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How Do We Learn? (ncase.me)
272 points by severine on March 1, 2018 | hide | past | favorite | 62 comments

I took a Coursera course titled Learning How to Learn[0] and found it really helpful as an intro class to this "field". It was also very practical.

[0] https://www.coursera.org/learn/learning-how-to-learn

I've also taken this course, but would recommend those new to it just read the post here, which is a good summary: https://www.reddit.com/r/GetMotivated/comments/5950tm/text_i....

Agree. Having done the course, I think a text summary does a good job of getting to the big ideas (I don't really like learning via video fwiw)

HN Needs a tip button for things like this. This is amazing. Thank you

Thx. It's a nice summary for this course.

That is a fantastic summary, thank you!

That class is free. Everybody should take it. Lots if insights on how to deal with procrastination, effect of physical activities on our brain efficiency, etc...

Giving you a vote for this. This Coursera course helped me reframe my study habits after graduating university and has proven to be invaluable for my self directed learning.

The title of the course really shows that learning is recursive. Pretty fitting given the name of the company who hosts us.

I Recommend this coarse, currently enrolled in

If you want to know the answer to this question, you have to look at the amygdala.

This dual set of brain regions are gatekeepers to long-term memory.

They/it only lets in things it thinks you might need later.

And it grades this need based on emotion.

So, if you want to recall something later, you need a purpose, and if the purpose ties into something emotional, all the better.

(I know some people are going to fight me on the assertion that emotion regulates memory, but do a little research before telling me I'm wrong.)

So how does one hack emotions to remember better?

Have a look at NLP(neuro linguistic programming) techniques regarding memory.

An example, before you start starting studying a topic, tell yourself, consciously, why you are going to learn this specific thing, and how you want to use it. After studying, tell yourself how are you going to use the things you have just learned, imagine yourself applying them in different scenarios. Even these two simple exercises helps brain to make those connections GP told about.

I don't want to get in to the topic of whether NLP has a scientific base, just want to emphasize that most of these techniques are brought together from examining how experts relevant to the area do things that made them successful.

I don't have enough time right now for a longer answer or sources, will try to expand later.

That's a really good question.

I don't mean to be rude and I am truly interested in this topic, but I must ask, is there a version of this that is readily legible? Fuzzy (out of focus) light grey text on a white background absolutely results in a headache for me when trying to read this.

I didn't have the visual issues so it was enjoyable for me to read.

My spaced repetition system requires that I copy ideas I want to recall. I'm sharing my summary of the main ideas in case they help you.


# Learning by Building Connection

New ideas have to connect with what’s already there — they cannot be stored, as if in a filing cabinet.

Throwing facts at people doesn’t work. You have to: * connect ideas to other ideas and everyday things

* understand an idea in multiple ways (e.g. words, visuals, etc.)

* once you make connections, you have to maintain them

* you don’t need to unlearn connections to make room for new ones

# Maintaining what you learned

Recalling is better for retention than re-reading. Spacing effect shows that we forget things quickly the first time we see it, but if you exert effort to recall things spaced over increasing intervals of time, you retain a lot more than if you were cramming.

# Learning through deep connections

You have to process ideas on a deep level to make them stick. A great way to learn something at a deeper level is to explain it to someone.

Thank you for your reply and assistance danial.

This seems more like "How Do We Memorize?", as is taught and performed (poorly) in American schools.

In contrast we learn by doing, by manipulating things or concepts.

Committing things to long-term memory is an absolutely essential component of any sort of learning. There are many studies talking about how doing doesn't necessarily imply any learning at all and only implies learning insofar as it leads to committing information to long-term memory. Furthermore, there are studies talking about how problem-based/inquiry-based learning (what it sounds like you might be thinking of) generally produces worse outcomes than direct instruction (which places substantial emphasis on committing things to long-term memory).

This all makes sense in light of the "human cognitive architecture". Working memory is severely limited while long-term memory is effectively unlimited. Thus, committing things to long-term memory frees up the scarce resource of working memory. In fact, there are many studies which indicate that the key differentiator between experts and novices is that they have a huge long-term store of schemata which can be applied in the problem domain and allow more efficient representation and manipulation in working memory.

It would be helpful if you would cite the studies that allegedly support your statements about the poor results of learning-by-doing. As previous poster points out “committing things to long-term memory” is memorization, a small part of learning.


"Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching"

> Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

Choice quotes include:

> The past half-century of empirical research on this issue has provided overwhelming and unambiguous evidence that minimal guidance during instruction is significantly less effective and efficient than guidance specifically designed to support the cognitive processing necessary for learning.

