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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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Цифровое тестирование смыслового чтения обучающихся начальной школы: анализ индикаторов поведения

Психологическая наука и образование. 2024. Т. 29. № 2. С. 32–49.
Bakay E., Yusupova E., Antipkina I.

Test-taking behavior in reading comprehension tests is explained, among other things, by meta-cognitive skills, which can be described by indicators of test behavior. These indicators include reading time, respondent-item interaction time, returning to the text, etc. This study is based on the analysis of the test-taking behavior of fourth graders (N=2168) during a reading comprehension test. Two types of indicators of test behavior were described: 1) timing and action speed control; and 2) nonlinear test navigation from item to item and returns to the text. Based on these indicators and using cluster analysis, we identified groups of students with typical patterns of behavior. These groups were described in the context of student gender and test score in the test. The results showed that the data about nonlinear transitions helps to find out the groups of students with regulatory difficulties, however the presence or absence of nonlinear transitions is not associated with test results. Higher results of students are associated with taking test in a linear pattern and a moderately long time.

Research target: Education
Language: Russian
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Keywords: чтениеповедениеreadingbehaviormetacognitive skillsметакогнитивные уменияcognitive strategyкогнитивные стратегии
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