Classification of knowledge
Knowledge is a collection of facts about the world and procedures for resolving problems. The former is narrative knowledge, while the latter is procedural knowledge。
Narrative knowledge, including symbols, concepts, propositions, etc
Knowledge that describes the characteristics and relationships of objective things and answers “what the world is”, also known as descriptive knowledge. It includes knowledge of the conscious memory and representation of humankind, including symbols, facts and organized subject matter knowledge。
Procedural knowledge: knowledge of how to do things
Procedural knowledge is essentially a set of operating rules or procedures that govern the behaviour of a person and is an answer to “what to do”. It is only when problems are solved that they can be reflected or described。
Strategic knowledge: procedural knowledge to facilitate the search for the best options
Strategic knowledge is a specific type of procedural knowledge that is specifically designed to regulate, direct, address individual internal memory, think about what to do. It is characterized by the observation, supervision, guidance and adjustment of internal memory and the functioning of thinking. Through monitoring and adjustment, one can avoid mistakes or find better ideas。
"the solution lies in the interaction of three kinds of knowledge."
The solution to any problem involves the development of procedural knowledge to solve the problem, using the theoretical knowledge stored in the brain, and continuous monitoring and adjustment of procedural knowledge to obtain the best and most scientific solution to the problem that is more appropriate to the current situation。
The transformation of narrative knowledge to procedural knowledge is an important stage in learning. At the learning and application stage, narrative and procedural knowledge interact in many ways. In solving problems, not only narrative and procedural knowledge, but also strategic knowledge, must be used。
Basis of the system
A clear understanding of basic concepts is the cornerstone of the knowledge structure
The stability of the linkages between concepts determines the strength of the knowledge structure
"cognitive structure."
The key to learning is to link new concepts and existing cognitive structures. (assimism theory)
"learning takes place at different levels."
The expression of learning — that is, learning the meaning of a single symbol or vocabulary。
Conceptual learning - the extraction of the common essential attributes of one type of thing by way of a summation, the concept being the abstraction of a particular type of representation。
The first theme learning is to capture the ideas and meanings expressed in a set of terms that make up the subject or sentence。
The concept corresponds to the various elements of the existence of the real world, and the proposition encompasses the relationship between the various elements, and the theory is the structure of the relationship of the various elements。
This structure is the model — a structure that characterizes the relationship between the elements. (it is also a psychological manifestation. I'm not sure
Multi-dimensional thinking models are all kinds of narrative memories that are sufficiently robust, stable, clear concepts, propositions, theories. It allows you to map the patterns of the world from different angles, from different directions, from one layer to another。
Building a knowledge system for disciplines
Knowledge systems should be built on a point-to-face step-by-step basis, starting with an enlightening body of knowledge from a broad perspective, then going deeper and deeper into the framework, and finally digging into and reshaping the links between knowledge and creating its own unique knowledge system。
The process of building knowledge systems
Points: collection from a wide range (inspired knowledge points)
Face: build a deep knowledge structure
Organism: deep exploration and re-engineering of the links between knowledge to build knowledge systems
Knowledge point - > knowledge structure - > knowledge system
1. Extensive collection of instructive knowledge
First, it is difficult to understand that knowledge systems are a network, without sufficient knowledge points. The second knowledge point needs to be constantly validated and must be entered in large quantities. Connections and validations are made between them。
A. Wide collection of inspirational knowledge points (theory + case) and inspirational knowledge points to generate strong linkages
Existing knowledge systems
• explain in their own language
• extract when required
Practice or use it often in life
Example: why do people have emotions
Theory: emotion is the "fast path" of the human brain system
Case: it's fun to eat sweet like we like it, because it's so hot that it helps us add energy. And for example, fear, seeing a tiger turn around and running to avoid danger, so complex in the primitive jungle that we have to produce many brain “quick ways” to help us react quickly。
Example: invisible knowledge
Theoretically, laypersons do not see that they can't write, that they can learn in their minds and in practice。
Examples: the touch of the tweeds, the chef's touch on the fire, the delicate grasp of the food, teamwork among the teams, the brain pattern of the master, the inner layout of the chess player. Much needs to be learned from the world itself, which often takes long periods of experience。
Internalized knowledge + memory know-how + easy to connect
Internalization of knowledge: an overview of the theory: a concise presentation of the theory in the way it is understood and understood in its own habits
