“A remarkable work that is both broad and deep, truly eye-opening. The author has delved into different dimensions and contexts of learning with clarity and depth. The book discusses how to learn, what to learn, and how to act, with rigorous structure, vivid cases, and strong readability. Many viewpoints are refreshing. It is both a concrete presentation of how the author conducts ‘output-based learning’ and an invitation for readers to begin their own journey of thinking and learning.”
— Xie Ping, Former Dean, Huiyan International College, Faculty of Education, Beijing Normal University

“Learning and education are not particularly deep disciplines... This book uses output-based learning theory as a framework to systematically connect and deeply analyze all these most important consensuses. It has a commanding comprehensiveness and an accessible readability. It is like a ‘learning Windows system’—every brain needs to install one, and the sooner the better.”
— The Author

“Very practical and to the point. Far better than dry explanations of how to study. Especially useful for those who work hard but cannot find the way in.”
— Xiao Xiao, Reader

★ Ranked No. 1 on Zhangyue‘s e-book new book list, No. 1 in social sciences and arts, and No. 5 on the overall hot list upon launch.
★ It distills output-based learning as the underlying logic of effective learning and systematically establishes the theory of output-based learning. Addressing the three questions of learning—how to learn, what to learn, and why learn—it comprehensively explores various learning methods. It integrates the latest learning theories and brain science research from around the world, organically weaving in knowledge from philosophy, physics, mathematics, literature, history, and economics.
★ Using vivid metaphors such as military commanders, mobile phone contacts, and brick-laying, it breaks down the principles of learning thoroughly. The book proposes several new viewpoints, such as interest being a biological energy allocation mechanism and the law of conservation of brain activity.

Through effective learning methods such as the Feynman Technique and Cornell Notes, as well as the learning insights and practices of renowned figures including Einstein, Schopenhauer, Liang Qichao, Yang Zhenning, and Yau Shing-Tung, combined with cognitive science and neuroscience, this book distills keywords such as output, reorganization, meaning, interest, thinking, and neural connections, and systematically analyzes the internal mechanisms of learning.

Furthermore, the book argues that what we should learn is a meta-question more critical than how to learn. Through interesting topics such as “What Exactly Is Einstein Saying?”, “What Traits Do Geniuses Have?”, “Are We Smarter Than the Ancients?”, and “The Gains and Losses of School Education,” it vividly explores truly important abilities such as creative thinking, questioning, imagination, and critical thinking, and offers concrete, practical learning suggestions.

The book draws examples from physics, mathematics, philosophy, history, economics, literature, and many other disciplines. It is a thorough, comprehensive, vivid, and concrete learning guide, aimed at helping learning enthusiasts, especially young people, break the stereotype of learning—learning is far more than exams and advancing to the next grade. It helps readers truly understand the essence and joy of learning, and apply what they learn for their own benefit.

Liu Shaohui
Graduated from the Department of Journalism, Southwest University. Publisher‘s editor. Long devoted to researching the internal mechanisms of learning.

A Metaphor to Help You Understand the Underlying Principles of Learning
— Output-Based Learning: The Secret of Efficient Learning

Learning is a process of output, reorganization, and refining meaning, ultimately achieving the privatization of public knowledge.

First, let me introduce a learning method: output-based learning—that is, learning knowledge through teaching others, discussing with others, recalling knowledge, drawing mind maps, critical reading, applying knowledge, thinking, writing, and other forms of outward output. This can be said to be the most efficient and the only effective learning method. Why? Let’s look at a scene from the TV drama Towards the Republic.

In Towards the Republic, Prince Regent Zaifeng dismissed Yuan Shikai, with whom he had conflicts, and established an imperial cabinet. Royal nobles took key positions such as Navy Minister and Army Minister. But soon the Xinhai Revolution broke out, and Army Minister Yinchang could not command the Beiyang Army that Yuan Shikai had built. Zaifeng had no choice but to recall Yuan Shikai. Here is the question: why could Yinchang, who was the head of the army, not command the Beiyang Army? And if he wanted to change this situation, what should he do? Some friends who know history might say: because the generals of the Beiyang Army were all promoted by Yuan Shikai and did not recognize Yinchang. And if Yinchang wanted to truly control this army, he should replace the key senior generals with his own people. The answer is indeed so. In feudal times, the structure of an army was often organized by its leader according to the closeness and friendship (and of course ability) of subordinates. A new leader had to readjust the structure centered on himself to fully control the army—if necessary, even creating new positions, adjusting the weight of certain positions, or even breaking up the organization and rearranging it. In addition, you need to build prestige among mid- and lower-level officers and even soldiers; spend time with this army, frequently show your face and give speeches in front of grassroots officers and soldiers, and at least become familiar with everyone from top to bottom. Ideally, you would have fought together, shared life and death, and secured military honors for everyone—then you would have established a flesh-and-blood connection with this army and could command it freely.

