This is because feedback loops which are too short for the overall system makes people focus on inappropriate intermediate goals. It’s the main cause of catastrophic long term strategic mistakes. This is also why people tend to flit around from field to field. As soon as they exhaust the easy gains, they look for a learner’s high elsewhere. This feeds their addiction, but doesn’t lead to learning any useful skills. The more accurate and more rapid the loop, the more quickly you’ll arrive at the top of the hill — and the less chance you have of leaving it to climb the mountains of mastery. Process improvement happens by creating many parallel processes and discarding the ones that are unfit, not by iteratively improving a single process.
You are learning Haskell right now (or anything you want really)
So I have come to the conclusion that the only thing that works is time and repetition, and that may seem daunting, but guess what? Time is passing. You’re learning Haskell right now. Or anything else you want to, for that matter.
I typically engage students in this model by asking them to draw their own Comfort/Chaos Circle. This is a great activity to get students to check with themselves and communicate where they are with me.
When we evaluate operators to partner with, I'm always trying to understand if they have a yet mindset. Are they intimidated or invigorated by the challenge of doing things for the first time? Does not knowing how to do something lead them towards action or inaction? Are they quick to acknowledge when they need to ask for help and leverage others around them, or do they turn inwards and shut down? None of us are perfect at this, but there are certainly people who are more inclined to meet new challenges head on, not just because it is the best option, but because it is the only option.
And it’s here where I made the crucial mistake – I prioritized winning over improving. do I do something that’s uncomfortable that will eventually push me to be better? Or do I prioritize winning right now, even if it doesn’t help me later? I chose the latter, to my detriment. It’s strange to say it, but for me, it’s far more comfortable being uncomfortable, than it is to be content on a seemingly endless plateau.
I am not convinced as Andy suggests that reading retention and note-taking are fundamental skills of knowledge work. What's more I have a suspicion that many knowledge workers over-rely on the act of collecting notes. Too much note taking is pernicious: it feels like doing something, while also giving you an excuse to endlessly delay putting forth your own thoughts until you have all the pieces. Rather than collecting and storing thoughts, the deliberate practice of knowledge, the expression of creativity that comes from play, necessitates sharing nascent and feeble ideas.
When you feel like you’ve learned whatever there is to learn from what you’re doing, it’s time to change course and find something new to learn so that you can move forward. You can’t be content with mastery; you have to push yourself to become a student again. So, perhaps, instead of asking that dreaded question, “What next?” turn it into this question: “What do you want to learn?”
This is "GORUCO 2014 - Samantha John, Jason Brennan - Designing a better Programmer Community" by Gotham Ruby Conference on Vimeo, the home for high quality…
In some sense, that’s all programming really is, modeling a domain in a way that can be leveraged by a digital computer. and without being willing to invest the time and money into education, smart, diligent people will still fail to grasp the concepts, and they will likely be wholly uninterested in them. programming, like any other field, is not always about what comes easiest: sometimes it’s important to sit down and study for a while to grok a particularly complicated concept, and other times, it’s simply important to learn by trying, failing, and asking questions.
“Physical fitness and brain performance are tied together, and it shouldn't be a surprise that grandmasters are out there trying to look like soccer players,” Ashley says.
Why there is no Hitchhiker’s Guide to Mathematics for Programmers
Unfortunately this sentiment is mirrored among most programmers who claim to be interested in mathematics. Mathematics is fascinating and useful and doing it makes you smarter and better at problem solving. But a lot of programmers think they want to do mathematics, and they either don’t know what “doing mathematics” means, or they don’t really mean they want to do mathematics. Honestly, it sounds ridiculously obvious to say it directly like this, but the fact remains that people feel like they can understand the content of mathematics without being able to write or read proofs. So read on, and welcome to the community. I honestly do believe that the struggle and confusion builds mathematical character, just as the arduous bug-hunt builds programming character. I’m talking, of course, about the four basics: direct implication, proof by contradiction, contrapositive, and induction. These are the loops, if statements, pointers, and structs of rigorous argument, and there is simply no way to understand the mathematics without a native fluency in this language. And so it stands for mathematics: without others doing mathematics with you, its very hard to identify your issues and see how to fix them. And finally, find others who are interested in seriously learning some mathematics, and work on exercises (perhaps a weekly set) with them.
