Вестник Северо-Кавказского федерального университета (Jul 2024)
Cross-cutting technologies in training physical culture and sports for students
Abstract
Introduction. The introduction of digitalization into the life of all humanity opens up enormous opportunities for the use of digital technologies in the education of university students. The use of these technologies is not limited to a specific field of activity, therefore they are widely used in various academic courses. The use of end-to-end technologies in the field of physical education is gaining popularity. Goal. To study and analyze the possibilities of end-to-end technologies in the field of physical culture and sports in training university students as a means of organizing and control-ling sports activities. Materials and methods. Insufficient representation of the research topic in the scientific community required an analysis of literary sources, systematization of end-to-end technologies and generalization of the results. Results and discussion. The study of scientific works of modern practitioners has shown the main focus in supporting the training process, in particular: the use of active teaching methods, the use of digital technologies in the independent work of students and end-to-end technologies in the field of physical education, which made it possible to classify end-to-end technoloies and highlight those predominantly used in physical culture and sports. Conclusion. The significance of the introduction and use of digitalization in Russian education is analyzed. It was revealed that end-to-end technologies: cloud technologies (Cloud Technologies); blockchain (Blockchain); Big Data (BigData); artificial intelligence (AI) – allow the use of a variety of forms and methods of their manifestation in the educational process of university students, and are one of the modern ways of intensifying and optimization of all education. The potential of using end-to-end technologies in the educational process of students in physical education and sports is considered. Research data is classified in a table.
Keywords