Accessibility: classification/labelling: classification of knowledge by discipline or subject in mind。
The brain likes to classify: your brain doesn't know how to connect knowledge when it's more and more enlightening。
2. Deep building knowledge structures
Having a knowledge point and a framework and a good knowledge structure is an excellent map. So when building a knowledge structure, your goal is to build as many links as possible between knowledge, which smart people will naturally do, and each learning a new concept will automatically link to other knowledge。
The creation of a knowledge framework needs to be built on a large stock of knowledge and understanding. The core principle of this step is the continuous clustering and fragmentation of a large number of knowledge points。
Example: cognitive psychology
Generating meaning: the classification of nature sex in the brain, further integrating and categorizing knowledge as it becomes more and more instructive
The law of the golden circle: encountering a new concept, over and over again. The golden circle code (2w1h) is the trick to build solid knowledge structures。
3. Building knowledge systems
The purpose of learning is to build knowledge systems, known as “knowledge systems”, which combine a large but diverse body of knowledge points into a certain type of knowledge architecture in a systematic, structured and targeted way. Through this knowledge architecture, we can better understand things and solve problems。
Like cooks who see the food on the table, they know naturally what kind of coolness they can offer because, in their brains, they form a whole system of knowledge through the years and years of cooking, such as the mix of materials, the weight of the load, the taste of the food。
The link between deep-seated and re-engineered knowledge: extensive learning to understand the knowledge structure of detaching wells with precision + continuous output and practice
Fundamental principle: the context in which knowledge should be applied should be structured. In their own knowledge systems, exporting knowledge is a process of restructuring, that is, of connecting knowledge。
The knowledge framework is built on the basis of structures and knowledge points, which are constantly clustered and divided, restructured, integrated with their work and lives, creating a link between output, deep exploration and re-engineering of knowledge。
Interdisciplinary knowledge framework
The essence of interdisciplinary learning is to activate the cybereffects of large breasts, to network knowledge from multiple angles, to network in the brain, to have a single node of thinking in every discipline, to have a cross-section of books in the network, to have a free flow of information, to have multidisciplinary ways of thinking and a rich level of understanding, to be able to think from multiple angles about complex issues, to quickly understand what is behind things, and to propose creative solutions。
A balance between breadth and depth of thinking
Extensive learning in many different disciplines
Understanding deep principles and thinking models linking these areas
Apply these thinking models to their core areas of expertise
Finally, you hang all your knowledge and experience in the cognitive network
One of the most efficient methods of learning to date is the thinking approach based on a plurality of ideas in terms of increasing cognitive capacity。
Reconstruct the knowledge classification management system
Over the years, i have recognized a more in-depth classification of knowledge. This approach applies to learning the rationales of all areas and benefits for life in solving practical problems. It is the management of knowledge systems based on thinking models
Create new cognitive networks
Accumulation of specialized knowledge: learning based on a disciplined knowledge system to facilitate rapid accumulation of knowledge
Knowledge system conversion, upgrading
Problem-oriented solutions: knowledge management based on thinking based on thinking models。
Increased knowledge systems
The process of building a knowledge system to bring knowledge back into-internalized-out requires that learners take the initiative to think. It is a process that is strong, arduous and joyful, and that, while building knowledge systems, learners ' intellectual understanding and cognitive abilities can be rapidly enhanced and, finally, learning is the real purpose of learning by using the knowledge systems they have learned to solve complex problems of life。
Building dynamically growing knowledge systems
I don't know. Build frameworks, refine models and form knowledge crystals
I don't know. Access to information, extensive search and enrichment of information dimensions
I don't know. Collapse, line up, strengthen narrative knowledge
I don't know. Practice testing, application output, internalization of procedural knowledge
As to what subjects you study, the most wonderful thing is that you don't need to know all the points of knowledge, just some core principles of enrichment. And once the framework of core principles is in place, learning is easy even to expand
Outreach system -- timely documentation, regular compilation, reflection on upgrading
On the basis of an initial knowledge system, we can record, distribute, fill and improve the knowledge system in all subsequent learning, whenever we encounter elements related to this knowledge system. As you accumulate more and more, knowledge systems become more sophisticated。
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