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I support this and find it really cool. However, I'd love to see less hero worship and more evidence. On its face there is nothing wrong with all those Alan Kay photos, but my feeling is that it's symptomatic of how much of what's being pursued rests on appeal to authority and/or nostalgia.

To make this more concrete. Consider one of their projects (http://harc.ycr.org/project/), the Block-based programming: what's the evidence that this is a superior way for learning programming? What's the evidence that so-called computational thinking enhances cognitive ability or is transferrable to day-to-day thinking?

Furthermore, much of their computer-based education ideas are based on Seymour Papert's research and ideas which in turn was based on Piaget's theories on mental development. Those theories, however, have been thoroughly challenged and is all but outdated.

EDIT: this was the top comment and actively upvoted, now it seems that the mods have placed it at the end just before comments with negative points. I had heard of YC's sensitivity towards any criticism but this seems extreme. Whats the point discussions without criticism.



Several years ago I gave a talk at HAR2009 about my work applying Constructionist Education ideas to SimCity, which explains how I collaborated with the OLPC project to open up and publish the SimCity source code as free software, and translate Papert's and Kay's philosophy into concrete goals and features:

HAR 2009 Lightning Talk Transcript: Constructionist Educational Open Source SimCity, by Don Hopkins.

http://micropolisonline.com/static/documentation/HAR2009Tran...

Chaim Gingold, who also works at HARC, discussed my work open sourcing SimCity and his own work analyzing and using the source code to teach game design, in his PhD thesis on Play Design:

Open Sourcing SimCity - excerpt from Chaim Gingold’s PhD dissertation on Play Design, University of California Santa Cruz, June 2016.

https://docs.google.com/document/d/1DNAvqvKsuLGih8dWz9feEjea...

Abstract: http://pqdtopen.proquest.com/doc/1806122688.html?FMT=ABS

PDF Viewer: http://pqdtopen.proquest.com/doc/1806122688.html?FMT=AI


Got links for crits of Papert / Piaget and modern alternatives? Constructivism at least appears to be live and kicking in the MIT Media Lab hype world

Edit: also on computational thinking, I'm not sure that's what people are arguing for http://worrydream.com/MeanwhileAtCodeOrg/


The main failures of Piaget's work is that it assumes a smooth progression in reasoning facilities with age and secondly, that its notion of formal operations rests too much on deductive logic. But humans do not really reason logically: affirming the consequent and denying the antecedent are fallacies often encountered. However, as the 19th century logician Peirce once stated, Not the smallest advance can be made in knowledge beyond the stage of vacant staring, without making an abduction at every step.

A famous counter-example is an abstract selection task which adults fail with high probability. Yet, when a structurally identical set of rules are given to ~9 years olds but couched in the language of permission, the children are able to pass with high probability. Stating the rules in terms of what the individual has experience with (or altering the linguistic phrasing) significantly increases the probability of solving much more than adjusting the age. So we have that on one hand, people develop capacities sooner (and more unevenly) than his theory supposed and that on another, some stages of reasoning aren't ever reached.

amasad is wrong to imply that the field has not progressed beyond the ideas of Piaget. Although, people do often get the important parts of Papert's ideas wrong by focusing too much on the computer part of computer-based learning. The computer should be a means to an end, a tool to help the learner explore more possibilities, make the abstract more graspable and amplify one's ability to ask better questions.


Even if we assume that all of Piaget’s theories about developmental timelines are bunk, how does that invalidate the concept of teaching constructively in a child-centered, problem-centered way? Those seem like mostly orthogonal concerns.

As for block-based programming: that seems like something we can test empirically, and indeed there’s quite a bit of literature about it (which I have not read and am not familiar with, sorry).


I was directly replying to the asked question. But, it is not just the developmental timeline that was off. There's also its hypothesis of what children learn and how they reason or what they are capable of that is inaccurate.

Child centered, problem centered is vague. More practically, the big things are: you want material that's novel to the learner but also somewhat familiar (this is true, regardless of age). Children's attention is more distributed and worse at blocking out irrelevancies. Therefore, more complex tasks (such as math) should be presented in a way such that the signal meant to be learned can be extracted with minimal ambiguity (less extraneous information in presentation). Few other things have replicated.


Thanks for your replies, which intuitively make sense and appear to come from a knowledgeable background. As in my question I would really like to read the peer-reviewed / field leading work that you're basing your statements on, same as the comment I replied to. Or even just names of people / labs / journals to search.


Yes, please do provide some citations. This is interesting stuff.


I would need to know what the actual task is, but isn't that obvious? If I ask adults "What's 2+2" in a language they don't understand and I ask the same question to children in their native language, the children will look smarter than the adults.


It's nothing at all like that. I already mentioned the Selection task above, it's a very googleable term. It's old and there is yet no theory fully explaining why people fail at it as they do. Pragmatic reasoning schemas are the nearest attempt at an explanation. https://en.wikipedia.org/wiki/Wason_selection_task


by serendipity I clicked through on this link and sgentle's link to Kay on McLuhan and the following sentence comes remarkably close to my experience of the two presentations of the Selection task:

> .. the most important thing about any communications medium is that message receipt is really message recovery: anyone who wishes to receive a message embedded in a medium must first have internalized the medium so it can be “subtracted” out to leave the message behind.

(a tangent, but perhaps interesting)


Thanks for the Peirce reference. Would you recommend any books/papers/videos as introduction to his work?


but looking at just one of their projects is antithetical to harc

from Götz' writeup:

> Simply building prototypes with prototypes would not be a smart recipe for radical engineering: once in use, prototypes tend to break; thus, a toolset of prototypes would not be a very useful toolset for developing further prototypes. Bootstrapping as a process can thus only work if we assume that it is a larger process in which “tools and techniques” are developing with social structures and local knowledge over longer periods of time.

a lot of the ideas, or prototypes, in harc are half finished and or completely abandoned

sometimes an implementation's best contribution is the ancillary knowledge gained by attempting or developing

also, i think kay's presence is less 'hero worship' and more a reminder of shared goals(o) as well as a default standin

Götz's first contribution to a project in the space was to create an animation using cutouts from multiple copies of a picture of kay that were lying around

would you call lenna 'hero worship'?(i)

(o) https://www.youtube.com/watch?v=ubaX1Smg6pY

(i) https://en.wikipedia.org/wiki/Lenna


Prototypes increase understanding and discovery without an undo burden on making something operational. The parent comment strikes me as a, "do you even".

Is it hero worship or having a wise, hardened bad-ass on the team?


Yeah this is spot on. The point of this kind of research is to discover how to frame the problem (we don't really know what it is yet) and create new contexts for thinking about computing. Under the lens of the current open problems in computing, their approach may seem odd, different, not grounded in evidence, etc. But like good art, good, foundational research provides new ways to think about the field entirely.




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