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June 22, 2026
‘In Science, You Are Your Own Boss
Polina Nasledskova is interested in identifying gaps in linguistics and topics that have been overlooked by other researchers. In an interview for the  Young Scientists of HSE University project, she spoke about rare ordinal numerals in Nakh-Daghestanian languages, the benefits of knitting for concentration, and the beauty of the Patriarshy Bridge.
June 19, 2026
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
June 5, 2026
'Im Used to Producing Distilled Knowledge'
Ivan Rubachev works in a HSE University laboratory established jointly with Yandex Research, where he focuses on machine learning with tabular data. In this interview with the HSE Young Scientists project, he discusses why following a vibe can be better than goal-setting, explains the concept of the Neural Turing Machine, and argues why withholding scientific knowledge is counterproductive.

 

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Моделирование компетенции в технологиях цифрового образования Ч.1.

Инновации. 2018. № 1. С. 64–71.
Башмаков А. И., Starykh V.

The article presents the guidelines of the competency modeling methodology invariant to subject domain, type of activities and psycho-pedagogical platform. The core of this methodology is systematics of the expandable metamodels adaptable to application conditions by profiling mechanism. The methodology is aimed at creating conditions for interoperability of systems and services that make up a digital education, dealing with competency description due to possibility of flexible selection of such interaction level, good information structuring and formalization, selection of competency description units repeatedly used in various contexts, as well as ontological approach. One more purpose of the methodology is preparation of grounds for realization of smart features of digital education technologies: adaptation, inferring, self-learning, anticipation.

Research target: Computer Science Education Economics and Management
Priority areas: economics
Language: Russian
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Keywords: онтологияontologyэлектронное обучениеметамодельmetamodelцифровизацияdigitalizationединица компетенциимоделирование компетенцииcompetency unitcompetency modelingdigital educationцифровое образование
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