Week 1: July 12th- Preface + IntroWeek 2: July 19th – Chapter 1 + 2Week 3: July 26th – Chapter 3 + 4Week 4: August 2nd – Chapter 5 + 6Week 5: August 9th – Chapter 7 + 8
Sharon De La Cruz Hero keyboard app for mobile phones

2. YES! Not taking for granted PROCESS
3. American history tends to be that. What is “American”-----whose America?

4. ----frustration, how do you unlearn even me creating a project for this week was frustrating.
comics as an instructional tool . "Secret Coders", Jody Colkin
HEY ALL - Our usual link for the video call is broken so please use this one instead:
Aatish BhatiaERES BOBO1. The US not being on the metric system is ,an example of QWERTY thinking. This has a ton of everyday consequences that make life more expensive & complicated for people. For one thing, science is done in metric (for good reasons.. metric was created to standardize units & connect them to things in nature you can measure) and students who aren't familiar with these units are at a bit of a disadvantage.
2. One coding concept that influenced me a lot was recursion. I remember being amazed at how it could solve problems that seemed so complicated like the Towers of Hanoi puzzle, by realizing that a big problem has a smaller problem contained within it, and the smaller problem a smaller one, and so on. Around the same time, I was learning about induction in math (a proof techinque that relies on recursively breaking a big problem into smaller steps) and so this was a new way of thinking about problems for me that felt empowering.
3. A lot of my school education didn't fit this criteria. E.g. it was very memorization heavy and the reason you had to memorize things were that somebody else had decided that you should know them (and we all knew the real reason was that it was easy to test). Playing with Lego Mindstorms robotics kit (which was strongly influenced by Papert) was an educational experience that did. I learned to program in C because I could use it to make my robot do stuff that it couldn't otherwise.
4. Ch. 1 taps into importance of diverse creators / educators, Ch. 2 taps into growth vs. fixed mindset
5. The towers of hanoi puzzle is
a great way to be introducted to recursion! In solving it you learn how to take a big problem and break it down into slightly smaller problems in an interative way. Learning to solve a Rubik's Cube can be a great way to grapple with an idea in group theory called commutators, which is when A*B is not the same as B*A. (e.g. putting on your socks and then your shoes is not the same as putting on your shoes and then your socks, so these things don't 'commute'. The same is true for most Rubik's cube moves.)
6. Nim is an example of a simple game you can play as a kid. It turns out that there's an optimal strategy where the 1st player will always lose, and learning this winning strategy involves learning about binary numbers. So the need for binary numbers comes up in a natural way.
1. In learning how to roll a kayak, you have to first learn a move called the 'hip snap'. I've noticed that kayaking & learning to roll seem to come more easily to people with dance experience, I think this is because they have prior body knowledge about staying loose, separating upper & lower body movements, swaying hips, etc..
2. For the third kind of knowledge, I think the answer to 'why do we need to know this?' is often unsatisfying to students. See also:
3. Having to memorize a lot of information was a barrier for me to fall in love with many subjects in school.
5. When learning to roll a kayak, there are tons of stumbling blocks you can run into. I read a great book that used a debugging philosophy, spelling out each of the different components of a roll, listing the commone ways that people mess them up, and how to fix it. I found this very helpful in learning to roll, and it helped me iron out my bugs."how we think about our knowledge affects how we think about ourselves [..] Our image of knowledge as divided up into different kinds leads us to a view of people as divided up according to what their aptitudes are." (pg 171).

For me this has been one of the strongest messages of the book. Our earliest exposures to a subject in school and our first impressions can leave a life-long impression by causing us to categorize ourselves into math-people or art-people or theater-people or whatever. And tying a particular subculture to our identity usualy means that we also actively deny our ability to thrive in another subculture (hence the art vs science divide). This relates to a couple of other things I've read.

1. Carol Dweck's work on growth mindset shows that the metaphors that we use when we think about learning (e.g. the math brain is a muscle that you can grow (growth mindset) vs. the everyone is alloted a certain aptitude for math at birth (fixed mindset)) affects how people perform in subjects, and that adopting a growth minset can help people learn things they otherwise would not have assumed they were able to. This relates to Papert's example in an earlier example of how many of us think we can't juggle because we identify ourselves as clumsy or lacking in hand-eye coordination, whereas if we focus on the process of acquiring a skill rather than on a self-reinforcing identity, it's possible to get better at it.

2. I was reading a paper ( on how metaphors shape our ability to reason. It lists some interesting examples on how the metaphors that people use to describe a phenomenon shape their attitude and behavior about that phenomenon. One example is that if crime is described using the metaphor of a virus, people are more likely to support treating crime through social reform (i.e. diagnose and treat it like a disease), whereas if it's described using the metaphor of a 'beast', people are likelier to support enforcement options like more prisons and policing (i.e. to hunt and cage the aggressor).

3. The modern creative coding movement is a great way to bridge science with art by showing that they can both inform each other in the process of making something delightful.

