[SamBam]

As a science teacher and former software dev, I find this totally cute, and I understand exactly why the creator chose to make it a physical card game.

That said, I do think the translation into a physical card game means that kids aren't getting the experimentation and near-instant feedback that they'd be getting if they were doing this digitally.

In order for a kid to "win," they either have to already know, or explicitly be told using words, what all of the commands do. Then they have to hear the parent analyze their solution, and tell them where they went wrong. Picture, however, a different game, played online: A kid has no idea what "sort" does, but when they link the "sort" command to a blob of text, all the lines are sorted in order. Now no one has told them what this command does, but they've discovered it. By playing the role of a scientist discovering these commands, they might actually gain an intuitive understanding of them.

I'm thinking of the board game "robot turtle," where kids needed to create a "program" of commands to move a turtle to a goal. When they did that, they had near-instantaneous feedback: the parent moved the turtle. If the kid mixed up their left with the robot's left, the failure was obvious. But if the game has been re-made so that there was no board, and the parent and kid just needed to talk about whether the turtle would actually end up seven paces forward and three paces to the left -- i.e. doing it all verbally -- it wouldn't have been nearly as powerful.

So I'm not raining on this, I can see this as very cool. But I am having a hard time imagining it's the best way to learn to pipe together commands.

[d-us-vb]

As a young Linux user I always hated the experimentation aspect because usually it meant just straight up getting the command wrong 5 times before trying to read the man page, thinking I understood what the man page meant, trying again another 5 times and then giving up.

This idea of experimenting and getting instant feedback is just survivorship bias for a certain type of person, not “the way we ought to teach Unix shell”

This view is corroborated by the research summarized and presented in the programmer’s brain by Felienne Hermans.

[robocat]

> usually it meant just straight up getting the command wrong 5 times before trying to read the man page, thinking I understood what the man page meant, trying again another 5 times

I think that is a developer's superpower. The poncy term for it is grit. I tell others that the secret to leaning computers is frustration and persistence.

> and then giving up.

Knowing when to stop or change direction is hard.

I've definitely wasted years of work failing to solve something that I eventually had to give up on (most memorably depending on nasty Microsoft products).

But I've also been paid very nicely because I've solved problems that others struggled with.

And I was paid for the failures too.

[bandrami]

I've been a sysadmin for a quarter century and I've always said my only real superpower is that I read error messages when they appear, something none of my non-admin coworkers can do, for some reason.

[TonyStr]

A smart, and by no means technically incompetent friend of mine struggled to get a software product to run. He would reinstall it, try different configuration, uninstall plugins, yet every time he tried running it, the program gave the same error message. I asked him to read the error, and it very simply stated that it was failing to create symlinks because the the disk was formatted with ExFAT. Had he just piped this message into ChatGPT, he would have avoided hours of debugging.

[benj111]

Do copy pasting them into Google count?

[bandrami]

Sure, about 3/4 of the time the answer is on the first page of results

[snowmobile]

I consider myself a fairly good developer, and I think that's in large part due to knowing, "doing this should be possible, and the reason it's not working right now is just due to stupidity (my own or the developer of whatever I'm using's)". But yes, in a few (thankfully rare) cases it just plain isn't practically possible. Even then, I've given up on problems just to have it nagging in the back of my mind and then randomly coming up with a beautifully simple solution weeks later. That's sort of the essence of what I like about programming (and math too).

[dspillett]

> the secret to leaning computers is frustration and persistence

And if persistence fails, bring out the big gun: belligerence.

[jama211]

Grit is something you gain once you already have an intrinsic motivation, such as already having a belief you can do this. Something has to spark in people that they’re capable in the first place.

[godelski]

People forget that struggling is part of the learning process. It's great that people want to make things easier to learn, but struggling is essential. You want to ensure that people don't struggle so much they get stuck (one extreme), but you don't want to make it so easy people don't struggle at all (the other extreme). There's balance, but that balance requires struggling.

[jama211]

I think this is one of those statements that sounds reasonable on the surface but if you read it over a few times it doesn’t say anything concrete enough to pin down anything that could be refuted, even though I think the vibe is off.

So in return I’ll share my vibe, which is that my point was a small amount of struggle can be good once people are already determined to learn something, perhaps because they have found a spark for it. But before they’ve found their spark, all it does is turn people off. And in general, I don’t think struggle is essential at all. In fact I’ve learned a great many things successfully without struggling.

[saulpw]

You must have a different brain than mine. I'm finding (and increasingly as I age), that the act of learning feels inherently uncomfortable. Like my brain really wants to use its existing toolset instead of learning something new, and is saying so quite loudly. A similar discomfort happens with exercise. If there's zero struggle to lift the weight, then your muscles aren't really developing. I think this is pretty well-known and well-documented.

