Reposted from: WeChat Official Account [大华嘻游] (dahua0768) Most people may never have summarized and organized their own knowledge and experience, but in the actual process of doing things, they often follow a set of scientific methods and logic. In real life, we often meet such people: they have deep insights into a certain profession or field, see problems accurately, and have unique perspectives, but when you ask them how they do it, they can't explain why.
Street Wisdom and Scientific Method There are two types of talent: street wisdom and scientific method. Because I've found that awesome people in real life fall into two categories: One type is those who haven't read many books or had much schooling, but can run a business or a company well. When you ask them how they do it, they usually can't articulate it step by step; they can only roughly tell you some principles of doing things or dealing with people. For example, many entrepreneurs who didn't finish elementary school but are very successful in business, or street and folk artists, belong to this category. These people are not necessarily very smart, but they must have high comprehension. Although they can't summarize the scientific method of achieving success, their logic in doing things must follow scientific laws. Many bosses, after achieving business success, attend MBA courses at CEIBS or Cheung Kong Graduate School of Business and have a sudden realization, which is the reason. The other type is those who have received higher education and possess a complete set of scientific methods for doing things. When you ask them how they do it, they can analyze it for you step by step, with clear steps one, two, three, systematic and meticulous. For example, Ji Shisan, the founder of Guokr, is such a peculiar person. He has a PhD in biology. Before founding Guokr in 2010, he had always been doing experiments in the school's biology lab, with no social work experience. But he summarized a set of entrepreneurial methods from scientific experiments, and did quite well. From the initial Guokr, he incubated MOOC, Zaihang, and including the recent hot Fenda, valued at over 100 million USD.
Inductive and Deductive Methods There are two basic logical laws for understanding things and thinking: inductive method and deductive method. Induction goes from the specific to the general; deduction goes from the general to the specific. Inductive method: Conditions: My dog A likes to eat fish; Neighbor's dog B likes to eat fish; Dog C likes to eat fish; Dog D likes to eat fish; ... Conclusion: Dogs like to eat fish. Deductive method: Conditions: Dogs like to eat fish; My dog Ah Huang is a dog; Conclusion: Ah Huang likes to eat fish. We summarize experience and knowledge from past practice, and we use certain knowledge theories to guide the development of other things. In this process, knowledge is constantly changing, but the method of understanding knowledge is relatively stable, which is metacognition—the cognition of one's own cognitive process.
Metacognition In a broad sense, knowledge can be divided into five categories: data, information, knowledge, talent, and wisdom. Data becomes information when organized; information becomes knowledge when it can solve a problem; knowledge becomes talent through repeated practice; talent becomes wisdom when it is thoroughly integrated. Talent and wisdom belong to the category of metacognition. The construction from knowledge to a knowledge system is the construction of metacognition. For example: Many traditional brand copywriters rely on feelings. Many advertising people, when writing copy or coming up with creative ideas, require a certain environment and mood, otherwise they have no inspiration. This is nonsense. Later, Li Jiaoshou appeared, telling everyone that writing copy also has scientific methods. As long as you master scientific marketing methods, writing copy is like solving math problems—you can derive it by applying formulas. So traditional advertisers were stunned.
Why Build a Knowledge System The Meaning of Hard Work Genius is 1% inspiration and 99% perspiration, but the 1% inspiration is the most important. Whether Edison actually said the second half of this sentence is not worth pursuing, but it still doesn't stop many people from thinking so. This sentence emphasizes the importance of talent and inspiration, which are uncontrollable factors. In real society, you'll also find that many successful people say their achievements are 99% due to luck. Luck is also uncontrollable. So what is the meaning of hard work? Humans are born with a self-awareness to control their own destiny, which is the fundamental difference between humans and other species. So even if only 1% can be changed, we should not stop learning and working hard on non-luck and non-talent factors.
