Posts tagged ‘Seymour Papert’

A little bit of computing goes a long way, and not everyone needs software engineering: The SIGCSE 50th Anniversary issue of ACM Inroads

This year is the 50th SIGCSE Technical Symposium, and Jane Prey was guest editor for a special issue of ACM Inroads on 50 years of ACM SIGCSE. You can see the current issue here, but yes, it’s behind a paywall — ACM Inroads is meant to be a membership benefit.

I’m really fascinated by this issue. Sally Fincher does a nice job telling the story of ICER. I enjoyed Susan Rodgers’ and Valerie Barr’s reflections. I’m still trying to understand all of Zach Dodds’ references in his SIGCSE 2065 future-retrospective. I found some of the articles frustrating and disagreed with some of the claims (e.g., I don’t think it’s true that AP CS enrollments plummeted after introducing Java), but discussion can be good for the community.

I was asked to write a piece about What we care about now, and what we’ll care about in the future. My bottom line is a claim that John Maloney (of Squeak, Scratch, and GP fame) reminded me is a favorite phrase of the great Logo (and many other things) designer, Brian Silverman: A little bit of computing goes a long way.

The important part of Scratch is that computationalists find value in it, i.e., that they can make something that they care about in Scratch. What we see in Scratch is the same process we see among the computationalists in computational photography, journalism, and science. They don’t need all of computer science. They can find value and make something useful with just some parts of computing. Scratch projects smell wonderful to Scratch computationalists.

There’s been a thread on Twitter recently about the use of software engineering principles to critique Scratch projects (see the thread starting here). Researchers in software engineering claim that Scratch code “smells,” e.g., has bad practices associated with it. There’s even a website that will analyze your Scratch project in terms of these software engineering practices, DrScratch.  The website claims that it is measuring computational thinking skills — I see no evidence of that at all.

These software engineering researchers are misunderstanding users and genres of programming. They ought to read Turkle and Papert’s Epistemological Pluralism and the Revaluation of the Concrete. People code for different purposes, with different ways of appropriating code. The standards of the software engineer are not appropriate to apply to children. Not everybody is going to be a professional software developer, and they don’t need to be.

Increasingly, people are only going to use parts of computer science, and they will achieve fluency in those. That’s a wonderful and powerful thing. A little bit of computing goes a long way.

January 7, 2019 at 7:00 am 26 comments

Constructivism vs. Constructivism vs. Constructionism

I wrote the below in 1997. I’m surprised that I still find references to it from time-to-time. That website may be going away soon, so I thought I’d put it here (only very slightly edited) in case others may find it useful.

I’d like to offer my take on the meaning of these words. I hear them used in so many ways that I often get confused what others mean by them.

Constructivism, the cognitive theory, was invented by Jean Piaget. His idea was that knowledge is constructed by the learner. There was a prevalent idea at the time (and perhaps today as well) that knowledge is transmitted, that the learner was copying ideas read or heard in lecture directly into his or her mind. Piaget theorized that that’s not true. Instead, learning is the compilation of complex knowledge structures. The learner must consciously make an effort to derive meaning, and through that effort, meaning is constructed through the knowledge structures. Piaget liked to emphasize learning through play, but the basic cognitive theory of constructivism certainly supports learning through lecture — as long as that basic construction of meaning takes place.

I don’t know who invented the notion of Constructivism, the educational philosophy, but it says that each students constructs their own, unique meaning for everything that is learned. This isn’t the same as what Piaget said. Piaget’s theory does not rule out the possibility that you and I may construct exactly the same meaning (i.e., exactly the same knowledge constructions) for some concept or domain. The philosophy of constructivism say that learners will construct their own unique meanings for concepts, so it is not at all reasonable to evaluate students as to how well they have all met some normative goal. (Radical constructivists go so far as to say that the whole concept of a curriculum makes no sense since we cannot teach anyone anything — students will always simply create their own meaning, regardless of what teachers do.) Philosophical constructivists emphasize having students take control of their own learning, and they de-emphasize lecture and other transmissive forms of instruction. This philosophical approach gets complicated by varying concepts of reality: If we all interpret things differently, is there any correct reality?

From my perspective, the assumption of constructivists is currently an untestable hypothesis. We know of no way to peer into someone’s mental constructions. Until we can, we do not know if you and I think about the concept of velocity differently or the same.

