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I wrote about very similar things from a teaching perspective here: https://lelon.io/blog/how-to-teach-math
In fact, I've thought a lot about how to generalize these techniques to a data structure (i.e. knowledge graph) so that anyone can zoom in or out to whatever level of abstraction they please:
https://lelon.io/blog/boosting-scientific-productivity-again
Would love to chat sometime!
This isn't really a learning technique. It's an analogy on learning. Every other day there's some blog post on HN about some analogy on some self improvement topic like learning, project management or complexity or whatever... I'll tell you what learning isn't. Learning isn't coming up with new analogies for concepts you already completely understand over and over again. I and pretty much everyone on this planet alre…
You completely understand learning? :)
This is nicely put. It reminds me a bit of David Perkins's [0] "whole ballgame" approach (i.e. the best way to learn how to play baseball is to play a few games or approximations thereof, e.g. tee-ball; you'll struggle mightily at first, but you'll ultimately benefit by having a sense of how the game as a whole works, and it provides valuable context and motivation for subsequently working on specific skills like thr…
This isn't really a learning technique. It's an analogy on learning. Every other day there's some blog post on HN about some analogy on some self improvement topic like learning, project management or complexity or whatever... I'll tell you what learning isn't. Learning isn't coming up with new analogies for concepts you already completely understand over and over again. I and pretty much everyone on this planet alre…
> Learning isn't coming up with new analogies for concepts you already completely understand over and over again. You completely understand learning? :)
A better phrase is "Learning isn't coming up with new analogies for concepts you already more or less understand over and over again."
Happy? does that satisfy your overly pedantic mind?
This doesn't sound very practical advice to me. It seems to be saying: Do a bit of breadth-first mixed with some depth-first. But whatever you do don't do only depth-first. But maybe that is an important point. Don't dig too much into details try to get the overall picture so you can decide what you should focus on most.
It seems to be saying that to me too.
Given the tree and maze visualizations, I'm a bit surprised that there was no corresponding visualization of the recommended strategy of switching back and forth between depth-first and breadth-first search (at regular or perhaps random intervals).
Regarding the optimality of various strategies, there is a distinction to be made between the optimal strategy for an individual learner/searcher, and the optimal individual strategy for searching collectively.
Also, there is a difference between strategies for acquiring existing knowledge that is new to you, vs. expanding the boundary of existing knowledge.
Regarding the "expanding the boundary of knowledge collectively" problem space specifically, it is worth noting that a pure depth-first approach isn't really possible in practice. Even in fields that reward depth-first individual search strategies such as math, an individual searcher's search is bounded by the length of their career, and each new searcher starts semi-randomly somewhere along the then-current boundary of collective knowledge.
Earlier quoted context omitted.
> Learning isn't coming up with new analogies for concepts you already completely understand over and over again. You completely understand learning? :)
:) A better phrase is "Learning isn't coming up with new analogies for concepts you already more or less understand over and over again." Happy? does that satisfy your overly pedantic mind?
You’re claiming to understand learning. People do phds in learning from multiple domains (psych, neuro, ux, etc). You already know it all?
The rabbit hole is deep. Coming in here and saying yeah yeah we all get it already is a sign that you don’t.
Earlier quoted context omitted.
:) A better phrase is "Learning isn't coming up with new analogies for concepts you already more or less understand over and over again." Happy? does that satisfy your overly pedantic mind?
You missed my point (and the author’s it appears). You’re claiming to understand learning. People do phds in learning from multiple domains (psych, neuro, ux, etc). You already know it all? The rabbit hole is deep. Coming in here and saying yeah yeah we all get it already is a sign that you don’t.
You're not a stupid person so you being not stupid knows that I and pretty much everyone on the face of this earth knows that we all are aware that no one understands ALL of learning. So if you're not stupid, and you already know this, why did you take the time to point out some pointless flaw in my wording?
I'll tell you why. Because you liked this analogy. You thought it was profound to compare learning to DFS and BFS and fractals and you were sort of offended when someone like me didn't find it profound. Not only do I not find it profound, I find it obvious and trivial. Comparing learning to fractals is like some offhand thought I can have for like 5 seconds than forget about because it's so trivial.
Too each his own man. If this article blew your mind great. It didn't do anything for me.
Here's another analogy for you.
Learning is like traveling down a path and encountering a several forks in the road. You can BFS the paths or you can DFS the paths
Replace Learning with "Life" and remove BFS. In life you can only choose one path every time you encounter a fork and the decision is permanent. No popping the stack like in BFS to try the other paths. It's just DFS all the way to the last final leaf node. You have one life so live it right.
Did that analogy blow your mind? Because I made it up 3 seconds ago. That's how trivial these analogies are.
This doesn't sound very practical advice to me. It seems to be saying: Do a bit of breadth-first mixed with some depth-first. But whatever you do don't do only depth-first. But maybe that is an important point. Don't dig too much into details try to get the overall picture so you can decide what you should focus on most.
That sounds pretty reasonable to me. You don't want to dive straight into depth-first because then you disappear down a rabbit hole with no context to tell you whether it's the right rabbit hole. Start out with breadth-first until you have a feel for the lay of the land, then pick a direction to journey in.
It also must be dependent on the topic under examination largely therefore the advice can only very generic.
Let's think about an example topic, say "Mathematics". What would be the best strategy for learning mathematics?
Earlier quoted context omitted.
You missed my point (and the author’s it appears). You’re claiming to understand learning. People do phds in learning from multiple domains (psych, neuro, ux, etc). You already know it all? The rabbit hole is deep. Coming in here and saying yeah yeah we all get it already is a sign that you don’t.
No. You missed the point. You're not a stupid person so you being not stupid knows that I and pretty much everyone on the face of this earth knows that we all are aware that no one understands ALL of learning. So if you're not stupid, and you already know this, why did you take the time to point out some pointless flaw in my wording? I'll tell you why. Because you liked this analogy. You thought it was profound to co…
It's nice to have another aspect or perspective on learning but it is certainly not a "new learning strategy". I agree.
And yet there is a merit in analogies, they can help you understand the underlying principles of something, in this case learning. I'm not sure people (including me) always get the full picture of something and an article can help with that showing learning from another angle.
In general I agree with you and yet the article adds something for some to their understanding of what learning is.
Thanks for that.