On Learning and Models
When you read to learn you have to remember that you can’t know everything.
Optimized learning is the process of figuring out what is important and what is not important and then flat out IGNORING what is not important.
Fragments from imaginary dialogues
“How can I optimize learning?”
“An essential principle of learning is:
Know your Why.
Just as when you think of a color, every instance of that color around you magically starts popping into view (perceptual-priming), knowing exactly Why you’re learning primes you to identify at a glance what’s important from the material, and acts as an information filter.
I’d go one step further:
Know your What.
Be specific. Know exactly What you’re looking for when learning. Build a high-fidelity Meta-Learning-Map.
I like to use mind-maps, like this:
“Can you explain the purpose of the Models branch?”
“When you learn, it’s important to grasp the essence of the material. I’ve come to realize that models encode this essence. This is a process of deconstruction. Deconstructing language, and deconstructing meaning.
Most of my life (FORTY years), I used to think in ideas. But since I set as a goal to become a Super Thinker [<link; medium read] and started thinking in models, a little less than a year ago, it seems like my mind has evolved.
I now think in units of meaning – that’s what the model essentially is. Every idea is an aggregate of models. It’s a bit like how Neo saw the reality behind the Matrix as green digital rain.
One of my many projects is creating a (practical) taxonomy of models. That’s what the Models branch of the mind-map is.”