Ask HN: What's your learning strategy? What's your strategy for retaining knowledge from lectures, papers, textbooks, talks, etc? Specifically, 1) Do you take notes? 2) Do you compile/rewrite notes? 3) Does spaced repetition work for you? 4) Do you have a methodology for extracting common themes/patterns across topics? Thanks! |
This leads to then what I consider "foundational knowledge", or refining your understanding on Bloom's Remember, Understand, and Apply categories. I think we try too hard to push students toward the Analyze, Evaluate, and Create categories too quickly, which results in poorer performance, especially in the classroom context where the next course assumes "mastery" (another term I dislike, I prefer proficient). Once a student is proficient, then we can talk theory all day.
So, in my classrooms, I mirror the methodology I commonly see in martial arts - warm-up, demonstrate technique, drill the technique, and (depending on the art) spar, or apply the technique. If you are struggling at one of these steps, then we can identify the issues and provide intervention practice at the appropriate level. Traditional classrooms don't really allow for extended spaced repetition, but I do believe it helps form autonomy.
More specific to your question since most of the above is just my general opinions on learning:
- Notes are good and writing notes is better than copy-pasting them [1]
- Highlighting your notes for important details is a lower level practice that is also beneficial [2]
- If you are given a technique/algorithm, attempt to do it on additional practice problems. If you can, through spaced repetition. For example, if you were learning the A* Search algorithm, change the starting and goal nodes in your current examples or make a new one with randomized numbers.
- Chi's ICAP Framework has a few additional points as well on which lower level practices are better than others [3]. However, as I'm arguing in my dissertation, better overall may not be better for the individual. If a student is struggling in a Constructive activity, I'm arguing it may be better to 'downgrade' them to a lower-level activity to reinforce understanding (again, my thoughts toward foundational knowledge).
[1] https://dl.acm.org/doi/pdf/10.1145/1240624.1240773
[2] https://www.sciencedirect.com/science/article/abs/pii/036147...
This is a great view. To add to this from a learner's perspective, though I'm not a professional educator (thanks for sharing your perspective as one): I've found that the ideas about worrying about "perfect practice" to be intimidating, especially as I've struggled with a 'perfectionist' tendency that causes procrastination and hesitation to attempt any practice at all.
People are wary of learning something wrong, then having to re-learn it, but I think that's a far better problem than delaying or avoiding learning something at all (with quality instruction, it's unlikely one can practice too far from the ideal; and even if that happens, it's not the end of the world. When attempting to learn, I try to remember the following quote from a webpage shared on HN a while back [0]: "Stay calm. Remember, you can’t become worse off than when you started."
[0] https://devjac.dev/posts/2021-05-29-my-personal-creed-of-emp...
Yup! I refer to this an "analysis paralysis" (a lot of my terms I'm stealing from martial arts). In essence, I freak out trying to fix my car because there are so many parts and I don't want to get it wrong, so I just... "don't". This is why we pay professionals the big bucks, but from a learning perspective, I think its what causes many people to abandon attempting something. They are scared to mess up, end up messing up, and leave due to feeling like a failure.
If, on the other hand, you can have an environment that supports experimentation and failure, and provides feedback on that failure, there will be less chance for abandoning the skill. This can be orchestrated through a combination of practice and a positive social network within the skill (peer mentors, growth mindset instructors, etc.). While persistence/perseverance/grit is still being researched, I think the social aspect can help strengthen it as well because you have a vested interest in succeeding and helping peers succeed.
"Sucking at something is the first step to becoming sorta good at something" ~Jake the Dog
--------------------
All learning is self-learning. Professors, trainers, and all teachers just organize and present the material to be learned. They don't teach it to you. You learn it. You're the one who actually absorbs, understands, and assimilates the knowledge by listening to the lectures, reading, thinking, solving problems, and other activities. Self-learning is a natural, human quality. While most of you have used this method in the past, you may want to do it on a more formal basis to speed up and fine-tune your methods. Here's a suggested approach (and trust me on this, you must write it down):
- Clearly identify what you want to learn. Write it out.
- Write some learning objectives for yourself. These statements clearly identify what you want to know and be able to do. For example, you should write something like "When I complete this learning assignment, I will be able to design and program an FIR DSP filter." The objectives should be expressed in "behavioral" terms, that is, using words that state some measurable outcome.
