In 1946, merican scholar Edgar Dyer proposed the "learning pyramid" theory. Later, the National Training Laboratory in Maine also released the "Learning Pyramid" report through experiments. The report said that human learning can be divided into passive learning and active learning. Passive learning: Activities such as listening, reading, audio-visual, and presentation have an average retention rate of 5%, 10%, 20%, and 30%. Active learning: Increase the retention rate of passive learning to 50%, 75%, and 90%, e.g. through discussion, practice, and teaching to others. At present, there are a lot of listening products. Readers can interpret a book in ten minutes. If we listen to one book a day, we can listen to more than 300 books a year. The better case is to read the original book, but if you finish the book without looking back, thinking about it, only content with input process, this kind of learning knowledge retention rate is very low. A few days later, I can't remember what I read. What's worse, this kind of effort can lead people to blindly pursue the speed and quantity of reading, and create a sense of diligence. In fact, this is a low level of diligence. The more you invest, the more you lose. There is also a large group of people. These people can read by themselves and take notesA or mind maps, but unfortunately their notes tend to be more of a synopsis of the book than an outli

ne. Many people are obsessed with this, and seem to know the knowledge of the book, but they do not know that they just did a simple handling work. Although this practice belongs to active learning to some extent, it is merely a simple statement of knowledge, which is quite different from high-level knowledge transfer. On a deeper level, after reading the book, you can practice the truth in the book. Even if there are one or two things that make your life change, it is also great, because from this moment on, the knowledge in the book has been transformed. It is a great step to go from knowing to doing, but it is one thing to know or do it yourself, and quite another to let others know or do it. Try to articulate what you know to others. You will find that it is not easy. You know what you're thinking, but when you talk about it, you start talking incoherently. What if you were asked to write down what you know? You may find it impossible to write. Notice that deep learning really begins when you encounter this difficulty! Because you have to use existing knowledge to explain new knowledge, when you can explain new knowledge, means that it is included in your own knowledge system, and at the same time to teach others, and possibly create new knowledge. Luo Zhenyu once said that he studied like this: "I required myself to write five reading essays every day, not long ones, but just a few words. Because real learning is like sewing buttons, sewing new knowledge into the original knowledge structure. Writing five reading articles every day is to force the original knowledge structure to react to the new knowledge, and then solidifying these reactions in words, and the sewing process is complete." It can be seen that "jointing" is the key to deep learning, and most people only complete "acquiring knowledge", but ignore the step of "jointing knowledge", so their learning process is incomplete. Some people do a certain amount of stitching, but the stitching is not deep enough, there is no high-quality output, and the depth of learning is greatly reduced. Shallow learning meets input while deep learning focuses on output. From idea to language to text, turning a network of thought into a tree and then into a linear text is equivalent to turning thought from a gas into a liquid and then into a solid -- the solid things are truly their own. After all, any knowledge will inevitably lose, and this loss has always existed, if you do not want to fix what you learn, for a long time, these knowledge will disappear, leaving no trace. When you have something of your own, you must teach it out. The professor and the stitch will consolidate each other and form a cycle. Liu Weipeng, the author of Dark Time, said: "Teaching" is the best "learning". If you can't explain something clearly, nine times out of ten you haven't fully understood it. Of course, the highest level of teaching is to make a layman understand what you are saying in the simplest possible words. Therefore, the way to deep learning is to force oneself to acquire high-quality knowledge, to deeply sew new knowledge, and then to teach others in one's own language or text.

In 1946, merican scholar Edgar Dyer proposed the "learning pyramid" theory. Later, the National Training Laboratory in Maine also released the "Learning Pyramid" report through experiments. The report said that human learning can be divided into passive learning and active learning. Passive learning: Activities such as listening, reading, audio-visual, and presentation have an average retention rate of 5%, 10%, 20%, and 30%. Active learning: Increase the retention rate of passive learning to 50%, 75%, and 90%, e.g. through discussion, practice, and teaching to others. At present, there are a lot of listening products. Readers can interpret a book in ten minutes. If we listen to one book a day, we can listen to more than 300 books a year. The better case is to read the original book, but if you finish the book without looking back, thinking about it, only content with input process, this kind of learning knowledge retention rate is very low. A few days later, I can't remember what I read. What's worse, this kind of effort can lead people to blindly pursue the speed and quantity of reading, and create a sense of diligence. In fact, this is a low level of diligence. The more you invest, the more you lose. There is also a large group of people. These people can read by themselves and take notesA or mind maps, but unfortunately their notes tend to be more of a synopsis of the book than an outli

ne. Many people are obsessed with this, and seem to know the knowledge of the book, but they do not know that they just did a simple handling work. Although this practice belongs to active learning to some extent, it is merely a simple statement of knowledge, which is quite different from high-level knowledge transfer. On a deeper level, after reading the book, you can practice the truth in the book. Even if there are one or two things that make your life change, it is also great, because from this moment on, the knowledge in the book has been transformed. It is a great step to go from knowing to doing, but it is one thing to know or do it yourself, and quite another to let others know or do it. Try to articulate what you know to others. You will find that it is not easy. You know what you're thinking, but when you talk about it, you start talking incoherently. What if you were asked to write down what you know? You may find it impossible to write. Notice that deep learning really begins when you encounter this difficulty! Because you have to use existing knowledge to explain new knowledge, when you can explain new knowledge, means that it is included in your own knowledge system, and at the same time to teach others, and possibly create new knowledge. Luo Zhenyu once said that he studied like this: "I required myself to write five reading essays every day, not long ones, but just a few words. Because real learning is like sewing buttons, sewing new knowledge into the original knowledge structure. Writing five reading articles every day is to force the original knowledge structure to react to the new knowledge, and then solidifying these reactions in words, and the sewing process is complete." It can be seen that "jointing" is the key to deep learning, and most people only complete "acquiring knowledge", but ignore the step of "jointing knowledge", so their learning process is incomplete. Some people do a certain amount of stitching, but the stitching is not deep enough, there is no high-quality output, and the depth of learning is greatly reduced. Shallow learning meets input while deep learning focuses on output. From idea to language to text, turning a network of thought into a tree and then into a linear text is equivalent to turning thought from a gas into a liquid and then into a solid -- the solid things are truly their own. After all, any knowledge will inevitably lose, and this loss has always existed, if you do not want to fix what you learn, for a long time, these knowledge will disappear, leaving no trace. When you have something of your own, you must teach it out. The professor and the stitch will consolidate each other and form a cycle. Liu Weipeng, the author of Dark Time, said: "Teaching" is the best "learning". If you can't explain something clearly, nine times out of ten you haven't fully understood it. Of course, the highest level of teaching is to make a layman understand what you are saying in the simplest possible words. Therefore, the way to deep learning is to force oneself to acquire high-quality knowledge, to deeply sew new knowledge, and then to teach others in one's own language or text.