Any learning is enhancing one's controllable abilities On the basketball court, a person suddenly comes on who looks like a veteran. He changes direction, breaks through, lays up, Flowing like water — Unfortunately, the ball doesn't go in. Again, He gets the ball, maneuvers, quickly shakes off the defender, then stops and jumps for a shot, with a clean and neat shooting motion. The audience below is about to cheer and boil. — But the ball still doesn't go in. Strangely, despite missing both shots, these two attacks have already allowed us to conclude: he is extremely good at basketball, and scoring is only a matter of time. Some people miss two consecutive shots and still earn the evaluation of a "master." Some people make four or five consecutive shots, but everyone thinks "that guy is just lucky." So, where is the problem? The key is that he is stable, that is, controllable. His dribbling, breaking through, and shooting postures are very stable. No matter how you defend, his shooting rhythm, angle, and movements won't change much. He can control the rhythm of himself and the ball. But those who shoot accurately but are not great have different shooting movements every time. This makes people feel that each of his shots is due to luck. The same scene reminds me of the finals of the third season of "Qi Pa Shuo" between Jiang Sida and Huang Zhizhong. You'll find that Jiang Sida had many outstanding moments in this season, which is why he was recognized by his teammates to represent the Da Jin team in the finals. But in the finals, he was nervous and performed poorly. On the other hand, his opponent Huang Zhizhong just stably performed at his usual level and easily won. Comparing the experiences of the two, you'll find that Jiang Sida is an amateur debater, while Huang Zhizhong is a professional debater. Compared to Jiang Sida, Huang Zhizhong can more stably output debate under the conditions of the finals. So, the criterion for judging whether a person is great is—whether they can maintain stable output under any conditions. Why build a knowledge system? We all want to become great people. How to become great? Great people are those who can maintain stable quality output under any conditions. So, building a knowledge system is to solve problems stably and efficiently.
How to Build Your Own Knowledge System? This is a big topic. Many people on Zhihu and Fenda have asked this question, indicating it's a relatively common topic. Summarized, there are about six steps: goal, acquisition, extraction, output, aggregation, and expansion.
1. Goal: Knowledge architecture is a path to achieve a goal Acquiring knowledge must be to solve a certain problem or satisfy a certain curiosity. Solving problems is setting goals. Discussing building a knowledge system without a goal is a false proposition. We too much hope to find a set of ready-made standard answers. This is a thinking inertia long domesticated by China's institutional education. You can't defeat all problems in life and work by building a knowledge system, so the construction of a knowledge system must be goal-oriented. First have a life plan, then clear goals. To achieve goals, you need to build corresponding knowledge architecture. So knowledge architecture is a path to achieve goals. To achieve goals, what knowledge and skills need to be mastered, which professional fields to enter, and in these fields, how to learn in a categorized way and incorporate into your knowledge system. How to acquire knowledge, how to absorb knowledge, how to absorb, how to output—everything becomes clear around the goal, avoiding useless work.
2. Acquisition: Search online, ask people, read books, do it yourself After the goal is established, the next step is how to quickly acquire knowledge. On this point, I previously wrote an article: How to quickly build cognition of an unfamiliar field? ➀ Search online "Baidu it, and you'll know." Baidu is definitely the first teacher for young people today, especially for the post-95s and post-00s. It's their first reaction when encountering problems. Searching online allows you to browse vast amounts of information, quickly giving you a macro understanding of a problem, facilitating decisions and references for deeper understanding. One thing to emphasize is that you should be familiar with the attributes of each search engine and various portal sites, so searching is more efficient. For example, for some in-depth Q&A topics, you can search on "Zhihu"; for WeChat articles, use "Sogou"; Douban's book reviews and film reviews are more valuable than e-commerce sites. ➁ Ask people After having a macro understanding, the next step is to seek advice from professional experts. This is the fastest way to build cognition. If you don't have such people in your circle of friends, you can try to connect with experts on social tools like Weibo. Generally, if you've done your homework, your questions can get responses from experts. If that doesn't work, you can spend money to book on "Zaihang", or ask questions on Zhihu or Fenda. In the future, such paid knowledge Q&A and experience sharing platforms will become more and more, with a wide range of expert fields and lower thresholds. ➂ Read books Books are dead people, or people you can't reach with your current resources. Reading is communicating with experts. Book knowledge is generally systematic and thoughtful, allowing you to systematically understand something. You can browse quickly, read intensively, or even read repeatedly, depending on the problem and the book. Sometimes it's not necessary to finish a book; reading the parts related to your question is enough. Sometimes, for a certain problem, I'll buy five or six or even a dozen books on the market related to the topic, basically covering all issues in the field, and then find corresponding cases and methodologies based on the problem. ➃ Do it yourself There is no knowledge that applies to all scenarios, nor a methodology that can solve all problems. Recognizing the difference between the two is particularly important, and only by doing it yourself can you discover this. Many knowledge seems universal, but in fact it's not. Many methods and answers are realized through doing. Practice is a deeper understanding and recognition, and the greatest respect for knowledge.