So how do you learn without struggle? Are you being spoonfed the material on a learning happy path so you happen to never make a mistake and thereby have to redo your work? Do you not experience effort and mistakes and frustration as 'struggle'? After you're "done" learning a particular skill without struggle, what happens when you have to apply that skill at a higher level than you learned it at? Is it just joy and rainbows all the time?

[godelski]

  > I think that is a developer's superpower.

I do too, but only because we can do both.

I think comparing math education to programming education is quite apt here. After all, programming is math[0]. Both are extremely abstract subjects that require high amounts of precision. In fact, that's why we use those languages![1]

One of the absolute most difficult parts of math is that you don't have feedback. Proving you did things correctly is not automated. You can't run it and have an independent (not you) mechanism tell you that the output is what you expect it to be. This leads to lots of frustration as you sit there thinking very hard about what you've done wrong. It is frustrating because you're often blind to the mistakes as that's why you've made them in the first place! But the upside is that you quickly become attentive to details and learn those pitfalls very well. This also means you can abstract very well (the entire point of math) as you learn to abuse things on purpose. The struggle is real, but the struggle is important to the learning process. You learn very little if there's no struggle. Your mind is made to remember things that are hard better than things that are easy.

In programming we typically have the opposite problem. You get instant feedback. This makes iteration and solving your specific problem much faster. You can experiment and learn faster as you poke and prod seeing how the output changes. BUT there is a strong tendency to leverage this too much and use it to outsource your thinking and analysis. Iterating your way to success rather than struggling and analyzing. This doesn't result in as strong of neural pathways, so you don't remember as well and you don't generalize as well. Having taught programming I can tell you that countless students graduate from university[2] thinking that because the output of their program is correct that this means that their program is correct. This is a massive failure in logic. Much easier to see in math that just because 3+3=6 and 5+1=6 doesn't mean that the process is equivalent[3]. The correctness of the program is the correctness of the process, not the correctness of the output.

While that's the typical outcome of learning programming, it isn't a necessary outcome and there's nothing stopping anyone from also using the same approach we use in math. Math is only that way because we're forced to[4]! Both have their strengths and weaknesses, but neither is strictly better. The strictly better learning path is the combination and that is the superpower we have. It's just easy to abdicate this power and only do the easy thing.

[0] We can really say this from Church-Turing but if you really have concerns with this statement you'll need to read more up on the theory of computer science and I suggest starting with lambda calculus.

[1] https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...

[2] and even graduate degrees. You'll also see this idea prolific on HN and I'm sure someone will respond to this comment countering the point

[3] You can abstract this, I'm not going to do some long calculation here but I'm sure most people have done a long calculation where they got the right answer but the process was wrong and they had a professor still mark them wrong (and correctly so).

[4] If you're going to lean on me I'll concede

[nomadygnt]

Maybe I am wrong about this but I think a lot of recent research has shown that trial and error is a great way to learn almost everything. Even just making an educated guess, even if it is completely wrong, before learning something makes it much more likely that you remember and understand the thing that you learn. It’s a painful and time-consuming way to learn. But very effective.

Maybe Linux commands is a little different but I kinda doubt it. Errors and feedback are the way to learn, as long as you can endure the pain of getting to the correct result.

[cheesecakegood]

Needs qualification. Research shows trial and error learning is very durable, but it’s not the most time efficient (in fact it’s relatively poor, usually, on that front). The two concepts are a bit different. Yes, trial and error engages more of the brain and provides a degree of difficulty that can sometimes be helpful in making the concepts sticky, but well designed teaching coupled with meaningful and appropriately difficult retrieval and practice is better on most axes. When possible… good teaching often needs refinement. And you’d be surprised how many educators know very little about the neuroscience of learning!

[zahlman]

> And you’d be surprised how many educators know very little about the neuroscience of learning!

I'm (pleasantly) surprised every time I see evidence of one of them knowing anything about it.

[raddan]

At the university level in the US, few faculty get any kind of training before they are expected to start teaching. And the teaching requirement is more or less “do no harm.” If you’re at a research university, which includes many publicly funded universities, then your career trajectory is based almost exclusively on your research output. I could go on, but it suffices to say that it’s not surprising that the teaching could be better.

That said, most institutions have teacher training resources for faculty. I was fortunate to be able to work intensely with a mentor for a summer, and it improved my teaching dramatically. Still, teaching is hard. Students sometimes know—but often don’t know—what is best for their learning. It’s easy to conflate student satisfaction with teaching effectiveness. The former is definitely an important ingredient, but there’s a lot more to it, and a really effective teacher knows when to employ tools (eg quizzes) that students really do not like.

