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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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?

Ценообразование в российских вузах: как влияют на стоимость обучения вузы-конкуренты?

Университетское управление: практика и анализ. 2023. Т. 27. № 2. С. 75–88.
Dmitrienko A., Myachin A. L.

The paper analyzes the pricing strategies of Russian public universities in the context of the influence of competitors on the market for tuition-paying education. The aim of the study is to determine how competition in local higher education markets affects the pricing strategies of Russian public universities. The empirical basis of the study is formed by the data of the Monitoring of Enrollment Quality at Russian Universities implemented by the National Research University Higher School of Economics. Using pattern analysis methods (order-fixed and order-invariant pattern clustering), homogeneous groups of universities were identified taking into account indicators characterizing the scale and quality of admission to bachelor's and specialist programs. Using the example of technical programs, the regression model for predicting the prices of education in universities of corresponding homogeneous groups for the period 2011-2019 is demonstrated. The results show that each homogeneous group of universities has one or several market leaders who serve as benchmarks for other universities in that group when setting tuition fees. At the same time, university pricing strategies involve orienting towards market leaders in their demand segments and specialty groups. The identified features confirm that competition among universities for students and funding leads to the emergence of market leaders in certain market niches. In some groups of universities, there are clear market leaders at the local and regional levels who have a significant lead over competitors due to the peculiarities of state policy and the high heterogeneity of the Russian educational landscape.

Language: Russian
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Keywords: образовательная политикаpattern analysisанализ паттерновpatternпаттернeducational policyhigher education marketрынок высшего образованияэкономика высшего образованияeconomics of higher educationpricing in universitiespricing strategiesценообразование в вузахстратегии ценообразования
Publication based on the results of:
The Dynamics of Human Capital in Academic Sector (2023)
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