> Our understanding of the role of long-term memory in human cognition has altered dramatically over the last few decades. It is no longer seen as a passive repository of discrete, isolated fragments of information that permit us to repeat what we have learned. Nor is it seen only as a component of human cognitive architecture that has merely peripheral influence on complex cognitive processes such as thinking and problem solving. Rather, long-term memory is now viewed as the central, dominant structure of human cognition.

> These results suggest that expert problem solvers derive their skill by drawing on the extensive experience stored in their long-term memory and then quickly select and apply the best procedures for solving problems. The fact that these differences can be used to fully explain problem-solving skill emphasizes the importance of long-term memory to cognition. We are skillful in an area because our long-term memorycontains huge amounts of information concerning the area.

> The aim of all instruction is to alter long-term memory. If nothing has changed in long-term memory, nothing has been learned.

I'll quit there, but that's only a few pages in and it's all quite good and definitely worth reading IMO.

That seems like a very engineering-skewed perspective on knowledge. I'm not sure how that advice could apply to a philosophy or sociology student. If doing means writing research papers, then that is going to be a hugely inefficient way to learn all the things they need to learn. They won't have the resources to write a paper on everything they read. Some of it needs to just go down the subconscious, rapidly and in large quantity, for quick reference later on.

> I'm not sure how that advice could apply to a philosophy or sociology student.

Do reading assignment, discuss/argue about it in class with a TA or professor to mediate and clarify stuff, maybe write a paper afterwards.

Engaging with the content is kind of a universal way to learn by doing.

I think philosophy and sociology are still poor examples - for the most part those subjects are reading, writing, and thinking. When I think of tedious fields that require mostly memorization, I think of medicine and law.

So you get students who can parrot what they memorize but cannot think, reason and solve new problems.

Maybe that's OK for philosophy and sociology, but in other fields students will be actually asked to contribute to the world and so must be trained to do rather than to memorize.

Except for scholars (who are primarily historians) what of philosophy and sociology is worth remembering anyway? Most of philosophy was written before Darwin and certainly before any significant brain science research was done. Much of sociology is also questionable:


The only reason education focuses on memorization is because in 1892 a committee chaired by the President of Harvard decided that high school education in the USA should prepare students for collegiate study in particular subjects of his choosing. Should we, today, continue to follow the direction of those professors, who were only interested in ensuring that, when students arrived at their departments, they were sufficiently indoctrinated to be scholars in their fields?


It seems he took the main ideas from this book[0] and made a little comic about it.

[0] https://barbaraoakley.com/books/a-mind-for-numbers/


This mirrors my own experiences very well. I always look for analogies to understand new ideas (or to explain them).

Also, if I'm driving to a relatively new destination that I've been to before and think I'll go to more times, I try to remember the way without looking at the GPS, because I've found that if I look at the GPS every time, I don't end up remembering the route as well.

There's an interesting subculture around the concept of "Quality" which was popularized by Zen & The Art of Motorcycle Maintenance.

If Quality is something intrinsic to the observer/universe pair, learning is maximized along the path of most resonance.

Learning-to-learn tricks can often desensitize you to your "true passion" (this is assuming it exists) because there isn't a coherent narrative that allows your experience and skills to compound in a unique way.

Instead you have a collection of brute-force gained skills to solve problems for other people and by becoming good at this become numb to what "you" uniquely can see as a problem and create unique solutions to.

Analogies may be the exception because they grow, relying on roots and branches. An analogy that doesn't feel ham-fisted is naturally connected to your existing pattern of "you".

Sal Khan is a fan of Carol Dweck's Growth Midset.[0]

[0] https://www.youtube.com/watch?v=WtKJrB5rOKs

Any suggestions for further reading? In particular a book geared towards people who aren’t domain experts would be great

From the most popular MOOC of all times, "Learning How to Learn", there is this book: https://barbaraoakley.com/books/a-mind-for-numbers/ Although the "numbers" in the title, the book is about any kind of learning.

I also like "Refactoring your Wetware": https://pragprog.com/book/ahptl/pragmatic-thinking-and-learn...

Might not be exactly what you're looking for but I recommend two books: "Peak" by Eric Anderson and "Mastery" by Robert Greene. Both of these books are really about getting to the top of your field but are both directly centered around how we learn. Mastery takes more of a macro approach to becoming the best by providing lots of real world anecdotal stories (like that of Leonardo Divinci, and Paul Graham) Peak goes a little bit deeper on the science of how we learn if I remember correctly, but both are definitely worth a read.