Constructionism is more of an educational method which is based on the constructivist learning theory. Constructionism, invented by Seymour Papert who was a student of Piaget’s, says that learning occurs “most felicitously” when constructing a public artifact “whether a sand castle on the beach or a theory of the universe.” (Quotes from his chapter “Situating Constructionism” in the book “Constructionism” edited by Papert and Idit Harel.) Seymour does lean toward the constructivist learning philosophy in his writings, where he talks about the difficulty of conveying a complex concept when the reader is going to construct their own meaning. In general, though, his claim is more about method. He believes that students will be more deeply involved in their learning if they are constructing something that others will see, critique, and perhaps use. Through that construction, students will face complex issues, and they will make the effort to problem-solve and learn because they are motivated by the construction.

The confusion that I and others have about these terms stems from (a) similar looking words and (b) meaning at different levels of the word construct. Piaget was talking about how mental constructions get formed, philosophical constructivists talk about how these constructions are unique (noun construction), and Papert is simply saying that constructing is a good way to get mental constructions built. Levels here are shifting from the physical (constructionism) to the mental (constructivism), from theory to philosophy to method, from science to approach to practice.

March 19, 2018 at 9:00 am 11 comments

Seymour Papert Tribute at IDC 2013

I only planned to watch a little bit of this.  Allison Druin’s talk was particularly recommended to me.  So I started watching, and Paulo Blikstein’s opening remarks were so intriguing. (I loved his characterization that today’s notions of “personalized learning” were “like telling a prisoner that he can walk around his cell all he wants.”)  I hadn’t heard Edith Ackermann in decades, and was particularly struck by her comment, “Any theory of learning that ignore resistances to teaching misses the point!”  Mike Eisenberg, Mitchel Resnick, and Uri Wilensky were all wonderful and insightful talks, and Allison was as good as the recommendation promised.  90 minutes later, I’m explaining to my family where I’d disappeared to…

The intellectual ideas discussed are fascinating, from epistemology to politics to education to design.  Recommended.

July 9, 2013 at 1:19 am 2 comments

The Royal Society wants every UK Child to learn Computing

The Royal Society’s report on “Computing in Schools” was released yesterday, and it makes broad and significant recommendations.  Much of the report is focused on preparing teachers for a rigorous computer science curriculum, and on creating an infrastructure in schools where computing is available and maintained. The report is frank and honest about the challenges of implementing a rigorous computer science curriculum in schools.

I am most excited for what the report recommends about the curriculum.  The overall goal is “Every child should have the opportunity to learn Computing at school.”  The specifics include:

  • Every child should be expected to be ‘digitally literate’ by the end of compulsory education, in the same way that every child is expected to be able to read and write.
  • Every child should have the opportunity to learn concepts and principles from Computing (including Computer Science and Information Technology) from the beginning of primary education onwards, and by age 14 should be able to choose to study towards a recognised qualification in these areas.

Given the lack of specialist teachers, we recommend that only the teaching of digital literacy is made statutory at this point. However, the long-term aim should be to move to a
situation where there are sufficient specialist teachers to enable all young people to study
Information Technology and Computer Science at school. Accordingly, the Government should put in place an action plan to achieve this.

“Statutory” courses (and the report goes into some detail about what “statutory” means and why they make that recommendation)! Computing for everyone!  Think about what you could do in science, mathematics, and business classes if you could assume that everyone knew something about computer science from age 14.  Maybe Seymour Papert’s vision of computing being used to create a “Mathland” could finally be realized in the UK.  Think about how higher education computer science would change if you could assume several years of introductory computer science already.  Here in the US? Well, we’ll always have drills and drafting tables.

January 13, 2012 at 8:15 am 8 comments

Learning about Learning (even CS), from Singing in the Choir

Earlier this year, I talked about Seymour Papert’s encouragement to challenge yourself as a learner, in order to gain insight into learning and teaching.  I used my first-time experiences working on a play as an example.

I was in my first choir for a only year when our first child was born.  I was 28 when I first started trying to figure out if I was a bass or tenor (and even learn what those terms meant).  Three children and 20 years later, our children can get themselves to and from church on their own. In September, I again joined our church choir.  I am pretty close to a complete novice–I have hardly even had to read a bass clef in the last two decades.

