Many readers may have heard of the "Feynman learning method", which is recognized as the most effective learning method in the legend, and we will analyze it today, where is the essence of this so-called most effective learning method? How can we effectively control him?
Identify a topic of study [such as learning about the energy discontinuities of quantum mechanics].
Simulation teaching [such as explaining the knowledge points related to the discontinuity of energy to others].
During the explanation, I found that the relevant knowledge points were not clearly controlled, or others did not understand, so I returned to check the relevant information and complete the details.
Explain it to others again in a simpler way, in an analogous way, in an easy-to-understand figurative way.
Many friends see this learning method for the first time, they will think that this is too simple, is not to repeat and repeat, is not to review.
Let's analyze where the essence of the Feynman learning method is and where the key points are.
Learning is basically mental activity, so before we can analyze it further, we must have a general understanding of what characteristics our brains have.
We can divide the human brain into 2 parts:
The animal brain, that is, the human consciousness, is part of our instinctive reaction.
The neocortex of the brain, that is, the prefrontal cortex of the brain, has the ability to calculate precise logic, and learning is mainly applied to this piece.
The weight of the human brain accounts for 2% of our human body weight, but the human brain consumes about 20% of the energy when it moves. To know that our brain evolved when we were monkeys in the jungle, it was a resource-scarce era, so the first mechanism of the brain is to use the brain without the brain, which is the default mechanism of the brain, called the "economic principle of thinking".
Therefore, in the evolution of 200-300 million years, the brain has compressed all the daily actions of the human body into a module of automated responses, which is our instinctive response, which is a rapid scene response.
We have computers today, you let the computer recognize whether a picture is a human face or an animal face, the computer has to go through a lot of calculations to get the result, and we let a child can quickly identify, this is the stake of our instinctive response, he is through 200-300 million years of genetic mutations and natural selection, the combination of this ability to evolve.
This instinctive response has the following characteristics:
It has undergone 2-3 million years of genetic evolution and has been compressed to the genetic level.
It is judged by analogy and quick analogy.
It is compressed into modules, embodied and stored in the brain.
The mobilization is energy-saving, fast, and basically does not require the active thinking process of the brain.
All animals have this type of instinctive response, and the instinctive response of primates is closest to that of humans.
The human brain neocortex, also known as the prefrontal cortex, is nearly 5,000 years or so before it appears, its emergence marks the beginning of human civilization, human beings have since begun to have the ability to understand the law, this is our precision logic computing ability, we give it a term called reason. In the words of computers, it is called algorithms, and in philosophical terms, it is called thought.
When human beings operate logically, they mainly use the ability of this piece.
Rational algorithms have the following characteristics:
He is only 5,000 years old, so there is no innate evolution, and the formation of any species requires millions of years of evolution.
Therefore, rational algorithms are difficult to mobilize, and even if they are mobilized, they also need a lot of training the day after tomorrow.
This kind of logical operation is extremely energy-intensive when mobilized.
Because the default mechanism of the brain is the "economic principle of thinking", the brain rejects active operations and rejects long-term high-load operations
Learning, using this piece of ability.
Combining the characteristics of these two parts of the brain above, learning is the process of using these two parts, our training for decades the day after tomorrow, some similar instinctive parts of millions of years of training, what does it mean?
The efficiency of the instinctual part is based on millions of years of genetic evolution.
The process of learning, similar to the evolutionary process of this gene, uses rational algorithms to package knowledge into our instinctive process.
We can understand that our computers today have memory and hard disks.
Memory is like a rational algorithm of the prefrontal cortex of the brain, and we give him a term here called "temporary workstation".
Hard drives are like the instinctive reactions of our animal brain parts.
Their roles are:
Memory is an indicator of the computer's computing power and working power, when working, all applications and temporary data, are running in the [temporary workstation].
His work intensity and ability to work are limited. After any program is run, the data is immediately stored on the hard disk, and when he exits the program, he immediately withdraws the temporary workstation so that other programs can come in and work.