I am frequently amused by the thought that here we have a bunch of people who have paid tons of money, set aside a significant fraction of their time, and nominally want to learn a subject that they signed up for; and yet, they still won’t sit down and actually do the reading unless they are going to be quizzes on it.

[zahlman]

> the thought that here we have a bunch of people who have paid tons of money, set aside a significant fraction of their time, and nominally want to learn a subject that they signed up for; and yet, they still won’t sit down and actually do the reading unless they are going to be quizzes on it.

How often have they put down the money, as opposed to their parents?

How often do they actually care about learning the subject, as opposed to be able to credibly represent (e.g. to employers) that they have learned the subject?

How often is the nominally set-aside time actually an inconvenience? (Generally, they would either be at leisure or at the kind of unskilled work their parents would be disappointed by, right?) My recollection of university is that there was hardly any actual obligation to spend the time on anything specific aside from exams and midterms, as long as you were figuring out some way or other to do well enough on those.

[d-us-vb]

Trial and error is necessary and beneficial, but not after the student becomes frustrated or anxious/bewildered by the complexity. The research shows that striking a balance between teacher intervention and trial and error is the optimal approach. If a teacher notices that a student is way off course but they keep persisting in one branch of the trial-and-error search space, it’ll be best if they intervene and put the student on the right branch. The student can still use the knowledge of what wasn’t working to find the solution on the right branch, but just persisting would be ineffective.

Gaining true understanding/insight is necessarily trial and error. Teachers cannot teach insight. But they can present the optimal path to gain insight.

[JamesTRexx]

Trial and error was the root of what became my IT career. I became curious about what each executable did from DOS and with that did my first tweaking of autoexec.bat and config.sys to maximise memory. Years later I was the only one who could investigate network (and some other) problems in Windows via the command line while I was the junior of the team. Ended up being the driver of several new ways of working for the department and company.

[raddan]

Ditto. I found that people whose attitude was “let’s just try it” tended to be a lot more capable and effective. Nevertheless the prevailing wisdom when I was in IT was that if you had a problem that didn’t have an obvious solution, you had to purchase the solution.

[lotu]

Sounds very profitable for whoever is selling solutions, I wonder if perhaps they also provide wisdom as a loss leader.

[shakna]

I'd add nuance to Hermans' work. Its not all experiment blind, but also not feedback-less. They advocate for "direct instruction", not just rote learning.

> As that is not a surprise, since research keeps showing that direct instruction—explanation followed by a lot of focused practice—works well.

Note the "lot of focused practice".

[0] https://www.felienne.com/archives/6150

[raddan]

There’s a pretty rich literature around this style of pedagogy going back for decades and it is certainly not a new idea. My preferred formulation is Vygotsky’s “zone of proximal development” [1], which is the set of activities that a student can do with assistance from a teacher but not on their own. Keeping a student in the ZPD is pretty easy in a one-on-one setting, and can be done informally, but it is much harder when teaching a group of students (like a class). The. Latter requires a lot more planning, and often leans on tricks like “scaffolded” assignments that let the more advanced students zoom ahead while still providing support to students with a more rudimentary understanding.

Direct instruction sounds similar but in my reading I think the emphasis is more on small, clearly defined tasks. Clarity is always good, but I am not sure that I agree that smallness is. There are times, particularly when students are confused, that little steps are important. But it is also easy for students to lose sight of the goals when they are asked to do countless little steps. I largely tuned out during my elementary school years because class seemed to be entirely about pointless minutiae.

By contrast, project work is often highly motivational for students, especially when projects align with student interests. A good project keeps a student directly in their ZPD, because when they need your help, they ask. Lessons that normally need a lot of motivation to keep students interested just arise naturally.

[1] https://en.wikipedia.org/wiki/Zone_of_proximal_development

[vacuity]

I'd like to add that, while anything will have some learning friction, learning the Unix CLI is rather unnecessarily painful.

[trashb]

I actually feel like the Unix/Gnu CLI is quite nice (yes I'm used to it already). I feel like it provides a lot of consistency through community standardization and standardization through POSIX and libraries. For example it's quite difficult to find a program that breaks the "-o --option" long/short options and if you do the "man command" or "info command" pages will tell you how to use a program. In my experience this is quite different on for example Windows.

Learning it is a step but once you've learned the basics you can read 90% of the commands.

[raddan]

I’m curious: what do you see as unnecessary about the CLI? Or, to put it another way, in what way should the CLI be changed so that the only remaining difficulties are the necessary ones?