What I want to say through this discussion is that the same principle applies to our mastery of knowledge. For example, if you copy knowledge into a notebook, or simply memorize it completely in your head, and declare it your knowledge—or if you like, you can even declare knowledge you just read on Baidu Baike as yours. But this is useless. It is just like being an empty Navy Minister or Army Minister: without reorganization, without “having worked with this knowledge,” you cannot effectively call upon it when needed. Other people’s language, even if you memorize it, is still theirs; other people’s thinking and logic are also hard to take root in your brain. To truly master a piece of knowledge, just like reorganizing an army centered on yourself, you must break other people’s language and logic, reorganize language and logic with your own thinking, replace the concepts of knowledge with your own understanding, and rebuild the network centered on yourself—for example, when reading an author’s “first… second… third…,” I often silently note it in my mind as “one… two… three…,” which is reorganizing according to my own thinking habits. Similarly, just as you lead this army into battle, you need to call upon this knowledge as much as possible to become more and more proficient in mastering it. To extend this: why are articles we write ourselves and insights we think of ourselves not easily forgotten even after many years? Because they are generated from within, with a neural basis, like an army we “built with our own hands,” and are easy to call upon even years later.

This is the underlying principle of why output-based learning is effective—output is actually a form of forced digestion. When outputting (for example, when we need to teach knowledge to others), we have no choice but to reorganize language and logic, unconsciously replacing the concepts and logic of knowledge with “our own trusted aides” (our own understanding), thereby truly mastering the knowledge. In addition, output strengthens memory by extracting knowledge and promotes connections and networking between knowledge in the brain. In short, if you fully grasp this metaphor, you have thoroughly grasped learning. And all the popular learning methods on the market—such as the Feynman Technique, Cornell Notes, mind maps, deliberate practice, the Simon Learning Method, the Learning Pyramid, various reading methods and memory techniques—all effective learning methods, no matter what they are called, ultimately boil down to output-based learning.

Next, let’s look at a joke that was once very popular: “Look at your phone contacts and you’ll know why you’re not doing well. Other people’s phones have Section Chief Sun from the Construction Committee, Director Li from the Municipal Office, Bureau Chief Wang from the Planning Bureau, Boss Cui, Boss Zhao… while my phone has Cement Zhang, Zhao the Mixer, Wang the Stone…” What I want to discuss is not the joke itself, but why our phone contacts are stored this way. Why not store a complete name? Wouldn’t that be more precise? In fact, what this joke reflects is the way we organize information—we organize information by meaning. Just like when we save the phone number or WeChat of the print shop owner at the entrance of a residential compound, the note is often “East Gate Print Shop,” not the owner’s full name. Because the print shop is meaningful to us, the owner’s name is meaningless. Therefore, everyone’s phone contacts are often understandable only to themselves, and there are certainly many strange names that others cannot understand at all. And our mastery of knowledge is the same—knowledge, as a kind of information, is also grasped through meaning. Just like the names in phone contacts, this meaning is private and must be actively processed by each person—if you cannot process knowledge with this kind of private meaning, this knowledge will be like those complete but unfamiliar names in your phone contacts: after a while you won’t be able to tell who is who, and it will be difficult to remember, understand, or effectively call upon. For example, if you introduce Xiang Yu, a Chinese historical figure, to a European, and you explain him according to the knowledge in history books, the other person may not understand or remember after a long explanation. But if you say, “This is China’s Napoleon,” the other person immediately understands: ah, this is a tragic hero of China, and easily remembers it. This is because the knowledge has been processed according to meaning. Therefore, the process of output and reorganization is actually a process of processing knowledge through meaning. That is, according to one’s own understanding, endowing knowledge with private meaning, and turning public knowledge into a kind of private knowledge.

Finally, to summarize: the essence of output is reorganization, and the essence of reorganization is refining meaning. And learning is a process of output, reorganization, and refining meaning, ultimately achieving the privatization of public knowledge. This can be said to be the most precise definition of learning from the perspective of how to learn. Every student should memorize it and ponder it thoroughly.