Going back to the book, I think 'objects to think with' are essentially metaphors that help us make abstract ideas more concrete. The turtle is one such metaphor. I think a big part of what makes Processing so popular is that it's based on a 'flip book' metaphor of programming. If we come up with more interesting and relatable metaphors for computing (or any abstract topic), more people will be able to relate to it. And, as Papert argues in the last chapter, we might also end up understanding the subject more deeply in the process.


In thinking about how we could adapt the samba school model of learning to teaching topics like programming, one approach I've recenty come across and have found fascinating is starting with something more hands-on and tactile like crafts and linking it to programming. This works particularly well for situations where the craft is a kind of computational object or artifact, i.e. a form of craft to which computation ideas can be applied. eg. Natalie Freed taught a workshop on how bookbinding can lead you into graph theory or this post on creating Adinkra stamps with Scratch or this on 'crafting with code'
Patrick Ester
Elizabeth Waters1) As a child I had clay that came in 3 colors, I religiously kept them pure but used them in combination to recreate the tools I saw my parents use as well as invent new places, buildings and people for fantasty play

1. How to feel words:

2. Teaching children about their body, especially their brain, suffers from “school knowledge” which is experienced as the information not being presented in an interesting and deep enough manner to satisfy children interested in their changing bodies. In part due to assumptions of “proto knowledge” like we all are currently using a body and brain so we must understand something about it. Education could go further to personalize knowledge through addressing cultural differences in students, exploring the social and historical drivers of misconceptions, and helping students develop their own algorithms for growing, learning and staying healthy.
Liam Baum A lot of my thoughts for these questions revolved around studying Jazz in college. I think improvisation can be an abstract idea to a lot of people, even trained musicians so I built a project that "improvises" chord tones over a common jazz chord progression using random numbers and shows a visual of the chord tone being played over which chord. There are still some bugs as working with specifc increments of time and random numbers is tricky in p5 but it is close enough to share. I bit off way more than I could chew trying to make a juggling algorithim. The LOGO example from the book made it seem so easy :/ This is as far as I got before getting fed up and moved on to some other projects. I'm sure if I had more free time I could focus on making it working but working on it consistently became a set back for moving forward on other things (including reading more chapters for this book). Oh well. All part of the learning process.
Lucas Viana1) Lego, Scratch (Papert's turtles!), paper and pencil, circuits and gears. I think of 'toys to think with' as objects that instigate curiosity through allowing the build of complex mechanisms from simple units, and at the same time working as models for understanding other subjects and phenomenon of our world.
2) Papert thinks of learning in "Piagetian" terms. She talks about creating an environment where learning is natural and constructive, so the student performs an 'active' position in the process, instead of the conventional 'passive' way of absorving information.
4) In elementary school, I remember of being presented to some concepts in math through the use of 'Material Dourado'. It was a set of little cubes that could be arranged in different ways in space, what brought me a spatial sense about operations such as multiplication, division and exponentiation. In 'Mathland', mathematics should be viewed as a language for expressing logic, and a fluent environment would induce learning not only by influence, but by revealing the beauty and joy that can be constructed and expressed through it.
1. stereotypes
2. Son of two computer scientists and growing up under the influence of the information age, my learning of programming languages happened in a very natural way. Therefore, despite being hard to identify changes, along my reading of the chapters I could see the presence of many aspects, presented by Papert as results of the learning of programming, in my personality. Some Scratch projects I made when I was 10 (6 years ago):
Sorry, struggling to keep up with the reading but school and scientific olympiads are making me very busy the last few weeks. Hope I'll be able to finish the book later and answer these questions. Also, as I told Sharon, I wouldn't be able to join any live conferences as I have classes on wednesday afternoon - an exhausting example of the fauty education system we have here. Good reading everyone, and greetings from Brazil! Very sorry to not have the opportunity to meet you :(
Vandana BajajPenis :)1.
2. Learning to code definitely changed the way I started thinking about other things. I think I became more 'procedural' in the way I thought about other things in day-to-day life, even if only slightly. I also believe that it helped in driving my interest in linguistics, the field I turned to after college was over. It definitely gave me an immedate affinity to formal semantics when I learned that it was based on many similar principles.
3. Sadly, I think my own experience of learning programming may have not fit these criteria. I recall having to code things that at the time felt so far from anything that could be relevant or important. I remember having to make tiny programs to calculate body mass index, convert Fahrenheit to Celsius, etc., and not feeling particularly empowered through the experiences.
4. Papert argues for the ease of children learning artificial languages (programming) by connecting it to what we know about child language acquisition for natural language. I wonder if Papert then thinks that there is a similar “critical period” for learning programming well as there is believed to be for becoming a native speaker of a spoken language. Furthermore, does he believe that it becomes increasingly more difficult for someone to become well-versed in programming in adulthood? Pushing this idea further, does Papert suppose that there is an innate component to the child’s capacity to learn programming as some linguists believe there is for the child’s capacity to learn a natural language? A second item from the chapters that jumped out to me was the portion or two where Papert describes his thoughts about how the current classroom model of teaching does not work well for trying to learn certain skills, one being programming. This is a provocative argument, but one that was interesting food for thought.
