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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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The Fear of COVID-19 Scale: Its Structure and Measurement Invariance Across 48 Countries

Psychological Assessment. 2022. Vol. 34. No. 3. P. 294–310.
Sawicki A., Żemojtel-Piotrowska M., Balcerowska J., Sawicka M., Piotrowski J., Sedikides C., Jonason P., Maltby J., Adamovic M., Agada A. G., Ahmed O., Al-Shawaf L., Appiah S. C., Ardi R., Babakr Z. H., Bălțătescu S., Bonato M., Cowden R., Chobthamkit P., De Pretto L., Gouveia V., Haretche C., Iliško D., Aruta J. J., Jia F., Jovanović V., Jukić T., Kamble S., Khachatryan N., Klicperova-Baker M., Koralov M., Kovacs M., Kretchner M., Fernandez A. L., Liik K., Malik N. I., Malysheva K., Moon C., Muehlbacher S., Nartova-Bochaver S. K., Torres-Marín J., Özsoy E., Park J., Piccinelli E., Ramos-Diaz J., Riđić O., Samekin A., Starc A., Trà K. T., Tomsik R., Umeh C., Wills-Herrera E., Wlodarczyk A., Vally Z., Zand S.

COVID-19 has been a source of fear around the world. We asked whether the measurement of this fear is trustworthy and comparable across countries. In particular, we explored the measurement invariance and cross-cultural replicability of the widely-used Fear of COVID-19 scale (FCV-19S), testing community samples from 48 countries (N = 14,558). The findings indicate that the FCV-19S has a somewhat problematic structure, yet the one-factor solution is replicable across cultural contexts and could be used in studies that compare people who vary on gender and educational level. The validity of the scale is supported by a consistent pattern of positive correlations with perceived stress and general anxiety. However, given the unclear structure of the FCV-19S, we recommend using latent factor scores, instead of raw scores, especially in cross-cultural comparisons. 

Research target: Psychology
Language: English
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Keywords: measurement invariancecross-cultural studiescoronavirusfear of COVID
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