Transformation of the methodology of teaching artificial intelligence technologies in the context of digitalization of Russian society
K. V. Rozov1, M. A. Abramova2
1Novosibirsk State Pedagogical University, Russia, Novosibirsk
2Institute of Philosophy and Law, Siberian Branch of the Russian Academy of Sciences, Russia, Novosibirsk
Keywords: artificial intelligence technologies, methods of teacher training, conditions of digitalization of Russian society, digitalization of education
Abstract
Introduction. The task is set to identify the possibilities of transformation and prospects for the development of methods for teaching artificial intelligence technologies in the context of digitalization of Russian society. This task is updated by the growing importance of artificial intelligence in all spheres of society. The rapid development of AI has led to the need to train a new generation of personnel with skills in the field of information technology. But the task of updating the content and methods of training future artificial intelligence technologies teachers has acquired the greatest importance. Methodology. Analysis of changes in methodology as a component of personnel training that fulfills one of the tasks of an educational institution, solved within the framework of an even larger task - the formation of conditions for the sustainable development of the country as a whole, involves the use of structural-functional and systemic approaches in the research process. Discussion. The work also presents an analysis of regulatory documents and training programs. A retrospective analysis of the content of the traditional training of future computer science teachers in the basics of artificial intelligence revealed a fairly strong lag behind what is in demand by society and the level of technology that is being implemented everywhere today, which makes it urgent to set the task of reforming both the content and methodological support. The analysis performed demonstrates the possibilities of modernizing the methodology for training future computer science teachers in the use of artificial intelligence technologies, which are embodied in the model developed by the authors for preparing future computer science teachers for teaching artificial intelligence. Conclusion. Testing of the model showed effectiveness in developing students’ skills in mastering technical information technology, as well as the ability to transfer their knowledge to students. The results of the study demonstrated the success of the attempt made in the study to solve the existing problem of updating the content and methodology of training future teachers.
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