Analytical review of the training system for mining engineers in Russia
Автор: Petrov V.L.
Журнал: Горные науки и технологии @gornye-nauki-tekhnologii
Рубрика: Подготовка профессиональных кадров. Организация исследований
Статья в выпуске: 3 т.7, 2022 года.
Бесплатный доступ
Personnel training for the mineral resources sector in Russia has always been one of the most relevant topics for discussion in academic and professional mining community, including the international context. Experts from many countries regularly present their research on the state and achievements of higher education in mining in the national training systems for mining engineers. The purpose of this paper is to analyze and quantify the system of training for mining engineers in Russia. To assess the quantitative characteristics of the training of mining engineers in Russia, the research used methods of analysis based on the objective data of state statistics on the graduation of mining engineers in all universities, as well as admission to the corresponding professions and training programs. Thus, 5,031 mining engineers were trained in Russia in the specialties “Applied Geology”; “Geological Exploration”; “Mining”; “Physical Processes of Mining and Oil and Gas Production” in 2021. 10,789 bachelors and masters were trained under oil and gas directions of training. The results of the analysis are presented in the paper in the context of particular universities, specializations and directions of training of Federal Districts and the country as a whole. The quantitative parameters of personnel training for the mineral resource sector at Russian universities indicate the opportunity for the formation of human resources potential within the higher education system of the industry exclusively at the expense of their own academic schools.
Mining engineer, mineral resource sector, oil and gas, mining, applied geology, higher education in mining, mining universities, regions of Russia, training, mining professions, prestige, university admission, admission statistics, quality, analysis
Короткий адрес: https://sciup.org/140296152
IDR: 140296152 | DOI: 10.17073/2500-0632-2022-3-240-259