Singing in the choir has the most unwritten, folklore knowledge of any activity I’ve ever been involved with. We will be singing something, and I can tell that what we sang was not what was in the music.  “Oh, yeah. We do it differently,” someone will explain. Everyone just remembers so many pieces and how this choir sings them.  Sometimes we are given pieces like the one pictured above.  It’s just words with chords and some hand-written notes on the photocopy.  We sing in harmony for this (I sing bass).  As the choir director says when he hands out pieces like this, “You all know this one.”  And on average, he’s right.  My wife has been singing in the choir for 13 years now, and that’s about average.  People measure their time in this choir in decades.  The harmony for songs like this were worked out years and years ago, and just about everyone does know it.  There are few new people each year — “new” includes even those 3 years in. (Puts the “long” four years of undergraduate in new perspective for me.) The choir does help the newcomers. One of the most senior bass singers gives me hand gestures to help me figure out when next phrase is going up or down in pitch. But the gap between “novice+help” and “average” is still enormous.

Lave and Wenger in their book “Situated Learning” talk about learning situations like these.  The choir is a community of practice.  There are people who are central to the practice, and there are novices like me.  There is a learning path that leads novices into the center.

The choir is an unusual community of practice in that physical positioning in the choir is the opposite of position with respect to the community.  The newbies (like me) are put in the center of our section.  That helps us to hear where we need to be when singing.  The more experienced people are on the outside.  The most experienced person in the choir, who may also be the eldest, tends to sit on the sidelines, rather than stand with the rest of the choir.  He nails every note, with perfect pitch and timing.

Being a novice in the choir is enormous cognitive overload.  As we sing each piece, I am reading the music (which I’m not too good at) to figure out what I’m singing and where we’re going. I am watching the conductor to make sure that my timing is right and matches everyone else. I am listening intently to the others in my section to check my pitch (especially important for when there is no music!).  Most choir members have sung these pieces for ages and have memorized their phrasing, so they really just watch the director to get synchronized.

When the director introduces a new piece of music with, “Now this one has some tricky parts,” I groan to myself.  It’s “tricky” for the average choir members — those who read the music and who have lots of experience.  It’s “tricky” for those with literacy and fluency.  For me, still struggling with the notation, it takes me awhile to get each piece, to understand how our harmony will blend with the other parts.

I think often about my students learning Java while I am in choir.  In my class, I introduce “tricky” ideas like walking a tree or network, both iteratively and recursively, and they are still struggling with type declarations and public static void main.  I noticed last year that many of my students’ questions were answered by me just helping them use the right language to ask their question correctly. How hard it must be for them to listen to me in lecture, read the programs we’re studying, and still try to get the “tricky” big picture of operations over dynamic data structures–when they still struggle with what the words mean in the programs.

Unlike working on the play, singing in the choir doesn’t take an enormous time investment — we rehearse for two hours one night, and an hour before mass.  I’m having a lot of fun, and hope to stick with it long enough to move out of the newbie class.  What’s motivating me to stick with it is enjoyment of the music and of becoming part of the community.  There’s another good lesson for computer science classes looking to improve retention.  Retention is about enjoying the content and enjoying the community you’re joining.

 

December 20, 2011 at 8:45 am 6 comments

Child Development Expert Offers Ideas for Promoting Early Science Learning

“By focusing more on middle and high school kids, we are already missing the boat because we are saying that this is where science starts,” she explains, “when in reality attitudes toward science, perceptions of science, and identities —where children start to see themselves as people who do science—begin much earlier and in home contexts.”

via “Educate to Innovate” Campaign: Child Development Expert Offers Ideas for Promoting Early Science Learning.

Is the above true?  I do believe that children’s identities and home contexts influence their attitudes about science. However, I believe that the those studying children (including Piaget, in this wonderful piece by Seymour) have suggested that young children act as scientists.  My read of the literature suggests that kids don’t turn away from science until middle school.  Thus, focusing on middle school is an appropriate point of intervention, because that’s when the identities start changing.

December 14, 2009 at 3:52 pm 3 comments

How do we make high school CS classes more “real”?

