Abstract
Today, artificial intelligence (AI) has significantly transformed all spheres of society. One of the tasks of the education system is to prepare children for successful lives in a modern technological world, ensuring their professional realization and demand in the labor market. In this study, we describe the conduct of a class with students within the framework of extracurricular activities focused on artificial intelligence: terminology is introduced, an approximate lesson plan is provided, and methodological recommendations are given. During the class, children become familiar with the concepts of artificial intelligence and machine learning, the differences between them, the concept of computer vision, the stages of machine learning, the steps of object identification, data acquisition and classification, examples of image recognition projects, decision trees, the concept of neural networks and their training, and they also teach a machine with built-in artificial intelligence to "see" objects. Throughout the lesson, various games were proposed to help understand and assimilate complex concepts. The uniqueness of these classes lies in their duration and the variety of activities. They can be conducted in summer camps, during scientific studies/research during holidays. Work on project implementation takes place in small groups, which directly contributes to the development of soft skills. It also provides an opportunity to organize competitions between groups, present one’s project to other groups, compare different solutions to a particular problem, and accordingly improve one’s own project. Special attention should be paid to the use of artificial intelligence in robotic systems. This combination allows for the expansion of the study of traditional STEM subjects. The article presents the experience of conducting classes within the volunteer project "Ukrainian Hacker School" for children. Using the example of a class involving Zumi, the main approaches and features of AI learning for children aged 10-16 are revealed.
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