- Identify some initial resources. Start with books at the local bookstore or go to www.Amazon.com or Barnes & Noble at www.barnesandnoble.com. Most cities don't have good technical bookstores, and it's tough to find anything at regular bookstores. Consider yourself lucky if you have a good technical bookstore or a good college bookstore. Plan to get multiple books to give you greater breadth of coverage with multiple explanations, examples, and perspectives. Don't forget to look through your stack of magazine back issues.
- Check out online sources. Do one or more Web searches, or go to relevant company Web sites. You may run across an appropriate tutorial, white paper, or application note that will give you what you need. The large semiconductor and equipment manufacturers have tons of stuff on their Web sites, so start digging. Also check out the professional societies and other sources listed in the tables and sidebars.
- Watch out for any conferences or seminars on this topic. Usually, such events never occur when you need them, but you might get lucky. If you find one, attend because it will provide a big head start for your own learning.
- Organize your materials. Lay them out, mark them up, and then make an outline based on your objectives. See what you have and what you lack, and make an initial list of things to do.
- Dig in. Set aside an hour a day or whatever you can to go through the materials. Turn off the radio, CD player, and television. Make a habit of finding some quiet time to read and learn.
- Look for a human tutor. You could be working just down the hall from an expert on the very subject you're trying to learn. Pick his or her brain. Ask this person if he/she will help you understand and learn. Take this person to lunch or offer to pay for lessons. Most people will gladly share what they know, if you aren't too proud to ask. The best way to do this is to learn as much as you can on your own. Then, go for the professional, personal help with tough questions or when you get stuck.
- Include some hands-on. Is there any hardware you can buy or put together to help you learn it? Maybe there's some software that will help. Buy it or have your employer buy it.
- Write a paper or article or teach what you have learned. You have to know it to write it or teach it. There's no better way to learn for yourself than to have to explain it to others.
--------------------
[0] https://www.electronicdesign.com/technologies/dsps/article/2...
then I ask myself, is there anything interesting I can build involving this concept? or any useful activity I can do?
and I try to build it or do it, while using multiple sources of knowledge, but I never try to just remember stuff, the brain naturally remember the pieces of the knowledge that were actually needed the most while practicing. you don't know what's important to remember until you practiced, so in the end if you try to just retain knowledge you remember very badly a lot of things, but if you practice really early you remember very well what was actually important
I needed to learn javascript, So I created a web app https://text2db.com/ , which coverts simple text to database script. It took 3 months to make it. A long time but I learned alot.
You should probably just keep notes and refer back to them.
> Do you have a methodology for extracting common themes/patterns across topics?
Your brain does this naturally if you get a lot of sleep and don't think about it.
Homework. So much homework. Do all the exercises in the book. Taking notes helps me focus on a lecture, but I might as well use a brush with water on slate -- I rarely ever actually look at them a second time. I do not learn by watching. I recall a few nuggets that my brain can reach for when doing the work. I learn through application. It's common in math that students do not understand the contents of a class until they're halfway through the next class that depends on it. That's where the integration (unavoidable pun acknowledged) happens.
2. I haven't figured out a process for compilation but my plan is to condense big concepts into readable texts with the intent of sharing them with others.
3. Spaced repetition works, but it is labor-intensive. I use a combination of spaced repetition, mnemonic images (like Sketchy.com), memory palaces and reflective journaling to process my hands-on experiments.
4. I can combine my mind maps to see connections between texts. For example, maybe one book talks about scalability in passing, and another goes in-depth. If I compare those two maps I can see the gaps between each and it helps me see how the two texts are related.
Be it just passing stupid ielts test or getting a job - once I invested enough time to build a concrete picture of what outcomes do i need to get and why - everything else including motivation follows organically in the most efficient way I’m capable of.
I believe there is no single best strategy of learning for a single person. Since learning is as diverse as the subjects of learning might be.
I copy/paste what I think are the "atoms" of the thing to learn. And i build a small graph of interconnected .md files in Obsidian.
To me, it is very important to break the medium that brings the information into a graph that suits you the most. (call that process my knowledge ETL, and the result .md files my personal knowledge graph :)
PS: the funny thing is that you indeed refactor your graph when you come back to it with more knowledge. You usually do not remove things, but reorganize it in a better way. Very interesting process...
Obsidian looks really cool - I'm doing a lot of projects in a very chaotic manner and have been wanting something for personal knowledge management, that graph / links thing is really cool.