I started working on a reply to Alan Kay’s comment on my previous blog post, and as it got longer with more links, I realized I should just use blog-owner’s prerogative and make a new post.  The issue we were discussing was how to make the case that the AP CS should count as a course that fulfills the “science” requirement in Georgia.  I commented:

Barb and I were just talking last night about the issue you raised, that the AP CS curriculum doesn’t look like a science. In the argument that I offered to the GaDOE, Computer Science classes have a lot of science practices (even if the content is not easily recognized as science by a traditional scientist), such as developing hypotheses, experimentation, and analysis of results. However, most CS curricula (including AP CS) do not make those connections between debugging and the scientific method explicitly.

Alan replied that he’d like to see more “real science” in these classes.

While pretty much agreeing with your comments, I think the real issue is a much deeper epistemological one — and is a problem not just in computer “science” but in the teaching of most high school and many college “real sciences” which have deep models as the representations for their theories (e.g. physics, chemistry, biology).

In the “real deal” it’s not so much about “hypotheses, experiments, analysis” (the standard elementary school characterization of science) as it is about the goodness and depth of the mapping between the observations and the model (in the standard characterization of science, this could be thought of as real thresholds in what “analysis” actually should mean).

So, how do we make that happen?  How do we get the “real deal” into high school classes?

My suggestion is that this doesn’t happen by making the argument for “real” classes at the state level.  The job of the Georgia Department of Education Science Committee is, explicitly,  to ask if any individual class “aligns with the GPS science standards, and/or the national science standards.” State standards are not re-written all that often, and Georgia just rewrote theirs.  Take a look at a given set of science standards, like those for high school Chemistry.  There you see terms like “hypotheses, experiments, analysis.”  Terms like “modeling” and “mapping” don’t appear at all.

How do we get a modeling and mapping focus in these classes?  Georgia (probably like most states) takes their lead from national authorities, like the American Association for the Advancement of Science standards “Science for All Americans.”  Take a look at what AAAS says about how to teach science — it’s a pretty close match to what Georgia has in their standards.  Nothing about modeling or mapping there, either.

The suggestion that I’m making is, if you want to get science classes to change, to make them more “real,” get the National Academies, or AAAS, or similar respected body to issue a report.  Larry Snyder’s NRC report on “Information FITness” gets cited a lot when discussing what students need to know about computer science.  It’s hard to make the case at the State level, because people within the State look outside the State for evidence.  These kinds of national reports make a difference.

Now, how do you get CS classes to be more “real”?  One way is by changing the Advanced Placement class, as NSF is trying to do.  Another way might be to use the same strategy as for Science — get the recognized authorities to come out with a statement, a report that says, “Here’s what real Computing Education should look like.”

My own opinion is that radical change is not going to come out of the ACM/IEEE curriculum standards process.  I was part of the committee for the CS 2008 standards update.  It is hard to get a dramatic and powerful statement for change out of that process.  We’re in a challenging stage in our field — we’ve got lots of ideas, and few measures for determining which is better than the other.

There were easily a half dozen new approaches to teaching CS that were vying to get a mention (better yet, a recommendation) in the new curricular volume.   How do you decide?  We have no reliable and valid measures of computing knowledge that cross approaches and languages.  We as a field can’t even agree on the learning objectives.  We on the committee tried to come up with some measure about usage and peer-review, but even that was insufficient.  If three schools do kinda the same thing and the approach got mentioned in a software engineering conference article, does that count?  Maybe it should — do we have a better standard? To list everything is no recommendation or guidance at all.  One of the criticisms of CC2001 was that it recommended a half dozen approaches for CS1 already.  I pushed to get some of those off the list — don’t we have evidence that some of these aren’t really all that effective?  The push back was similar.  “How do we really know that these don’t work?” and “We know friends who use those approaches.  How can we say in this volume that they don’t work?”  The result is that the volume reflects the least common denominator curriculum, which is useful for describing current accepted best practice, but it’s not a forward-looking statement of what should be.

Seymour Papert in his book The Children’s Machine argued that part of what happened to Logo was school.  School has a process of compartmentalizing and turning new ideas into standard curricula.  We can argue that this is wrong (and Seymour did in his book), but it is the reality.  I am describing here the process (as I understand it now, incomplete as that understanding is) of how one achieves curricular change at the secondary level — you show how you can meet the existing standards, or you push to get the standards re-written, with the most leverage coming from authoritative statements at the national level.  It’s hard work, but as Seymour points out, that’s how the system keeps from thrashing.  The system is designed to make it hard to change the system.

