Importance of deep learning and learning strategies

People's deep learning capabilities are increasingly scarce. In that era when technology and information were far less developed than today, limited learning conditions forced people to calm down and turn to this kind of deep learning.

Humanity has entered an era of unprecedented abundance of material and information. Novel, interesting, light and condensed knowledge can be seen everywhere. What people worry about is no longer the lack of knowledge to learn, but the inexhaustible knowledge. Today, I am afraid that few people can take the initiative to calm down and study in depth. Many people even believe that learning in the current era does not have to be so "hard and arduous".

There are so many ways that people can easily acquire knowledge. For example, listening to a book every day, participating in the online class of the great people, subscribing to a famous column, or participating in a certain learning group... It is easy and efficient, full of dry goods, as long as you persevere, you will be able to achieve success. Unfortunately, this perception is doomed to be an illusion. Because technology and information have changed dramatically in our generation, human learning has not changed rapidly, and our brains work almost exactly the same as they did a hundred years ago.
The worse news is that while "rich information and diverse methods" bring convenience, they also deeply deplete people's ability to "deep learning", and this tendency is becoming more and more obvious. There are various indications that the fast, simple and easy way has further strengthened people's low-level "primitive brain" functions, while the high-level "modern brain" functions have been further weakened. And deep learning capabilities, almost all rely on high-level "modern brain".

The reality is that the more people learn, the more anxious they become, the more impetuous they become, and they understand a lot of truth, but they still cannot live well now, let alone their whole life.
I vaguely see that the world is moving towards two poles: A small number of intellectual elites still face the core difficulties, and work hard to deeply study and produce content; The vast majority of information audiences enjoy light learning and consume content. Just as the social class is gradually solidified, the intellectual class is also gradually solidified. If you are stuck in wrong cognition for a long time or are accustomed to light learning, once you lose your deep learning ability, it will be difficult to break the limit of the intellectual class, and you will always be trapped in the low level of cognition.
If we really want to occupy a place in the trend of the times, we should abandon the illusion of easy learning as soon as possible, temper the ability of deep learning, go upstream and become scarce, otherwise the road of life will inevitably become narrower and narrower.

What is deep learning?

In 1946, American scholar Edgar Dale put forward the theory of "Learning Pyramid" (Cone of Learning). Later, the National Training Laboratory in Maine, USA also did the same experiment and released the "Learning Pyramid". "Report.
According to the report, human learning is divided into two levels: "passive learning" and "active learning". Passive learning: such as listening, reading, audition, and demonstration, the average retention rate of learning content is 5%, 10%, 20%, and 30%.
Active learning: For example, through discussion, practice, and teaching to others, the retention rate of the original passive learning content can be increased from 5% to 50%, 75% and 90%.
This model nicely shows the contrast between different learning depths and layers.
The learning that is convenient, novel, and concentrated dry goods seems to be easy and efficient, but it is actually at the shallowest level of passive learning. A better situation is to read the original book by yourself, but after reading it, you don’t review or make a little summary, and you are only satisfied with the input process. The knowledge retention rate of this type of learning is very low.
Can't you remember what you read after a few days?
To make matters worse, this effort can lead to a blind pursuit of speed and quantity of reading, creating a sense of diligence, which is actually a low level of diligence, and the more invested it is, the greater the loss. Beginner readers will inevitably step into these two pits, and there are also a lot of people who learn the other kind of shallow level. Such people can read by themselves, and also make reading notes or mind maps, but unfortunately, the content of reading notes is often a list of the contents of the book, which looks more like an outline.
Many people are fascinated by this, as if they have the knowledge of the whole book, but they don't know that they are learning. We do not produce knowledge, we are just knowledge porters! Although this approach is to some extent active learning, it is simply a "knowledge statement" and is very different from a high-level "knowledge transfer". On a deeper level, it is amazing to be able to practice the principles in the book after reading, even if there is one or two points that change your life, because from this moment, knowledge has been transformed.
Going from knowing to doing is a huge step forward, but knowing or doing it yourself is one thing and letting others know or do it is another.
If you don’t believe me, try to tell others clearly what you know. You will find that it is not easy. You can think clearly in your heart, and when you speak, you will start to incoherent. What if you are asked to write down what you know? You may not be able to write at all.
Note that this difficulty is where real deep learning begins!
Because it must use all the existing knowledge to explain the new knowledge, when you can explain the new knowledge clearly, it means that it has been incorporated into your own knowledge system, and at the same time has reached the level of teaching others, and may create generate new knowledge.
In addition, some people have a certain amount of stitching, but the stitching is not deep enough, and there is no high-quality output, which also greatly reduces the depth of learning. Shallow learning satisfies the input, while deep learning focuses on the output.
From ideas to language to words, that is, the net-like thinking turns into a tree-like structure and then into linear words, which is equivalent to changing the thought from a gaseous state to a liquid state to a solid state—those solid things really belong to themselves.
After all, any knowledge will inevitably be lost, and this loss will always exist. If you don't want to make what you have learned solidify, it will disappear over time, leaving few traces. If you have your own things, you must "profess" to go out, and "professor" and "suture" will consolidate and circulate each other. This is the highest level of deep learning I'm aware of right now, and maybe more advanced, but for the vast majority of people, it's enough to be able to do it and do it well.