I chuckled when you mentioned refactoring your graph being an interesting process - because I've done similar but with notes and folders no visual linking system just pretty much putting notes in the right folder/book/whatever I'm using - and it's a right pain in the ass compared to this way.
2) n/a
3) yes, sort of. Learning something an hour per day over 10 days > learning something for 10 straight hours in one day
4) no method, but I tend to naturally go just below the surface on many different topics, so I think that helps.
A key thing for me is that I learn best by doing.
So maybe watching 5-10 hours of a structured "course", usually at 1.5x speed is about my limit before I have to get started on my own project applying what I'm learning.
After that, it's mostly blog posts, GitHub, and Stack Overflow to learn the more advanced aspects.
The next best thing is explaining the topic to someone who has no idea about it.
I used to. 90 percent of them were about tools or other things to look up later. Now, I add those to the backlog, and the other 10 percent become Anki cards. These days the only things I write down are meeting related: action items, questions I want to find an answer to, and maybe 1 piece of key information I want to refer to later.
> Do you compile/rewrite notes?
Nope! I may adjust Anki cards if the phrasing turns out awkward, or if there's a term collision. And if a card is tagged 'leech' thats a sign to rework it but generally I'm not trying to memorize things word for word where this might help.
In practice the hardest cards, the ones that get marked leech, are the bill of rights. Especially the middle ones that are basically a paragraph joined into a single sentence. Like, I know a warrant needs to be supported by evidence but its not always immediately front of mind that this is a 4th amendment right (instead of say 5th or 6th), or the exact phrasing. Fortunately this is a hobby topic rather than a professional need -- and hopefully if it were I'd be better at it =)
> 3) Does spaced repetition work for you?
I think so. For papers I generally extract a few key topics or points. Today's was three sentences about Cox proportional hazards, after hearing about his most famous contribution in an obit thread.
4) Do you have a methodology for extracting common themes/patterns across topics?
No? My general approach is to spend a few minutes thinking about how I might apply it in my work, and the go looking to find out who did / what they found. So for proportional hazards, I ended up googling and found a few places where this was applied, like analyzing churn rate (https://towardsdatascience.com/strategies-for-customer-reten...)
But note that I'm not trying to merge two topics of study in order to unlock some deeper truth, or better learn a general pattern. I'm trying to advance the state of the art in a field I consider myself pretty good at by learning how other fields work and stealing their best ideas. Kind of the inverse of the Hamming / Feynman jumping fields every five years.
3) Never tried it, curious but not that curious;
4) Take long walks and think about nothing.
I don't really fell that I have the space to incorporate notes in my type of learning as I love reading about all sort of random stuff and getting to the peak of Mt. Stupid [0] and kinda leaving it there unless it's of real interest to me.
- I found that I can retain much better if the course has readings. It can be lecture notes in textbook form (not presentation), or just a textbook. I found that without this, if all they provide are presentations, or blackboard work, then it is very hard to retain what I learnt long after the semester ended. (You could say I should create my own notes, but paying to learn is essentially to be more time efficient. I really don’t have time to create my own “textbook” from their blackboard work. I envy those that can transcribe in LaTeX in real time.) - creating cheat sheet (even if the exam don’t allow them and just for personal reference) is useful to keep the big picture, make you be successful in the semester, and can be useful in the long run. But especially if you are page limited due to exam requirement, the cheat sheet can becomes cryptic for your future self. I think this is a must for any course. - I lately also creates personal wikis to hold my knowledge. Basically Wikipedia is a very successful medium even for stuffs you know, you can look it up there to retain your old stuffs. Personal wiki is basically try to recreate the Wikipedia experience tailored for personal use, meaning only for relevant stuffs (say san history), or even links to various useful sections and other site such as math world. One tip is that in Chrome there’s an extension to force MathJax on Wikipedia, and with that you can click on a Math equation and copy and paste LaTeX in your personal wiki. (As it is personal, there’s no copyright issue, but if you share make sure the license is compatible and cite.) - 2nd brain: the last point about personal wiki may be similar to what some might call a 2nd brain. I still didn’t attain it (my “database” is fragmented in various places.) But I should learn more about that and may be one day I can build one.
What I said is more about being able to retain knowledge in the long run. Eg the real world doesn’t care if you make a search to find stuffs. So what I said is more about how not to let what you learnt be wasted because you can’t retrieve them.