Ultralearning, in my opinion, often works well because it compresses the frustration barrier to a shorter period of time. Whenever we, as human beings, sense a comparative disadvantage, it’s as if our brain immediately tries to avoid practicing the skill. One-on-one tutoring immediately removes the “I’m the worst in the class” feeling. It also removes the “I’m the best in the class” laziness that can afflict high-performing students. Woah, hadn’t thought of it this way. À la the more “single-player games” tendency I’ve been leaning into.
The Haskell Pyramid This is the Haskell Pyramid The triangle shape represents the knowledge you may learn about Haskell: wide at the bottom, and acute at the top. The pyramid is tall, heavy, and intimidating.
listening to a podcast at a multiple of its intended speed goes against the grain of the medium, which is better suited to soothe, comfort, entertain, or saturate the environment than to impart knowledge. In this sense, using computers makes us act more like computers.
When we’re unable to answer a question, it tells us we need to return to the material to review or relearn it. In a sense, this is a sort of reality reconciliation akin to checkins, therapy, OmniFocus Reviews, and the like. The “Study Deck” item in the Tools menu allows you to quickly switch to a deck with the keyboard. You can trigger it with the `/` key. When opened, it will display all of your decks and show a filter area at the top. As you type characters, Anki will display only decks matching the characters you type. You can add a space to separate multiple search terms, and Anki will show only decks that match all the terms.
Everything is different now, but I am still at my desk. Except with the websites. They separate themselves from the others, because I don’t feel much better at making them after 20 years. My knowledge and skills develop a bit, then things change, and half of what I know becomes dead weight. This hardly happens with any of the other work I do. I don’t bring this up to imply that the young are dumb or that the inexperienced are inept—of course they’re not. But remember: if you stick around in the industry long enough, you’ll get to feel all three situations. Experience, on the other hand, creates two distinct struggles: the first is to identify and unlearn what is no longer necessary (that’s work, too). The second is to remain open-minded, patient, and willing to engage with what’s new, even if it resembles a new take on something you decided against a long time ago. This situation is annoying to me, because my thoughts turn to that young designer I mentioned at the start of my talk. How many opportunities did I have to reproduce what I saw by having legible examples in front of me? And how detrimental is it to have that kind of information obfuscated for her? Before, the websites could explain themselves; now, someone needs to walk you through it.
Using spaced repetition systems to see through a piece of mathematics
You might suppose a great mathematician such as Kolmogorov would be writing about some very complicated piece of mathematics, but his subject was the humble equals sign: what made it a good piece of notation, and what its deficiencies were. even great mathematicians – perhaps, especially, great mathematicians – thought it worth their time to engage in such deepening. I’m still developing the heuristic, and my articulation will therefore be somewhat stumbling. Every piece should become a comfortable part of your mental furniture, ideally something you start to really feel. That means understanding every idea in multiple ways, People inexperienced at mathematics sometimes memorize proofs as linear lists of statements. A more useful way is to think of proofs is as interconnected networks of simple observations. For someone who has done a lot of linear algebra these are very natural observations to make, and questions to ask. But I’m not sure they would be so natural for everyone. The ability to ask the “right” questions – insight-generating questions – is a limiting part of this whole process, and requires some experience. Conventional words or other signs have to be sought for laboriously only in a secondary stage, when the mentioned associative play is sufficiently established and can be reproduced at will. So, my informal pop-psychology explanation is that when I’m doing mathematics really well, in the deeply internalized state I described earlier, I’m mostly using such higher-level chunks, and that’s why it no longer seems symbolic or verbal or even visual. I’m not entirely conscious of what’s going on – it’s more a sense of just playing around a lot with the various objects, trying things out, trying to find unexpected connections. But, presumably, what’s underlying the process is these chunked patterns.
“The fact that you can fool yourself, for the most part, into thinking that you have done something really valuable with your time is really dangerous.”
Teaching potential via examples versus learning curve
“@jckarter @kylebshr I’d caution against judging any language’s teaching potential via toy examples of string manipulation that never happen in real life. More important is how the learning curve progresses into day 2, day 20, day 200.”
