Numerical dyslexia

Numerical dyslexia

Algorithmic thinking can be understood as a system of thinking methods aimed at solving problems. Here, two sides of understanding are hidden. The first is to define someone else’s algorithm. The second, to build one’s own. If it is necessary to interact with something when solving a problem, you will have to understand how it is arranged. Only Numerical dyslexia then, you can build your own algorithm. It is difficult to imagine a task that does not require interaction with anything.

Even if you are just trying to get through the door, you need to know the “door algorithm”. How many people would break into an open door and it would open the other way. They just didn’t ask the question: “Why does it not open?

Numerical dyslexia

Why should it develop algorithmic thinking?
After it became clear what is algorithmic thinking, it is easy to answer this question. The easier we can understand other people’s algorithms and build our own, the better. In other words, it is useful to know and understand how and what works.

This type of thinking very much helps us to master many knowledge and skills, including school subjects. The ability to think accurately, formally, if necessary, becomes one of the important signs of a person’s general culture in today’s high-tech world.

Here are some of the skills that are required in many areas:

Division of a common task into subtasks.
The ability to plan stages and time of the activity.
Evaluation of activity efficiency.
Search for information.
Processing and assimilating information.
Understanding sequential, parallel, non-deterministic actions.
Of course, Goethe also noticed that things are not divided into reason without a trace. But reason is very useful in life. When people say that they can think, they usually mean developed algorithmic thinking.

How to develop algorithmic thinking?
Like everything that requires development, algorithmic thinking should be trained. It is possible to train haphazardly, for example, playing strategic games. But so the development turns out to be one-sided. The understanding of properties and limitations will be the worst developed.

Understanding and construction of algorithms is engaged in computer science. Computer science also studies their properties. It is logical to assume that studying the disciplines related to computer science and programming will develop algorithmic thinking in the best way.

From such a wide field as informatics, programming should be distinguished. Studying the properties of algorithms and learning to work with them is best done using programming as an example. The computer itself is also an interesting and useful thing, which also adds motivation for learning how to program. Academician A.P. Ershov said back in 1986 that computer literacy was the second literacy.