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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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Современный мировой ландшафт онлайн-обучения наукам о данных

Высшее образование в России. 2022. Т. 31. № 4. С. 129–147.
Никольский В. С., Лукашенко М. А., Шарова Е. А.

 

Data science as an emerging branch of applied knowledge and a new field of study
is showing a strong momentum. Besides, the corresponding sphere of educational research is
actively developing. At the same time, most of the scientific publications are aimed at studying
specific issues related to the content of the programs and their methodological support. The
wider context and especially the international perspective are lacking for the necessary atten-
tion of researchers.
In this regard, the purpose of our study was to summarize and systematize information about
training programs in the field of data science presented on online platforms of the main macro-re-
gions – America, Europe and Asia. For this purpose, we found out what elements the corpus of data
science training programs consists of, as well as how courses are distributed on educational plat-
forms by countries, organizational providers, level of education and duration of study. Based on the
data obtained, we conducted a comparative interregional study of educational programs presented
on online platforms.
The findings made it possible to draw conclusions about the specifics of the global landscape of
data science online education, as well as to determine the specifics of the Russian segment and to
formulate recommendations for solving significant problems of the domestic economy using data
science online education

Research target: Education
Language: Russian
Full text
DOI
Text on another site
Keywords: обучениеlearningbig dataнауки о данныхМООК data sciencedigital online platforms MOOCs онлайн-платформы большие данные
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