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September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Обновление аффективно окрашенной информации в рабочей памяти: роль эмоционального состояния

Российский журнал когнитивной науки. 2018. Т. 5. № 2. С. 45–56.
Suchkova E.

The aim of the current study was to provide an empirical evidence of an emotional state’s influence on the updating of affective information in working memory. The emotional congruence effect was expected: participants in a happy emotional state would be more successful in updating positive information compared to negative and neutral information. It was also expected that participants in a negative emotional state would show the opposite pattern of results. The sample included 66 subjects (age: M = 18.56; SD = 1.02). To measure updating, an affective n-back task was applied with positive, negative and neutral words as stimuli. To induce an emotional state, a combination of autobiographical memories and music listening was used. No emotional congruence effect has been obtained. The pattern of results for reaction times and accuracy was similar in both groups; most likely, it was partially caused by the sequence effect. In all types of trials, participants responded faster after emotion induction. The accuracy of responses to negative (M = 0.83; SD = 0.12) was significantly different compared to positive (M = 0.78; SD = 0.16) and neutral trials (M = 0.73; SD = 0.21). The results show that the updating of emotional stimuli is more effective compared to neutral stimuli; among emotional stimuli, updating negative stimuli is more effective compared to positive stimuli. 

Language: Russian
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Keywords: обновлениеworking memoryрабочая памятьуправляющие функцииemotional stateэмоциональное состояниеexecutive functionsN-back tasksэмоциональная конгруэнтностьemotional congruenceupdatingemotional induction"n шагов назад"индукция эмоциональных состояний
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