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News
July 24, 2026
‘I Like Self-Fulfilling Prophecies
Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.
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.

 

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Метрики центральности сетевого анализа как инструмент определения уровня абстракции понятий внутри понятийной структуры обучающихся

Психологические исследования: электронный научный журнал. 2025. Т. 18. № 102. Статья 3.
Andronova E., Kapuza A.

This study examines concepts as systemic elements within a conceptual structure, drawing on the theoretical framework of L.S. Vygotsky’s cultural-historical psychology. A key characteristic of concepts is their level of abstraction, which reflects their degree of generalization within a system. However, existing classification methods lack a unified approach, complicating empirical research. The current study aimed to explore network analysis metrics as a tool for distinguishing concepts of different levels within a concept structure. We analysed 242 concepts from conceptual maps created by experts and students in data analysis. First, a qualitative analysis was conducted using formal definitions and expert evaluations. Then, betweenness centrality and degree centrality metrics were applied to assess their effectiveness in distinguishing conceptual levels. The findings showed that betweenness centrality and normalized betweenness centrality significantly differed across levels: higher-level concepts had higher values compared to the basic and subordinate ones. Degree centrality varied depending on the classification method. When classified by definition, all group differences were shown to be significant. When classified by maps, differences were found only for the subordinate level. However, the number of incoming connections did not show distinguishing capability. Based on the results, it can be assumed that network analysis demonstrates potential not only in assessing the systemic characteristics of a conceptual structure but also in evaluating the role of individual concepts within it.

Research target: Psychology Education
Language: Russian
DOI
Keywords: сетевой анализnetwork analysisconcept structureкультурно-историческая теорияконцептуальные картыconcept mapsL. Vygotsky’s cultural-historical theory levels of abstractionпонятийная структурауровни абстракции понятий
Publication based on the results of:
Using digital traces to study learners' behavioral strategies (2025)
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