Lastly, I find teaching very useful too. Being about to teach makes sure you truly understand a subject, and even reorganize it in a manner that’s easier to understand. But often you can’t control what you teach. You can’t say today I want to master Stochastic Differential Equation and let’s teach a course about that. But on the other hand, try to spend some time teaching some concept you find hard to grasp can be useful (audience and feedback like questions can provoke your mind to finally click.)
best combo I found was text to speech feature of online textbook, I'd listen to it and if I found anything even remotely important I'd stop the recitation and copy the text in notepad or something, and by the end id have compilation of important notes. The act of highlighting/copying/pasting was enough to form a good memory.
This will make you look like a „genius“ to outsiders, but it only works on subjects that allow for short feedback loops.
(example where it works: coding, example where it wouldn‘t work: raising a child)
In tech this can be an obstacle when communicating because many engineers have an extremely fine-grained memory, seemingly all the time. I will hand wave different concepts as a black box that we don't need to know right now, where they are happy to explain them at length, in detail. But if it's not relevant, I just don't care. They will also expect me to explain concepts that (to me) aren't relevant to the problem, and I have to say "I don't remember."
You're a mapper, like me. The only reason I ever want to learn details is if they are important corner cases.
>In tech this can be an obstacle when communicating because many engineers have an extremely fine-grained memory, seemingly all the time.
Those folks are packers, they know all the corner cases, and worry incessantly about them.
Google "mappers vs packers" to learn more, far more.
This is a good habit. A technique I have been using in previous weeks is to initially do a superficial read (inspired by Mortimer Adler's "How to Read a Book"), not worrying if I understand every piece of information, highlighting along the way. The goal is to understand the overall structure and broad arguments of the text.
Since highlighting is ineffective for learning [0], these act as markers to focus on for creating flashcards as learning material upon a second, more in-depth read.
[0] Research paper [PDF]: https://pcl.sitehost.iu.edu/rgoldsto/courses/dunloskyimprovi...
When a child learns a new word, they may go around gratuitously using it for a while.
When you learn a new concept or technique, gratuitously apply it in every way you can think of. Having done that, you will be able to use it appropriately when the need arises.
For example, in music, if I learn or discover a new kind of chord substitution, I will gratuitously apply it to a bunch of chord progressions. Then I'm left (hopefully) able to apply it when that sound is what I want, or when it solves a voice leading problem.
The idea is you consume and apply, then quickly turn a combination of theory + practice into your own words which is proving to yourself that you understand it. The key point there is "you", you don't need to publish the written component to anyone. Its purpose is to force you to come up with unique thoughts to combine this new information into something coherent which I'm sure has some benefit in making your brain remember it (but I have no scientific proof of this). It can also be used as a personalized detailed reference in case you ever forget the details which IMO is much better than scattered notes you tried to quickly write while you listened to or read something.
I don't know if this is a formal way of learning something. It's something I've done for most of my life because it felt intuitive at the time and still does.
- don't take rigorous notes because it ends up replicating a lot of the material that I'm consuming anyway
- still write some notes if something interesting stands out; it's usually related to some core idea/explanation, not to technical details
- don't obsess over having "complete" notes or worry too much about organizing them
- try to write some relevant code alongside whatever I'm learning
- spaced repetition is for memorization; I'm not trying to memorize
This is different from how I used to learn for exams at school/university where I would repeatedly re-synthesize notes to a shorter and shorter format until I can reproduce the material from a cue.
I think the distinction between the two modes is important; it seems very weird to me to see knowledge workers putting so much effort to memorize stuff that they can look up anyway.
When you start something new, all the symbols are "too close together" and it takes time and repetition to increase the "resolution" on that map so that you can put the symbols into position with more precision and not have them confused with one another. You don't yet have a good intuition for the significance of each symbol and it won't come from being told, because sources have biases - frequency over time and space is a much stronger signal. It's the same with connections between symbols.
Doing, rather than just reading, is important; you need to try and find that Goldilocks zone of growth, where if things are easier you're not learning but if they're harder you lose hope. Try something just beyond what you know how to do, page in new information on demand when you get stuck (from docs, people, source code, whatever it is).
Writing notes helps me personally creating the space for symbols and reminding myself of what I already heard about but I don't know that it's necessary for everyone, and I especially think I've found it more useful as I've gotten older (and know more stuff already). Sometimes when I learn something "new", I pin it close to a concept I already know, which dulls its novelty and I'm probably more inclined to forget it, until I'm reminded of it again. And this is down to that "creating mental space" idea again.
