible that interdisciplinary computational thinking is not a thing at all. Still, I think there is a place for computer science in the liberal arts (that is, in the […]

  • […] 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 […]


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