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News
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.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Методика оценки цифровой грамотности студентов

Психологический журнал. 2025. Т. 46. № 1. С. 84–94.
Maklasova E., Жаркова А. П., Rodionov G.

The evolution and widespread use of digital technologies in our lives led to the usual social practice transformation and creation of their digital equivalents across the world. This was followed by the digital transformation of education. One way to assess the effectiveness of these changes is to assess the digital literacy of the subjects in the educational process. Digital literacy is one of the main factors in successful involvement in online learning. Different studies are focusing on different aspects of digital literacy, so there are a lot of different definitions and ways to figure out its structure. The purpose of the article is to combine existing ideas about students’ digital literacy and to test a psychological methodology for its assessment. The methodology included 19 items to evaluate four groups of digital literacy skills - data analysis skills, information management skills, digital equipment setup skills, and software skills. At the time of the socio-psychological survey, 100% of respondents were studying remotely using digital technologies. The exploratory and confirmatory factor analysis (n = 500; 69% women; M = 28 yrs., SD = 10 yrs.) results showed that the four-factor structure explains more (53%) than the two- (43%) and one- factor (34%) structures. This is in line with the theoretical model that the methodology is based on, and there are high signs of internal consistency (above 0.7). The correlation analysis (n = 103; 64% women; M = 21 yrs., SD = 4 yrs.) revealed that all components of digital literacy are positively related to a person’s social capital. This is in line with what other studies have found. Therefore, it is recommended to use a four-factor framework for assessing the student’s digital literacy.

Research target: Psychology
Language: Russian
Keywords: социальный капиталинформационно-коммуникационные технологииsocial capital information and communication technologiesцифровизацияцифровая грамотностьdigital literacy digitalization
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