What’s the role of the body in learning computing?

July 9, 2010 at 6:51 am 7 comments

The notion of “embodied cognition” and the role of the body in learning has been popping up for me in various places recently, which has me wondering about the role of sensing and moving in the physical world for learning computing.

  • At the Journal of the Learning Sciences editorial board meeting, there was some discussion about papers on “embodied cognition” (where I joked to the person sitting next to me, “Do we do papers on disembodied cognition?” but got caught by Cindy Hmelo, co-Editor-in-Chief, then the teacher made me repeat it in front of the whole class.)
  • As Aleata mentioned, Ulrich Hoppe was strongly against the current interest in tangible programming at ICLS.  He criticized both the LilyPad and our Media Computation work as focusing on the wrong things.  These are pandering to “engagement and motivation,” and he feels that it’s more important to get students to think critically about different programming languages than we’re using now.  He believes that we should shift our focus to declarative programming languages as having a stronger mathematical base, and provided a detailed example in Prolog.
  • In the recent issue of CACM, there’s an interesting (but too short) interview with Chuck Thacker (new Turing Award winner) where he talks about his interest in tablet computers.  He suggests that the only way of getting information faster into a computer than typing is “to use a different set of muscles…writing or drawing.”
  • I’m currently reading some papers from the Spatial Intelligence and Learning Center where they talk about how we evolved learning with our hands.  The interesting question they’re exploring is how use of our hands might support learning of higher-level cognitive functioning.  Does the mere act of writing notes about complex topics help us learn those topics?  How does use of our hands in manipulatives enhance learning?

Which, of course, has me wondering about the role of these manipulatives in learning about computing.  Does the use of the robot and the textiles in the LilyPad work trigger a deep evolutionary mechanism that might be enhancing learning of the much more abstract computer science?  I don’t know, but I’m intrigued and am digging further.

One such connection that has been a focus of some of my research is the application of embodied cognition research and theory to explain various anomalies in educational research and new techniques for instruction and educational technology, as described in a recent post about an upcoming AERA symposium on embodied cognition and education I am organizing.

For example, researchers have found that attending to student gestures or using gestures while explaining concepts or procedures (for example in a math class) helps student understanding, and also having students interact with and physically manipulate models (such as acting out a story or physically manipulating a simulation) helps student reading comprehension or physics understanding.

via The Connection between Embodied Cognition and Learning: 3 Examples from Physics Education « EdTechDev.

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7 Comments Add your own

  • 1. Alan Kay  |  July 9, 2010 at 1:51 pm

    Aren’t there a hundred years of examples from Montessori, through PIaget, Vygotsky, Bruner, Xerox PARC, the Tufts “body physics”, etc., to draw from?

    Did all this get lost? Is there no “Learning Sciences” Ur-book that gathers together the core of what is known?



    • 2. Alan Kay  |  July 9, 2010 at 2:30 pm

      For example

      Click to access AJP000858SokoloffComputers.pdf

      We put this on a Mac and used it at the Open School with children — and it worked extremely well.

      Also, I forgot to mention Hadamard’s study of scientific and mathematical thinking, which has come up a few times in this blog.

      I.e. there is a lot known and tested about “multiple mentality learning” where some of the mentalities are highly connected to sensors and effectors.

      It is a little painful to see practitioners in a conference apparently not be aware of this past work.



  • 3. Mark Guzdial  |  July 9, 2010 at 3:40 pm

    Microcomputer based labs are great, no question. How do they help to learn computing? Yes, there is a learning sciences book: http://www.amazon.com/Cambridge-Handbook-Learning-Handbooks-Psychology/dp/0521607779

  • 4. Mark Guzdial  |  July 9, 2010 at 3:46 pm

    Is this what you meant by Tufts “body physics”? http://www.ceeo.tufts.edu/robolabatceeo/coolandnew/Rob_HTML/TableOfContents.html

    • 5. Alan Kay  |  July 10, 2010 at 8:42 am

      The URL I gave in comment 2 is an example of what I meant by “body physics”. Thornton and others were looking for a pretest that would predict grades at the end of the course and eventually found that a test on the ability to read graphs, especially about motion, acceleration, etc., would do it.

      Then they wondered if they could improve things if they could find a good way to help the students learn how to read graphs (a reach, but an interesting idea).

      They initially (mid-80s) hooked a sonic range finder to an Apple II to track the forward and backward motion of the students’ bodies and plot these on the screen.

      Then they did many things, inclduing have the students try to match the time-motion graphs with graphs made by their bodies. They did this instead of one of the labs for the physics course — and the results were huge and repeatable.

      This hooks in very strongly with Bruner’s notions of where and how you should start to learn difficult ideas, and also with Hadamard’s findings.

      It should be the basis of any “physics of motion” (and I think science and math in general) courses for children and (as Thornton showed us) even for college kids.

      The URL in 4. seems to be about something different, but also looks promising.



  • 6. Cameron Fadjo  |  July 10, 2010 at 12:25 pm

    At Columbia we are exploring a form of applied embodied cognition to the instruction of abstract concepts in computer programming. The form, called Direct Embodiment, has the students physically enact a script-like sequence of statements written in Scratch that implement simple and complex conditional statements and mathematical operators. You can read more about our research by visiting http://www.ilt.columbia.edu/projects then click on ‘iWorld’ or, to read some of our most recent articles, visit http://www.columbia.edu/~clf2110 and click on Publications.

    So far we have found that Direct Embodiment may lead to increased implementation of complex conditional statements (i.e. conditional statements with a logical operator or nested conditionals). Our current line of research examines the effects of implicit vs. explicit imagination when physically enacting pre-defined scripts and if either instructional form has a positive effect on mental model formation and efficient code structure implementation (a harder construct to define and measure).

    Alan, thank you for sharing the article from comment two.

    Cameron Fadjo

  • […] As I’ve mentioned previously, SILC hasn’t looked much at computer science yet, but there are lots of reasons to think that spatial learning plays an important role in computing educat…. Spatial reasoning, which is the ability to mentally visualize and manipulate two- and […]


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