Brain Rules by John Medina and Make it Stick by Peter Brown are pretty good, and not too tough going. In terms of the mechanics of memory, they're pretty good particularly.

I've been reading the book Becoming Fluent, and it seems like a great introduction to the field. It's about how cognitive psychology can help adults learn a new language.

However, from another angle, it's basically about using the idea of language learning to teach basic cognitive psychology.

(My phd was in human memory, and I can't stop thinking about ways this book could be used as part of a cool learning course).

It should be noted, however, that learning a language is very different from many other kinds of learning (understanding complex systems, learning history, etc.) in that it engages very different patterns in declarative and procedural memory and possibly involves some specialised networks. I know some very frustrated scholars of second language acquisition that lament the over-applying of the general science of human learning to specifics. (Just making a general point here; the book you are reading sounds like it's specifically about language indeed.)

I am probably in what they would consider the over-applying camp ;). When it comes down to it, I think there's a tendency in many different fields to cast within-field learning problems as distinct from others, but in general, researchers in those fields often don't have a ton of experience on learning in other domains.

RE networks, I agree that there is likely evidence for distinct patterns of activation in various neuroimaging studies, but having worked in memory + neuroimaging, I think there's a serious risk that people will take something like "statistically significant difference in brain activity" and use it as a substitute for "substantial differences in learning behavior / retention". (this is a well known problem in imaging).

I'm not too familiar to L2 acquisition research, though, but those are my impressions from thumbing through some of the field. Would def love to hear some study recommendations :).

Can this work in learning a new programming language? I'm seeing parallels in that you'll need to recognize/encode patterns/syntax in both.

I build tools for teaching data science at DataCamp, so am really interested in this question! I think so, and suspect the ways in which a good language tutor assesses / recognizes where students can improve will have direct parallels for coding.

Greg Wilson (who founded Software Carpentry) has a great collection of thoughts on learning to program in general: http://third-bit.com/

The "Learning How To Learn" course is also one of the most popular MOOCs


Learning at scale via MOOCs seems to be enormously effective. EdX alone issued 250K certificates for 2.5M registered users. Mostly in CS.

I'd be interested to see YC Startup Schools own results as well. Do at least 10% of Startup School 2017 grads go on to full time work on their companies?

"Mindstorms" by Seymour Papert is a must read IMO.

The Lakoff book linked looks approachable.

I have a website- hit me up; email in profile.

After reading about and learning all about how our biology works and everything about the brain, cognitive neuroscience, psychology, etc has anyone put these ideas into practice? It would be impressive if an outsider became an expert in a field which they knew nothing about.

how did they do the artistic fonts etc? Do they hand-write first, or is there some special fonts available?

very helpful links, will practice with it, thanks!

I never got Zines. Beyond their cutesy art style, they generally don't seem particularly effective at conveying information in a somewhat concise manner. And if you don't want to be concise, why use such a very visual medium then and not just write an article?

Sir and/or Madam,

I feel the need to inform you that you are, more than likely, quite ill-informed. Zines are a spectacular human achievement, worthy of your attention and respect. Or, were it otherwise, how do you explain this godamn amazing piece of work:


This looks hilarious and interesting. Reminds me of Diagram http://thediagram.com/ but PoC||GTFO seems a lot more programming specific?

Yes indeed, PoC||GTFO is very programming specific, down to the point where the PDF is an executable that can be used to serve .. the PDF. ;). (This particular zine is famous for such badonkadonk!)

Just wanted to follow up - thanks for that amazing ref! I've just blown a fat wad on some DIAGRAM merch and cannot resist wasting the rest of the day downloading the whole godamn site. WOW! Great fun! Love it! Huge TA!

This is amazing. Thank you for sharing this!

You are welcome, I am most glad to have shared it with a like-minded soul. Don't forget to read the fine print! :)

There's nothing to get. A zine is just a self published magazine. Not all of them are hand drawn.

Essentially, zines were blogs before the web.

Fair enough, I wasn't aware of the original meaning since I only came across it multiple times on the web in this drawn, comic-like form.

I figured that was the case, so I'm glad I could fill you in.

I agree that the hand drawn style isn't the best way to consume this sort of content.

Since we're on the topic of learning... https://hbr.org/2012/03/hard-to-read-fonts-promote-better-re...

Sometimes you just want to write and draw with pen and paper.

It's because forty-something programmers wish they were 90s scene kids. And/or _why the lucky stiff.

This is why it's important to keep multiple projects going simultaneously.

Each project needs time for the brain to digest in order to make the right decisions.

You save time by going slow, but async. parallel.

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