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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Оценка эффективности образования по инженерно-техническим специальностям: коэффициент доучиваемости

Университетское управление: практика и анализ. 2025. Т. 29. № 4. С. 112–128.
Лопухин А. М., Barabashev A. G.

The article analyzes the effectiveness of education based on the results of admission to state-funded places in engineering and technical specialties at Russian universities. The retention rate is considered as an indicator that complements the universal indicators of the Russian Ministry of Higher Education and Science’s Monitoring, and characterizes the quality of admission, the educational process, and educational outcomes. The aim of the study is to
DOI 10.15826/umpa.2025.04.034
develop a typology of training programs based on admission and completion indicators, taking into account the significance of the retention rate indicators. Based on data from the VPO-1 form of the Ministry for the period from 2014 to 2024, the influence of the dynamics of budget place redistribution in favor of engineering and technical specialties on changes in the retention rate is analyzed. It is concluded that an increase in the number of state-funded places in engineering and technical fields generally does not lead to a corresponding increase in the number of graduates. It is revealed that the gap between admission and graduation is particularly pronounced in regional universities, where the retention rate is significantly lower than in metropolitan universities. The analysis was conducted both for the Russian Federation as a whole and for individual subjects of the Russian Federation, including the Krasnoyarsk Region and the city of Moscow. It is shown that engineering and technical fields form a separate type of training, characterized by a decrease in the retention rate when budget places are redistributed in their favor.
Based on the conducted research, recommendations are formulated on improving the management of budget place allocation for engineering and technical specialties for executive authorities and founders of higher education institutions in the Russian Federation.

Research target: Political Science, International Relations, and Public Administration Education Economics and Management
Language: Russian
Full text
DOI
Keywords: инженерные специальностиindicative governanceengeneering specialitiesretention rateиндикативное управлениекоэффициент доучиваемости
Publication based on the results of:
Self-organization of citizens and the public administration system: a theory of mutual influence, the experience of Russia and other non-western countries and ways of improving the effectiveness of productive interaction (2025)
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