Keyword: «individual educational trajectories»

the article substantiates the necessity of scientific understanding and practical solution of the problem of personal self-determination of the future teacher in the context of individualization of pedagogical education.

The paper presents the features of the professional training of a future computer science teacher for the use of artificial intelligence technologies to form a roadmap for an modular academic discipline based on cluster data analysis. Learning dataset include information about the choice of specific learning tasks by abstract students, about assessments of the formation of their profile skills and interest in studying the discipline. Data clustering is performed using the k-means method. The software implementation is based on the use of the machine learning and data analysis Python libraries: Scikit-learn and Pandas. The result of the training is the readiness of future teachers to use cluster analysis of data in their future professional activities to develop pedagogical recommendations for students on the choice of an individual educational route.

The relevance of the study of the issues of training specialists in economics for industrial enterprises of the Russian Federation is due to the need for these enterprises to solve tasks set by the country's leadership: computerization, sustainable development, import substitution, technological independence of Russia, and V. V. Putin's proposal to "return to the traditional basic training of specialists with higher education", combining the best of the Soviet system and experience the last decades. The purpose of this article is to study the peculiarities of the training of specialists in economics with higher education for domestic industrial enterprises in the Soviet and post-Soviet periods, to identify existing problems and identify opportunities for their solution in the conditions of the course of changes in higher education set by the President of the Russian Federation and guidelines for the development of Russian industry. In the course of the research, the following methods were used: analysis, synthesis, generalization, systematization, comparison. The results of studying the problems of training specialists in economics for industrial enterprises of the Russian Federation at the present stage of the country's development demonstrated the washing out of the curricula of technical and technological disciplines, which were mandatory in the Soviet period, and industry specifics was practically eliminated. The solution to this problem is possible both through the introduction of a specialty with the assignment of the qualification "engineer-economist", and the development of specialized, tailored to the needs of specific enterprises and/or industries, the main educational master's degree programs for graduates of engineering specialties with focus on economic disciplines. Following the traditional model of economist training, when a student studies a sequence of courses predetermined by the university, or providing the student with a choice of the disciplines studied should depend on its infrastructural, material, financial status, and the level of academic staff qualification. Universities with limited resources have two ways – refusal of training in interdisciplinary specialties, which include "engineer-economist", or networking with other universities in the training of future economists for industrial enterprises. The theoretical significance of the article consists in the systematization of existing research works on the training of specialists in economics with higher education for industrial enterprises of the Russian Federation; its practical significance lies in the applicability of the conclusions formulated in the development of educational standards for economists, including engineers, economists, managers, and in the justification of the content of the main educational programs and the choice of educational models training by universities.

The article discusses the reflection of current trends in the development of educational systems in scientific research. There are six main areas of scientific research: the formation of digital literacy; development of the «data-driven learning» model; designing digital distance learning tools, including for group learning; development of educational robotics; usingф big data analytics to implement individual learning paths; development of «hybrid learning» technologies. The main features of each of the directions are analyzed, the positive pedagogical effect from the practical application of relevant developments is revealed. The article also reveals the main elements of the «hybrid learning» technology.