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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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Самостоятельность и агентность школьников: различение понятий

Социологические исследования. 2023. № 11. С. 80–92.
Добрякова М. С., Yurchenko O.

The article explores the conceptual difference between the notions of "autonomy" and "agency" in relation to students' learning outcomes. These concepts are often used as synonyms. We argue that distinguishing between them is more productive for practical pedagogy. Unfolding the essence of agentive action in 9 theoretical theses based on sociological and psychological approaches, we trace its prerequisites and outline the forks where agency and autonomy diverge. Agency implies a desire for change based on a consciously constructed identity and values. Independence focuses on achieving mastery within existing roles and social norms. In a social sense, in the continuity/change pair, independence aims at continuity, while agency aims at change. Distinguishing these concepts will help consciously design learning situations and set realistic learning outcomes. However, can agency be a realistic measurable learning outcome in the conventional sense? Probably not, since it is tied to identity and personal attitudes towards social situations, and will therefore be very individual. Autonomy as an learning outcome is simpler, because ultimately it requires comparing the student's skills to those of an adult. The key factor differentiating autonomy and agency is the nature of the individual's identity - its orientation towards reproducing the existing or towards individual search and change. Overall, the paper makes a conceptual contribution by differentiating the terms agency and autonomy in education.

Research target: Sociology (including Demography and Anthropology Education
Language: Russian
DOI
Text on another site
Keywords: образовательные результатыautonomyавтономиясамостоятельностьlearning outcomeseducational outcomesagencyагентностьагентность ученика
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