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  • Как измерить состояние потока в учебе? Апробация Шкалы потока в учебе на выборке российских студентов
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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Как измерить состояние потока в учебе? Апробация Шкалы потока в учебе на выборке российских студентов

Вопросы образования. 2024. № 4. С. 95–125.
Ivanova A., Denisov I.

The state of "flow" is experienced by a person who is so immersed in an activity that he or she is not paying attention to anything around them.  Flow state can play an important role in educational achievement. Researchers around the world have shown that a flow state is positively related to self-esteem, life satisfaction, psychological well-being, and, to some extent, educational achievement in students. There are currently no questionnaires in Russian that can measure the flow state in learning quickly and reliably enough. This paper will describe the process of localizing the study-related flow inventory in Russian and present the initial results of its validation. Validation was conducted on a sample of about 600 individuals who, at the time of the survey, were in the process of learning. Confirmatory factor analysis was used to gather evidence of construct validity; the functioning of the scale for different groups of survey participants was also investigated; in addition, the item response theory was applied to assess the reliability of the scale, to assess the quality of individual scale items, and to investigate the functioning of individual categories. Like the original version, the Russian-language scale is quite reliable and also demonstrates invariance to the conditions of heterogeneous samples of subjects: by gender, by work/study status, and by the way the sample was obtained. The application of the scale in the Russian context highlighted the problem with the scale structure, which was previously shown by researchers from some countries when trying to adapt the scale into the languages of their countries. Overall, the Russian-language version of the study-related flow inventory can be successfully applied in Russian research practice.

Research target: Psychology Education
Language: Russian
Full text
DOI
Keywords: состояние потокаапробация методикиconstruct validityflowконструктная валидностьscale development and adaptationstudy-related flow scaleшкала потока в учебе
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