Repetition increases symbol salience, particularly when you're surprised by the divergence between what you thought something meant and what it actually means. The risk of simply reading, and not doing, is that you're not surprised often enough. Doing stuff keeps you honest.
The summary is that doing practice tests (e.g. creating flashcards in a question-and-answer format, or regularly doing practice problems) is highly effective, along with studying over a longer period of time instead of cramming. Switching between learning subjects ("interleaved practice") is also effective, along with creating explanations in your own words about a text, together with asking yourself questions about the text. In contrast, highlighting the text and rereading as a way to learn is relatively ineffective.
[0] Full text [PDF]: https://pcl.sitehost.iu.edu/rgoldsto/courses/dunloskyimprovi...
"There are four key steps to the Feynman Technique:
"-Choose a concept you want to learn about
-Explain it to a 12 year old
-Reflect, Refine, and Simplify
-Organize and Review"
> It's like Charlie Munger once said about mental models: “All this stuff is really quite obvious and yet most people don’t really know it in a way where they can use it.”
The long and short of it is that you go through a cycle of Knowing, Doing, Assessing. Each of those has sub sucked and pieces but they fit together really well and work generally across different types of things you’re trying to learn (intellectual, skill,ms, physical).
I like instructions that specify how things work, so I can route around problems, and understand what the goals and mechanisms of a system I'm using. I can tolerate a wide variety of discrepancies in those instructions, and work around small changes in procedures that might not be documented.
If I'm being tested on general knowledge, and how things work, it is stuffiest to read and understand the materials provided.
Practical Example - Right now I'm trying to understand the fine grained details of how quantum computers work, I've watched a lot of boring youtube with words like Hamiltonian, Eigenstate, etc... none of which has clicked, but all float around like loose puzzle pieces... eventually I'll find the detail I need, and a connection will be made, I'll then go back and find other pieces until I understand the landscape at the detail I want to know.
If I'm being tested on random facts (dates, buzzwords, etc) then it's time to break out repetition and wrote learning. This is also the mode when learning a new skill, practice, practice, practice.
---
If you're a packer, the opposite is true. You'll likely keep a lot of notes, and be good at memorizing facts.
I've worked with packers in the past, they like clear, precise, easy to follow instructions that very closely fit what they will see as they follow them. If the instructions don't match what they see, they will end up needing help, or get frustrated.
I'm not sure how packers best learn. I suspect it's repetition all the way.
---
Repetition of the same problem type or set can give illusion of fluency through short term memory familiarity.
Say somebody says a long string "The Cap Theorem is Consistency, Availability, and Partitioning," you write down the initial letters with space to come back and complete the words: T__ c_____ t_____ i_ c_______ a______ p_____. Once you have the initial letters down the hardest part is done. For very long sentences you want to remember this helps a great deal because you will still remember the last several words with the hint of the first letter when you do a second pass to fill the (rest of-the-word) in.
I find that when taking classes, reading papers, articles etc, I learn far better if I can #1: Immediately see where the material is useful due to having encountered a problem it solves, and #2: Immediately put relevant information into code/CAD/notes etc.
1. Always be reading.
2. Teach everything you know.
3. If you don't know, learn enough to start teaching.
4. Take notes when you feel compelled to.
5. Use sleep as a memory tool. One nap during the day, and before going to bed each night think about what you're learning or want to learn more about. You'll wake up with more clarity every time.
The best book on this topic is probably "Learn Like a Pro" which came out last year.
It seems that teaching is the most underrated crucial elements to understand a new and/or difficult subjects. The FAST method proposed by Jim Kwik also includes teaching as one of proven elements to quickly learn and understand [1].
[1]Jim Kwik’s FAST Method Will Help You Learn Faster
The best form of spaced repetition IMO is the application of the acquired knowledge in a big project over time. That way re-visiting the concepts comes naturally as you continue to develop something over time.
In programming, examples would be:
• writing code and reading and understanding other people's code.
• `executing' some code with pen and paper
• translating a formal statement of an algorithm into code
• translating some code into a formal statement of the algorithm
• translating code between two languages
• implementing the same functionality in as many different ways as you can think of
In learning scales on a musical instrument:
• ascend, then descend
• descend, then ascend
• start/end on notes other than the root
• all of the above but whilst playing the scale in intervals or arpeggios
In learning the times tables, examples:
• what are the factors of 24?