[vacuity]

I'm not qualified to give a complete answer, but I think two main issues are the proliferation of flags in standard tools (e.g. ls has a lot of flags for sorting behavior) and the extreme preference for plain text. Text is very useful, but a lot of semantic information gets discarded. Representing structured data is painful, stdin/stdout/stderr are all in one place, window resizing makes a mess sometimes (even "write at end of line" isn't given), and so on. I'm definitely not qualified to describe just how to fix these issues, though.

[raddan]

I think you hit the nail on the head. Plaintext is universal in a way that nothing else really is. Outputting structured data means that consumers would have to process structured data. That definitely raises the difficulty of the programming. It’s not an easy problem, but I also do not have any good ideas.

[inopinatus]

I'm trying to remember being a young Unix user but it was four decades ago, so the details become hazy. Nevertheless the proper go-to after the manpage fails to clarify matters is the same as it ever was, that is, one reads the source code, if you have it, and this is easier today than ever.

[pmontra]

Getting a pipeline wrong 5 times is common. The normal process is: write a couple of steps, right output! Add a grep, bad output! Fix it, again, again, right output! Add cut -bM-N, adjust the boundaries a few times. Sort the output. Oops, sort -n

[jackdoe]

> But I am having a hard time imagining it's the best way to learn to pipe together commands.

To be honest, it is very strange how hard it is to teach programming concepts, for some reason almost all humans use computers but only 0.1% or so can program them.

I am not sure we have the 'best way' to teach anything computer related.

People develop world model for physics quite early, they know they can pull with a rope but cant push with a rope.

And they get intuition, things that are thrown up, go down, and they can transfer this intuition in the math, because math is real.

For some reason its hard to do that with code. People keep trying to push with a rope, even after studying for many years.

PS: I am trying to teach her neural networks now and am working on this RNN board game https://punkx.org/projekt0/book/part2/rnn.html to fight the "square" dragon. I want her to develop good world model for neural networks, so that she understands what chatgpt is. I just keep experimenting, sometimes things click, sometimes not.

[bc569a80a344f9c]

> almost all humans use computers but only 0.1% or so can program them.

This is nitpicking but I was curious: there are 4.4 million software developers in the US (https://www.griddynamics.com/blog/number-software-developers...). The population is 340 million, 0.1% would be 340,000. You’re off by over one order of magnitude.

[jackdoe]

there are 45 million devs in the world (out of which probably 10 can actually program) and 8.5 billion people

we could say 0.5%?

[antonvs]

It’s misleading to use the entire world’s population. A very large proportion of that hasn’t ever had the opportunity to learn to write code.

[smj-edison]

> I am not sure we have the 'best way' to teach anything computer related.

Not saying this is the best way, but have you followed any of Bret Victor's work with dynamicland[1]?

[1] https://dynamicland.org/

[jackdoe]

Yea, and I think it is amazing, but in the same time it will work for some and not for others

The same way scratch works for some, redstone for others, and https://strudel.cc/ for third

I think the truth is that we are more different than alike, and computers are quite strange.

I personally was professionally coding, and writing hundreds of lines of code per day for years, and now I look at this code and I can see that I was not just bad, I literally did not know what programming is.

Human code is an expression of the mind that thinks it. Some language allow us to better see into the author's mind, e.g forth and lisp, leak the most, c also leaks quite a lot e.g. reading antirez's code or https://justine.lol/lambda/, or phk or even k&r, go leaks the least I think.

Anyway, my point is, programming is quite personal, and many people have to find their own way.

PS: what I call programming is very distant from "professional software development"

[dr_kiszonka]

Amazing diagrams!

[derrida]

hey, I just copy and pasted your comment into an agent I hope you don't mind.

one shot result:

https://wonderful.exe.xyz

you could do the same, or I could give you access to this one if you want.

[empath75]

unreal that an agent knocked this out in one shot.

[derrida]

well, technically 2, my second was "good, now do it better"

[antonvs]

fyi, the dragging feature doesn’t work on iPad.

[d--b]

One could make an app that actually scans the cards from a distance and computes the stuff. Brett Victor style.

[dhosek]

I’m wondering whether it could be played with a Unix box connected to the big TV in the living room so that with each command added to the pipe you can see the result. That’s my instinct for what to do with this, although it does feel like it is a play once kind of game.

[williamcotton]

Would this be something along those lines?

https://github.com/williamcotton/guish

It's a GUI for constructing and executing Unix pipelines and it shows the output of each step in the pipeline.

[dhosek]

I’d been thinking more just typing the commands into a terminal window on the big screen, but something like this could be really helpful for seeing the intermediate steps.

[derrida]

woah that looks nice!