The purpose of the lessons is to introduce students to artificial intelligence technologies and their use in the modern world. The series consists of 7 lessons that can be taught by both computer science teachers and teachers of other disciplines. For example, the lesson “Machine Learning in Art” can be taught as part of the Fine Arts or Music, and “Machine Learning in Sports” can be taught as an alternative lesson in physical education.
During the lesson, students will become familiar with various aspects of using machine learning technologies in different areas of human activity. Active immersion to the world of new technological solutions related to robotics, driverless cars and trains, intellectual games, voice assistants and, finally, works of art should help create an atmosphere of student involvement in the amazing era, in which we live, the discoveries that are being made by our contemporaries. But, more importantly, the entire “kaleidoscope” of discoveries that schoolchildren are introduced to and discuss should help them understand the level of requirements for future specialists in various professional fields. This is a serious career guidance idea for the lesson, a task for the future.
The lesson will introduce students to one of the most promising and dynamically developing areas in the modern IT industry related to the development of artificial intelligence technologies.
The lesson scenario is structured according to a didactic spiral: at the first turn, the concepts and technologies of computer vision are considered through the prism of the personal experience of schoolchildren, analyzing which students are immersed in the subject field related to the development of technologies in this area. Analysis of practical examples and active involvement of children in activities will help not only to initiate the desire of schoolchildren to “immerse” in this area of knowledge, but will also contribute to the formation of meta-subject and personal results.
The lesson is built on a block-modular principle. The structure of the lesson involves various options for its layout from content blocks, depending on the technical equipment of the class and the availability of access to the Internet.
In the first (invariant) part of the lesson, schoolchildren will become familiar with the main aspects of the use of machine learning in art, and in the second, they will independently complete practical tasks directly related to the topic of the lesson.
The lesson includes an interactive conversation, practical work and predictive reflection.
During the lesson, schoolchildren are introduced to the main achievements in the gaming industry, taking into account their chronology. It is important to show that humanity has been trying to recreate human intelligence and teach machines to play for several hundred years, but outstanding achievements have been achieved only in the last 20–25 years.
As a result, this should spark discussion about the ethical and emotional implications of using machine learning technologies in games.
Students will have an interactive lesson where they will become familiar with the capabilities of various intelligent systems, which will help increase their motivation for design and research activities, provide the opportunity to independently train a neural network, and even contribute to the formation of an ecological culture that corresponds to the modern level of thinking.
The lesson is focused primarily on an overview of existing intelligent dialogue systems with a demonstration by the teacher of their capabilities.
During the lesson, students can learn how the problem of creating intelligent dialogue systems has been solved by the engineering and scientific community for 80 years, and independently draw conclusions about the growing dynamics of development of this branch of the IT industry, as well as get acquainted with the practical aspects of its application, primarily in our daily life.
Against the backdrop of a very diverse conversation about sports (from training athletes, diagnosing their physical condition, organizing team interaction, commercialization of sports to mind games and e-sports), students will become familiar with the capabilities of artificial intelligence and, in particular, machine learning systems. All this should provoke students’ interest in various aspects of the use of machine learning technologies aimed at solving problems of prediction, classification, adaptation, etc.