First, convey mathematical ideas.
Symbolization enables mathematicians to express their mathematical ideas in a standardized form under the agreement of * * * *, thus promoting academic exchanges and cooperation.
Second, conciseness and reasoning
Symbolic language is usually more concise and easier to reason than written expression. It is simpler and clearer to express complex formulas with digital symbols than to describe them with words.
Three. Education and training
In primary school mathematics education, symbolic thinking also has important value. The new curriculum standard emphasizes the cultivation of symbolic sense, including abstracting quantitative relations and changing rules from specific situations and expressing them with symbols, as well as the transformation between symbols.
Fourth, universality.
Besides mathematics and science, symbolism is also widely used in other fields, such as logic, linguistics and computer science.
Application field of symbolic thinking
First, the symbolic thought in mathematics
In mathematics, symbolic thinking is the foundation and core. Mathematicians use various symbols (such as letters, numbers, operators, etc.). ) to represent mathematical objects, relationships and operations, thus establishing mathematical models and deducing mathematical theorems. This symbolic expression makes mathematics more concise, accurate and easy to reason.
Second, the symbolic thought in science
Symbolization also plays an important role in scientific research. Scientists use symbols to represent experimental results, observation data and theoretical models in order to better understand and explain natural phenomena. Through symbolization, scientists can transform complex practical problems into abstract mathematical models for quantitative analysis and prediction.
Third, symbolic thinking in logic.
Logic is a subject that studies reasoning and argumentation, and symbolic thinking plays an important role in it. Logicians use symbols (such as propositional variables, logical operators, etc. ) to express the relationship between proposition and reasoning, so as to construct a logical system and conduct formal reasoning. Symbolization makes the process of logical reasoning more clear, standardized and computable.
Fourthly, symbolic thinking in computer science.
In computer science, symbolization is widely used in programming languages, algorithm design and data structures. Programmers use symbols to represent variables, functions and program structures in order to write and understand computer programs. At the same time, the design of algorithm and data structure also depends on symbolic abstract thinking, so that the problem can be effectively decomposed and solved.