5. I’m not sure how different of an example this is from what Papert already spells out, but what immediately comes to my mind is a toy I very recently purchased for a three-year-old. It’s called a “Code-A-Pillar”, marketed as appropriate for kids aged 3 to 6, and intends to get them to understand relative directions (left, right, straight forward, etc.) by providing a caterpillar head plus multiple detachable segments. Each segment is marked with an arrow indicating the direction, and the expectation is that the child will spend time detaching and attaching the segments in different orders, turning the caterpillar on, and then seeing what the resulting path it takes is, and how it differs from when the segments are reordered.
6. Having a child play around with tossing a coin might help them understand probabilities.
3. I remember in high school, sadly, not being able to fall in love with physics. The majority of the examples my teacher used in class and on exams had to do with football and other sports, and these were things I actually did not have any interest or knowledge of at all.
5. Coincidentally, I also learned to juggle at some point. I do remember it taking at least a number of weeks for me to learn to cascade juggle three balls. While I don't believe I used the type of computational approach described by Papert, I do remember that the method I employed (which was described in the book I consulted at the time) involved learning to toss one ball with a good form, before moving to two, and then finally juggling three. I have found, though, that the art forms I have started engaging more with in adulthood -- dancing and playing musical instruments -- have seemed to become more easier by a computational sort of approach -- or, I have enjoyed the learning process more because I now am likely to automatically find something like a computational approach, thereby making the activity appeal to my other interests. While I do feel that these physical activities are perhaps a bit easier with a computational approach, there is still an 'art' to these skills that is difficult to directly map to a step in the computational process
Holden Lee1. English as international language (irregular grammar and phonetics makes it difficult to learn), as opposed to a language designed to be easy to learn (like Esperanto). E-libraries maintained as traditional libraries (with limited copies of books). One way to push back is to design complete (toy) examples of an alternate way of doing things. For example, we could simply copy video games into a virtual reality environment, or we can explore fundamentally different experiences that virtual allows. Vi Hart has done many such projects (
2. When something is repeated, find a system to do it, freeing up attention. Be in the habit of writing down unambiguous procedures to do things, for communicating to other people or to yourself when you forget.
3. No: A writing class where I felt there wasn't transparent discussion on what good writing was, and where I had a hard time appreciating the assigned readings. Yes: A class on improv poetry which was a comfortable environment to try and fail, and it was shown as something that anyone could do anytime.
4. How do you teach someone to play in an intellectually interesting way, rather than e.g. in a repetitive way? Esp. with just a computer program?
5. group theory -> Rubik's cube
3. I liked programming only after I learned functional programming - it made sense mathematically and was elegant. Before I had thought about programming as boring/rote.
Alice Tang1. Sorry will finish this up later
2. Coding definitely causes me to think more about efficiency and about the delegation of tasks that may be better performed by a computer program. Namely, computers are amazing at rapid iteration. In one instance, analysis of biological data has increasingly come to rely on computational methods. However, input data were not always recorded in ways amenable to computational parsing and thus computational research. Thus, we must consider how we generate and record data, for there exists some divide between human and computer-readability. I also remember an early instance of this occuring while I was completing my calculus homework (we were learning about Euler's method). We had to do about 10 problems in which we were to manually crunch out the intermediate answers that build up to the final solution. After about three problems, I grew exceedingly bored (oops) while feeling that I had sufficient understanding of the topic. Thus, I wrote a computer program to generate answers for me. (And I'd like to think this helped me internalize the concepts in new ways as well.)
3. Relating what Papert says about combinatorial thinking
I think we should question our classification systems – why do we classify the way we do and how do our methods speak to our societies are constructed
What are the underlying assumptions
Walter Ong – Orality
Also just generally a lot of works from media theory go hand-in-hand with ideas Papert discusses (he even cites McCluhan directly.
4. Optical illusions: It is difficult to understand and grasp that which we do not yet even know, to understand beyond that offered by our perceptions. For one, it is hard for us to understand the limits of our perceptive capacities. For instance, we are told of "impossible colors," but how do we even begin to imagine what they look like. Optical illusions essentially take the limits of our perception and throws them at our faces.
6. Elon needs to put down his Kurzweil and pick up some Kafka. It's nice to hear him acknowledge that tech isn't an unalloyed good, but the immediate threat of AI isn't so much machine uprising as it is machine-assisted oppression. We can't build the utopias of tomorrow if the societies of today are crushed by algorithm-assisted dystopian impulses.
The immediate examples I cited were state oppression, but there are so many other wonderful ways AI can and has amplified the trends he noted, from black-box sentencing algorithms and crime predictions to subtle algorithmic influences on the culture and media we're exposed to, shaping our worldview, taste, and even mood in ways we're often unaware of

Other commends: some underlying currents of thought:
Building intuition
Eliza Struthers-Jobin
Lawrence Barriner II
Guillaume Pelletier-Auger
Jonathan Bimberberran exquisite handcraft crafter