3. Extraction: Remove the useless, clarify logic, modularize knowledge ➀ Remove the useless Every time we move into a new home, the room is clean and simple. Within a month, you'll find a lot of idle items or clothes in the room, and you start to not find where your things are. When you move again, you find you have so many things. Knowledge is like organizing items. Our brain is a room that receives various information and knowledge every day through mobile phones, computers, conversations, and sharing. If the knowledge in the room is not deleted and organized in time, and some things are not thrown away, the brain will be a mess over time. Even if it's knowledge you've learned, you won't remember it when encountering problems. Many times we read WeChat and browse Moments every day, receiving so much information, much of which is useless. Efficient people will deliberately block some information, and generally, experts have stronger abilities to filter and screen information than others. In a speech, the guest spoke for two hours, but only a few points were truly useful. So knowledge needs to be deleted and refined. The purpose of deletion and refinement is twofold: one is to find the key points, and the other is to facilitate memory. Only by remembering the key points can you be helped when encountering the same problem next time. Einstein said, Education is what remains after one has forgotten what one has learned in school. ➁ Clarify logic Why does the same guest's speech get better organized by Note Masters, and sometimes even the guest thinks it's better than his own speech? Besides removing filler words and topics that deviate from the speech theme, it's because Note Masters have sorted out the logical relationships of the content, divided and marked the primary and secondary, making it smooth to read, with clear priorities and obvious key points. ➂ Modularize knowledge Yang Ning, founding partner of Lebo Capital, shared his life philosophy in an internal sharing—"playing routines", which means he used the same routine to easily handle many problems, sometimes without thinking, and it worked every time. Including his two successful investment cases, he used the same routine. This routine is actually modularized knowledge. In life, we encounter problem 1, problem 2, problem 3, problem N. Most people will give a solution for each problem. But sometimes problems 1, 2, and 3 may be in the same knowledge system. As long as you find the underlying theory, you can solve all problems at the phenomenon level. So, to modularize knowledge, the best way is to use mind maps to organize these underlying theories or methodologies into knowledge modules one by one. In this way, when facing similar phenomenon-level problems, you can directly use the corresponding knowledge module to solve them. For complex problems, use multiple knowledge modules.
4. Output: Strengthen cognition, associate and reconstruct ➀ Strengthen cognition The process of output is the process of practice, the process of turning others' knowledge into your own, and the process of knowledge from theory to practice. You cannot cultivate a practical habit from thinking; you can only cultivate a thinking mode from continuous practice. Knowledge is the same; it must be output, that is, sharing, communicating, and practicing. Otherwise, it's dead knowledge and useless. For example, taking notes, writing articles, making products, sharing, communicating, practicing, etc., are all outputs. They help strengthen the original knowledge modules, and in the output process, many people will ask questions or communicate, which is also a rethinking and testing of the original knowledge modules. The reason why China's university education is disconnected from the workplace is that it is a "playground mode" that starts from theory and ends at theory. The essence of playground mode is composed of some established play items, each with a defined starting point, path, endpoint, and duration. In the playground, games are predictable, and you are in a series of false challenges. ➁ Associate and reconstruct Another output method of knowledge is association and reconstruction. Knowledge is not simple accumulation, but the creation of associations; otherwise, it cannot form a system. Professor Li Shanyou associated quantum mechanics in physics with enterprise management and output the internet thinking. Luo Pang's New Year's speech last year, if carefully analyzed, you'll find that the core viewpoints are actually quoted from others, traceable to a certain person's thought in a certain book. For example, the main theme throughout the speech, "understanding modern business with biological thinking", mainly comes from three books by three people: Visa founder Dee Hock's "Birth of the Chaordic Age", Kevin Kelly's "Out of Control", and Wang Dongyue's "The Theory of Evolution". But Luo Pang cleverly connected these thoughts and viewpoints, and associated them with many current business events last year. Listening to the full four hours, people didn't feel bored, but instead had their minds opened. As the saying goes: All knowledge is copied; it depends on how you copy.
