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  • ОБРАБОТКА И АНАЛИЗ РЕЗУЛЬТАТОВ МОНИТОРИНГОВ ДЛЯ УПРАВЛЕНИЯ ФОРМИРОВАНИЕМ УСЛОВИЙ КАЧЕСТВЕННОГО ОБРАЗОВАНИЯ
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News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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ОБРАБОТКА И АНАЛИЗ РЕЗУЛЬТАТОВ МОНИТОРИНГОВ ДЛЯ УПРАВЛЕНИЯ ФОРМИРОВАНИЕМ УСЛОВИЙ КАЧЕСТВЕННОГО ОБРАЗОВАНИЯ

Моделирование, оптимизация и информационные технологии. 2017. Т. 5. № 4. С. 1–18.
Shvindt A.

The article reviews models and procedures for processing and evaluation of monitoring results, including student participation, focused on intellectual support of administrative managerial decisions when developing of conditions and corresponding resources for the achievement of applicable regulatory requirements for the quality of university education. The first stage of processing is normalization of factors which characterize the conditions for quality education, indicators of graduate employability and student-oriented monitoring. The next stage is aimed at building the models of integral evaluation of factors and indicators. With the chosen structure of a model in the form of additive convolution, a parametric identification procedure based on the comparison of results of neural network modeling, visual information and subsequent expert evaluation is proposed. Evaluation of monitoring results consists of ranking and clustering of higher education institutions on the basis of integral assessments of education quality. The sequence of steps in the clustering procedure, which determines probabilistic estimates with the use of expert's views, according to which a great number of higher education institutions are divided into a given number of clusters, is described.

Research target: Education
Priority areas: state and public administration
Language: Russian
Text on another site
Keywords: кластеризацияранжированиеclusteringrankingнормированиеrationingintegral evaluationadditive convolutionинтегральное оцениваниеаддитивная свертка
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