How to learn deeply?

As above, deep learning has three elements: Acquire high-quality knowledge; stitch new knowledge in depth; export results to teach. Such learning will inevitably give up the sense of security of "learning fast" and "learning more", at the same time it will take more time, face a more difficult situation, and even "suffer it". But please believe: the right actions are often counter-intuitive, things that are comfortable and easy at the beginning often don’t yield good results, and things that are uncomfortable and difficult at first can really yield results. So, we need to gradually improve.

• Obtain and read first-hand knowledge as much as possible. From the perspective of reading, it means reading classics, reading original works, and even academic papers. The classic first-hand knowledge has been accumulated over time, and the depth of its value has been proven, which is worthy of intensive reading. Focus on the first-hand knowledge that meets your needs, and give up the dry fantasy of "reading it in a few minutes...", "one book a day..." and "ten...classes", although those can also bring some inspiration, But after all, it is fragmented and chewed.
  Although it is more difficult to read it in person, only by experiencing it in person can you feel the real pleasure of deep understanding or cognition, which is many times more enjoyable than absorbing second-hand knowledge. It’s best not to ask someone to replace you with reading. In the long run, you must acquire the ability to mine yourself, so that you can go further.

• Write what you have learned as much as possible in your own words. Every time you read a good book of value, you use the way of writing to reconstruct the author's thoughts in your own language. Do your best to explain and extend based on your own experience, knowledge, and perspective, rather than simply listing the main points of the book. A simple "knowledge statement" cannot achieve the effect of deep stitching. Only by doing "knowledge conversion" can new knowledge be deeply stitched with the old knowledge system.
  So when refactoring, take only the most needed viewpoints, and discard other irrelevant viewpoints, even if they make sense. Really in-depth good essays often have little to do with the original book. It’s just that the original book triggered thinking and cited cases. In the end, it seems that the reading notes are often a brand new article, and even create new knowledge. This process is asymptotic. Although it seems to be someone else's point of view at the beginning, it will gradually derive one's own point of view. Although it will be difficult at first, as long as you keep practicing, you will have more and more experiences, viewpoints, and cases that you can relate to, and your thinking on a topic will become more and more in-depth.
  So there is no need to be fast, ask for more. If necessary, take enough time to polish a theme or point of view. When a piece of work that is close to your current best level impresses others, the impact and harvest are far stronger than writing every day without deep thinking. I encourage everyone to write because once you can write clearly, you must be able to speak clearly. Moreover, the article has a compound interest effect and can be read by others at any time, which indirectly achieves the purpose of discussing, communicating and teaching others.