And the hard disk, like our instinctive part, is where data is stored, and this data is stored in an organized manner according to certain principles, such as in the way of the library. In this way, the [temporary workstation] can call data from here at any time, and because it is arranged in advance, it can be called quickly.
The core capability of the [temporary workstation] is algorithms, algorithms need to be precise, one link at a time, so he is dedicated, single-threaded to ensure his precision.
[Temporary workstation] Every time a computing task is completed, the data is immediately stored in a figurative graphical way into the "hard disk" and stored according to some kind of orderly regulations. Then move on to the next task.
[Temporary workstation] in the operation, to consume a lot of resources, so he generally does not take the initiative to calculate, when encountering things, it gives priority to retrieving data from the "hard disk" to match the work, because this way is efficient and energy-saving.
Information that is not encoded by the Temporary Workstation is not stored on the "hard disk" because the "hard disk" is also limited.
Okay, the groundwork is complete, and we return to Feynman's method.
The essence of Feynman's learning method is to constantly force your brain to start the [temporary workstation] mode, that is, our rational logic operation mode, because the professor to others, in order to let others understand, you must become a law, especially his law is to ask you to tell a 10-year-old child, so you must make the knowledge points easy to understand.
The essence of this process of constantly consulting information, becoming legal, simplifying, and analogical is a process of forcing [temporary workstations] to encode, simplify, and store a knowledge point from various angles.
Others can't understand, then you have to change the perspective, or re-consult the data, this is the re-coding process, which is essentially different from the review, review is only a process of retrieving data from the "hard disk", [temporary workstation] does not take the initiative to work.
Passive learning features:
The knowledge point enters the [temporary workstation], because it is passive learning, the [temporary workstation] only calls up the resources of the original "hard disk" to match, because this is efficient and energy-saving.
Therefore, the knowledge points learned passively are not computed and actively encoded by [temporary workstations]. So it's easy to forget.
Professorial Learning Features:
Since it is ready to teach others, the temporary workstation is fully operational at the beginning, identifying, encoding, and then storing it in the "hard disk".
When the professor found Caton, he went back to re-consult the information, and ran the [temporary workstation] again to encode and store this knowledge point from another angle, and filled in the details that were missed for the first time. So the knowledge point that exists in the "hard disk" at this time is much clearer than the first time, much clearer, and even clear to the details.
In order to make the other party fully understand, or understand in an easier way, so run the [temporary workstation] again to recode the knowledge point, this time from another point of view, the previous 2 times feel complicated to remove, simplify the way, and even in order to make a 10-year-old child understand, you must make this knowledge point into a figurative story or example that is too simple to be simple
It is in such a process of constantly starting the [temporary workstation] to strengthen the knowledge point from a different angle, so that this knowledge point is finally packaged and compressed into an effective module, stored in the "hard disk", and can be called at a high speed and accurately.
In the mathematician's mind, the whole world is effectively encoded into formulas by him, and anything can instantly correspond to the modules in his brain that have been clearly encoded to form formulas.
Mental arithmetic, or blind chess that can play against dozens of people at the same time, is also the truth.
The core of this process is to make a knowledge point clear, and we must constantly force us to start the [temporary workstation] to the knowledge point, and become the angle of evolution coding and storage. This makes the subsequent call from the "hard disk", because the previous encoding storage is very clear, there are details, there are cases, so it can achieve more efficient mobilization, and longer storage, and even integration.
Passive learning By default, the [temporary workstation] does not actively encode the information, he just mobilizes the information from the "hard disk" to match.
Feynman himself was a physicist, a professor of physics at the California Institute of Technology, and a 1965 Nobel Laureate in Physics.
Feynman had a special ability to express complex principles in simple and simple language, to present profound physical ideas with clever analogies, and these methods and ideas of his were incorporated into his Feynman Lectures on Physics.
Interested readers can directly use the search box above today's headline app to enter "Feynman Physics Lecture Notes" to find the pdf document of the handouts.
This is a set of physical thought lecture notes that every friend who thinks about the mysteries of the universe should read.
Since his English name is fenyman, Chinese name is also called "Feynman"