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News
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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Совершенствование содержания программ математического цикла для экономистов-бакалавров на примере дисциплины «Линейная алгебра»

Вестник Нижегородского университета им. Н.И. Лобачевского. Серия: Социальные науки. 2022. № 1(65). С. 157–165.
М.В. Котельникова, А.В. Аистов

The article presents a method for improving the content of the disciplines of the mathematical cycle ("Linear algebra", "Mathematical analysis", "Probability theory and mathematical statistics") based on the content of the program "Econometrics" for the direction of training 38.03.01 Economics of N.I. Lobachevsky National Research University. The described methodology can be applied to any discipline and includes seven main points. The article presents the following results of the methodology use for "Linear algebra": matrices of logical connections (MLS) within the discipline and the interdisciplinary "Linear algebra"–"Econometrics"; chains of significance of content elements (a fragment of a table); the result of allocating a common (invariant) part of the programs of several selected universities; a hierarchy of topics within the discipline and their rating built on the basis of the analysis; a variant of redistribution of time allocation for seminars and independent work; examples of possible topics for research and project work. It is proposed to redistribute the hours of training sessions depending on the rating of each topic obtained as a result of the conducted research. For those with a high rating, it is necessary to allocate more time for seminar classes, for those with a low rating-for independent work. According to the results of the application of the methodology, there was an improvement in the quality of students 'mastering the material of mathematical disciplines necessary for a more complete study of "Econometrics", and, as a result, to increase the level of formation of "Professional mathematical competence of an economist" (PMCE), which positively affects their further successful professional activity.

Research target: Education
Language: Russian
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DOI
Text on another site
Keywords: рейтингэконометрикаиерархияratingeconometricsинвариантhierarchyinvariantПрофессиональная математическая компетенция экономиста (ПМКЭ)цепочки значимости элементов содержания дисциплинprofessional mathematical competence of an economist (PMCE)matrix of logical connections (MLS)chains of significance of content elementsматрица логических связей
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