• recite the multiples of 7 backwards from 70
For coursework, I would take notes. At the end of the day, I would reread the notes and complete them. Completing them means correcting errors, filling in details from examples, and using assignments and course material embellish the notes. Embellishment means adding notes of personal interest from other course material, and also adding examples from problem sets. My notes were my source of truth, and I kept them in good order. For exams and future coursework, I would only use my notes since they were complete.
In my professional life, I consume a lot of material but do not take notes. I find that there are two important aspects to learning. The first is high exposure to material. Being able to put a name or provenance to an idea is helpful in finding my way back there again. The second, which is similar to what nickjj mentions in a comment above, is to close the loop. To wit, my engagement with material is to find aspects for which I can test it outside of the scope presented or examine in in contrast to another idea. By engaging with the idea, I am able to come to an understanding of its verisimilitude and utility to me.
In the later, I do not take notes while attending lectures and reading. However I maintain complete lab notes for my work. Lab notes include random thoughts, references, uri:'s of data sets, links to papers and wikipedia articles. The lab notes are written for me, and are mostly in chronological order. By the contain as thorough an appendix as I have the patience to maintain.
Sounds like a joke response, but it isn't. My focus will settle on something because I want to do a specific thing in that area, and it just doesn't let go, even when I need it to. As a perfect handy example, my brain is currently full of a) chess, and b) compliant mechanisms, when it should be full of Rails/React interview prep.
I guess the transferrable principle here is to have something concrete you want to do with the knowledge you're gaining so that your brain has a tonne of hooks to hang the theory off.
[1] https://www.amazon.com/Mind-Over-Machine-Hubert-Dreyfus/dp/0...
Somehow I failed to learn things when I was taught in "official ways", yet I managed to learn the language by being brutally forced into practice and environment that pushed me to make it happen. I moved countries when I was 12, they put me in school straight away without knowing how to speak (although I have been studying for a few weeks, at least the basic grammar).
The language group has been similar to my native tongue, however the alphabet was different (as I was used to cyrilic). Nonetheless, as a kid - I already saw some patterns and similar rules.
I managed not to fail my class as well as spoke and wrote really well after 2.5 years. After 5 years I was better than most of the native tongue speakers in terms of grammar and on par with their vocabulary. Obviously using the language every day and being pressed to do so contributed.
Years later I started learning German in high-school... was so bad it and never managed to even get to the basic level after 4 years. I moved to Berlin again years later but because English was already quite prevalent, it never pressed me to learn German and I never did.
Somehow the most effective learning curve was just doing the thing, making a lot of mistakes and I never took textbooks into account even when doing so.
The methodology was just deliberate practice and tacit knowledge in the end.
I went through a bad patch as the nineties ended and I thought that computer note taking might be a good idea. It produced pretty good notes (I type well) but was much less conducive to learning. In fact, I felt it was distracting and counter-productive.
Handwritten notes. Definitely my first line of offense against ignorance.
After that, teaching it. If I can find an opportunity to make a presentation. That's great. I will always confirm understanding and level up when I explain what I know in a semi-formal way. Explaining to colleagues and friends is good. I didn't do study groups in college but found analogous social activities very helpful since.
After that, doing it. If it's a practical topic, putting the lessons into practice asap is very helpful. Like, I'm sure, many of you, I am a programmer. If I start using a new tool, technique or idea, I will soon have solid understanding.
Of course, I also keep going. If I do not keep seeking progress in a topic domain, then any knowledge I have will fade.
I have created a learning framework for myself to learn literally anything. First of all It’s not going to be easy to get started learning something new because there are many holes in your mental model about the material and the aim of the learning is to fill those holes. We’re living in an information era. You can drawn yourself in surfing the web/docs/articles if you are some kind of perfectionism to convince yourself that you’re learning. But that’s the trap. You should spend about 30-40% of your time learning the material and 60-70% of your time applying it and then under the process you’ll find: “Oh I don’t know how or what is X” then you go to learn about X specifically. This works best. In other words as you will be applying what you have learned so far you start “learning on demand”. In other words filling the individual holes. This loop will force you to learn the topic.
So my strategy is to work first and learn second. When I encounter a roadblock I try o learn something new, but in most cases I then quickly forget about it soon. This might happen several times over. Once I had to learn about unix file permissions, I knew all the commands and numbers and what they meant and it all made sense. But now I only remember `chmod +x` and that there is a command named `chown`. This satisfies for my day-to-day needs and is enough so that I can re-learn the thing if necessary.