October 19, 2009 at 10:39 am 1 comment

Education is to Social Work, as Civil Engineering is to Chemical Engineering

I’m listening to Paul Romer’s Seminar about Long Term Thinking, and got to thinking about the SALT podcasts and TED talks.  These really are remarkable educational opportunities — really smart people, who are also really good at communicating their ideas to a lay audience.  These are not necessarily front-line scientists.  Michael Pollan and Malcolm Gladwell, for example, are both journalists who focus on taking important ideas from science (and economics and…) and making them accessible.  Why is that uncommon? We have relatively few people who do this kind of thing, as opposed to all scientists or even all educators.  Is it because that combination of talents is so rare, or because there is little market, interest, or demand for it?

Seymour Papert once argued that educational curricula should be evaluated like art — don’t try to identify the best, but instead argue about how well this example expresses something, or how accessible another one is, or how another one leaves people thinking and talking for years later.  Compare curricula for how they reach and engage people, not for a measurable, numeric bottom line.  Wouldn’t it be great to have so many compelling CS1 curricula that we could have a CS1 “art gallery” and compare them along the lines Seymour described?

Let’s imagine that we wanted to have more education that was engaging, compelling, and explained things to people.  We’d have to re-organize how we teach and structure education.  In fact, that would go against the basic structuring mechanisms of universities.

When I was at the University of Michigan, there was a lot of excitement about the proposed increased connections between the School of Education and the School of Social Work.  At some places, like Northwestern University, these are housed in the same schools.  That makes sense because the goals of Social Work are very similar to the goals of Education — improved human development, meeting human potential, individual self-reliance, and so on.

However, if we grouped scholars in terms of methods, we would structure universities very differently.  I’ve always found it odd that Physics and Mechanical Engineering are in separate schools/colleges at most Universities, and the same with Chemistry and Chemical Engineering.  Aren’t these really the same things, relying on the same theories, doing similar experiments?  Instead, we group by outcomes.  Civil, Chemical, and Mechanical Engineering are all about applying science to solve problems for people, at a large scale (by creating bridges and buildings, chemical plants, manufacturing capacity).  Never mind that what I see faculty in Chemistry and Chemical Engineering doing much more similar things than faculty in Civil Engineering and Chemical Engineering.

If we did group by methods rather than outcomes, what disciplines would be the natural collaborators for Education?  What disciplines would lead us to think about how we do things, so that we could create the kind of curriculum-as-art that Seymour described?

  • Journalism, which also cares about methods for finding “truth,” for conveying that to people in ways that are understandable and compelling, and for structuring the story so that the punchline is up front, and the greater detail is at the end.
  • Theater, because lecture is a kind of performance. Experimental Theater does a better job of getting the audience interacting with the performance than do most lectures!
  • Medicine, which is (much more than Education) about meeting individual needs and figuring out how to tailor broad approaches to health for the individual’s particular combination of strengths and illnesses.
  • Film and Television Studies, which know a lot about using multiple media for creating a compelling story.  Everyone who does On-Line/Distance Education should take a Film Class, to figure out how you package a compelling story/experience for others whom you never see.
  • Theme Park Designers (yeah, I know it’s not an academic discipline, but maybe it should be).  I’m a big Disney Imagineering fan.  Imagineers know how to draw you into the ride with the prestory, setting expectations and explaining the context, and then giving you an experience that you talk about and remember later.
  • Economics, because in the end, most Educational decisions are economic ones.  We know how to get two-sigma improvements in learning — give everyone a personal tutor.  That’s too expensive to do at scale.  Everything else we do is a step down from that, and if we knew how economists think about these trade-offs, it might help us in Education recognize our trade-offs and where we’re making them.
  • Psychology, because Education is just Psychology Engineering.  If in a methods-oriented University we lump Chemistry and Chemical Engineering together, we certainly should put the Psychologists and the Education faculty in the same building.

Okay, I’ll get back to my Faculty Summit talk preparation now, but I’m thinking about how the quality of education should be as much about the student’s experience as about the student’s performance on the test.

July 10, 2009 at 11:00 am 2 comments


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