• Reflect on your life. Learning is not only about reading, but life experience can also be learned in depth. The things that happen every day in our life pass through us like a stream of water, and they will not stay. If we are not careful, it will be difficult to leave traces. Just like passive learning at the shallowest level, the retention rate is very low, and it is difficult for a life without reflection to produce depth.
  Continuous reflection has made my perception of the details of life stronger and stronger, and life has left me more and more things. Perhaps the idea and concept of this article have many elements that also come from daily reflection. If I had to recommend an indispensable habit, I would push reflection.

The benefits of deep learning
In addition to allowing us to give up impetuousness and hone our reason, deep learning can also bring many benefits, such as cross-border capabilities.
In the book "What is the possibility of your life?" Classical said that human ability is divided into "knowledge, skills and talents".

• Knowledge is the least transferable. Even if you read a doctor of medicine, you will still not be able to fry an egg.
• Skills are usually composed of 70% general skills and 30% professional skills, and the transferability is better;
• At the talent level, the boundaries between occupations are completely broken.
  This explains why those great people can easily cross-border between fields. Because they have reached the level of talent in one field through deep learning, and these talents are also applicable in other fields, it only takes a small amount of time to become familiar with the knowledge and skills to play.

But on the other hand, if you never reach the talent level in one field, when you switch to other industries, you can only start over with the knowledge and skills at the bottom, which is very laborious.
Deep learning can help people cross boundaries, no doubt, and it can also help people generate inspiration. We all know that Einstein was on his way to work at the patent office. When he saw the Bernier clock tower, a hypothesis suddenly popped into his mind: "If a bus is moving at the speed of light, then the hands of the clock tower will not be seen from the bus. Will it be still?" This assumption made the greatest discovery of the 20th century, the special theory of relativity, into people's field of vision.
Another German chemist, Kekule, was very tired and had a daydream about a snake biting head to tail. This snake became a clue to his discovery of the molecular structure of benzene. People marvel at the intuition and inspiration of scientists, but if Einstein was a hairdresser and Kekule was a plumber, they wouldn't get that intuition and inspiration.
Because inspiration can only manifest with the help of the subconscious when they have explored enough in their own field, these principles have been confirmed in modern brain research. Although we are not scientists, deep learning can still give people a higher probability of harvesting unexpected surprises. At the same time, deep learning allows us to look down from above, see more connections in general, generate insights, and accumulate more and react faster.
For example, when I deeply interpret "Beyond Sensation", I know the correct thinking. The core of the test is to keep my subjective cognition as consistent as possible with the objective world. Suddenly, I have a new understanding of the words "emancipate the mind and seek truth from facts".
It turns out that our party has always been doing this, and looking at the development of the motherland in recent years, such a big fact has proved that this truth is extremely correct and important, and I would definitely not see this connection in the past.
Not only that, if you have accumulated enough cognitive depth in some fields, you can also mobilize advanced cognition, even in the face of things like film and television programs, entertainment gossip, and news hotspots that "corrode" people's attention. They are associated with useful thinking, producing insights that are deeper and more unique than the crowd.
By extension, hot entertainment is not without value, and superficial knowledge is also meaningful. But the premise is: you need to have enough cognitive depth first - the breadth below the depth is effective.

Focus on deep learning while remaining open to shallow learning. How should books and other products be treated? Totally reject or stay away? I don't think it is necessary, because deep learning and shallow learning are not in conflict, and shallow learning also has its value. The important thing is not to engage in the anti-weight relationship. We can use it as an entrance to learn new information, but we can't pin all the growth process on it.
A more reasonable attitude is: focus on deep learning while remaining open to shallow learning. Pick some people to follow and stay connected with them through these platforms. Some of the valuable information they release will lead us to the wider world, but in the end it's up to you to read, think, and do it yourself anyway.

Like this article, if it touches you, it's just for you. Opened up a new perspective. In the end, whether you can acquire deep learning capabilities can only rely on your own actions, and no one can replace it.

Thank you for your time. See you at the next.