And for the general context that are important to know in detail I found that teaching is a good way to remember and reinforce. I teach a course every year and every year I am surprised how much I've forgotten. But it quickly comes back after I start preparing materials for the class.
When I was young I used to think that you can learn a thing once and then remember. Now I know that, speaking strictly for myself, this is not the case.
After that spoiler, here is how I learn things:
1. Get the difficult stuff and read through it as long as your brain can parse it.
2. Once you have the first overview, rest and visit the same thing next time.
3. On second attempt depending on the context: i. If it is problem solving: Attempt to solve problems (look at examples and try to establish relationship) ii. If it is theoretical: Note down the key assumptions, key steps, key proofs.
4. Until you are confident, loop 2 and 3.
5. After 1 month or so, you will forget what you have then, thus go back to step 1.
Yes, this is highly inefficient. I really want to break out of this loop. But the issue is I am so accustomed that my brain goes into this mode by default.
The result is I get my own version of understanding which may not be the actual true understanding. But it is as close as it can get (70-80%). So I am happy about it!
I only integrate one or two practices at a time, and I stopped short of implementing SRS or a Zettelkasten because I began to realize I was spending too much time on productivity to actually get anything done. I'll probably return to them later - I think SRS especially gets a bad rap from people who like to think about things conceptually as "just being rote memorization", but IMO the human brain is not a computer for Platonic objects. It thrives on hard data and real-world examples, and "memorizing" components or instances of a particular concept so they're at hand for effortless retrieval just makes connecting them to existing ideas easier (which is arguably all understanding things is).
But remember that it's just a scheduling mechanism to save you time, not to help remember, necessarily. I like the Harry Lorayne book on memory for various tricks and techniques to actually remember. It's not groundbreaking but goes over a lot of the standard and proven memory hacks.
Specifically though I use different methods for different materials. For some specific things I need to memorize verbatim I use hand written index cards/spaced repetition. For learning math, programming, etc there is no substitute for doing example problems with solutions you can check. For general reading I write my own summaries, notes.
Only if you use it as such. SRS is a scheduler to help you optimize your time, to not spend time on things you probably don't need to refresh. The actual memory/learning part is orthogonal.
I use SRS to plan different practices of things (in my case programming languages or concepts). If I consider that I did one of them well, I mark it as such and won't see it for a longer time, if not, I mark it badly and I'll see it again sooner.
I’m curious. If you would be willing to share, could you demonstrate an example of a prompt? My learning items have almost always been questions and answers, and occasionally image occlusion (‘label this part of the diagram’) and cloze deletion (‘fill in the blank’).
[0] https://www.supermemo.wiki/en/learning/spaced-repetition
I strongly agree. In the learning blogs (e.g. SuperMemo wiki) and forums I’ve read (r/Anki), there is a bias to solve every learning problem with space repetition (very roughly, flashcards on a computer program scheduled in an optimized way).
I’ve seen users try to make it work for math and physics, and though it may work for some users, the approach was ultimately a distraction in my experience, from doing lots of practice problems.
I think memory plays a key role in learning and especially recognizing opportunity to use something I've learned.
That might be how you learn, which is a good thing to know, but the presentation of your personal understanding of yourself come off like “this is the way for all”, which gives me the yucks.
For me I need to re-formulate things in my own words (or my own code) until I understand which parts of a system I have blind spots on, then dig into those, then rinse and repeat.
If I can express it in simple language in a way that hangs together, and go into detail about complicated parts of the system, I’m getting somewhere.
The downside of learning a system of human invention fundamentally is that one invariably comes to understand that it is a Rube Goldberg machine that some yahoos figured out how to sell.
Not sure why you assume OP is speaking about his own personal experience?
I am unsure what OP background is, but I will assume he knows what he is taking about.
there are theories of the mind that actually supports this view.
It goes back to early attempts at AI [0], and different perspectives on this also caused a split amongst researchers.
> If I can express it in simple language in a way that hangs together, and go into detail about complicated parts of the system, I’m getting somewhere.
What you have said does not actually contradict what OP has, but rather could be used to support what he said.
Yet it seems you believe it contradicts him?
For the tech things, the prompts are things like:
"Do an exercism.io exercise in <language>" where language is one of the programming languages I'm studying or want to keep "fresh"
"Write the basic 'counter' in React. With class compoments" or "... with functional components".
Things of that nature. Stuff I can get done in a half hour or less.
I thought I was the only one that did this.