5. Aggregation: Classify, decompose, re-aggregate, establish order and system To completely build a knowledge system, you must experience the decomposition and re-aggregation of knowledge. The decomposition and re-aggregation of knowledge is a cyclic iterative process from theory to practice to theory. Knowledge modules in the same field, when classified and combined, form a knowledge system. To ultimately integrate multiple knowledge systems, you must go through a lot of practice. This is because the establishment of a knowledge system is driven by practice and problems. Problems and practice can decompose the points in the original knowledge modules, and these points are continuously reconstructed in the practice of solving problems. Then, through summary and induction, you think about how to abstract from the bottom up to form a complete knowledge system in a certain field. For young people who haven't built many knowledge modules, it's not recommended to directly refer to others' complete knowledge system diagrams for systematic learning. It's best to start from practice and problem-solving to build knowledge modules. The paid audio "Good Talk" created by the "Qi Pa Shuo" team is selling well on Ximalaya recently. You'll find that the 6-minute voice every day is aimed at a problem in a specific scenario. All knowledge points are finally summarized into five-dimensional speech abilities: speech, communication, persuasion, negotiation, and debate, ultimately forming a knowledge system of speaking. All scenarios and problems solved by knowledge points are within this speaking knowledge system. And the underlying theory of this speaking system summarizes research results from multiple disciplines such as communication, linguistics, psychology, advertising, business, and philosophy. From this, it can be seen that science and philosophy are the two main sources for obtaining metacognitive theory. So, to gain metacognition, it's best to read some academic works.
6. Expansion: Build systematic thinking beyond the boundaries of knowledge The essence of building a knowledge system is actually building systematic thinking. Generally, at this step, the knowledge system is basically complete. But human thinking has boundaries and loopholes. The above five steps can establish a logically self-consistent knowledge system, but they also cause limitations in thinking. For the most common things, we are very familiar with them. Through interaction with them, we form experience and skills, but we are also ignorant of them. We live with them in an ignorant way. It is our "familiar but unknown world." In fact, we all live in this world with the illusion of a "familiar and known world." We hardly think about the possible "unfamiliar and unknown world", and at the same time mistakenly think that what we encounter is already under control. This illusion locks us in a narrow intellectual area, turning a blind eye to a broader world. Three basic characteristics of our education system determine that it can only cultivate mediocre people most of the time: One: Cultivating talents in an "assembly line" manner This assembly-line talent production method is an economical and efficient education method, but it often comes at the cost of smoothing the edges of students' individual interests and talents. Two: Screening talents in a "standardized" manner There is a concept called "standardized testing", which is to define the various processes of assessment as precisely as possible to minimize errors and maximize uniformity. Knowledge that is easily standardized and certain becomes the focus of assessment and teaching, while things that are difficult to standardize, requiring deep thinking, controversial discussion, and subtle appreciation, are all avoided. Three: It only satisfies the inheritance of abstract knowledge and ideas Many university undergraduate educations organize teaching with the idea of being a preparatory class for cultivating scientific research talents, only completing theory to theory, lacking the practice link. The environment has the greatest impact on a person's systematic thinking and values. Most people find it difficult to jump out of the concepts instilled by their family environment, growth history, and social circles. The books they read later, the things they experience, and all their thinking only reinforce the rationality of the values they firmly believe in. Unless experiencing major changes, people's ideas are extremely difficult to change, and we sometimes find it hard to realize this. So, contacting more people with different growth environments, listening to more completely different ideas, and understanding these things with a peaceful mindset is a better way to build an excellent systematic thinking and values.
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