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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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Типология результатов сотрудничества российских вузов с бизнесом

Высшее образование в России. 2024. Т. 33. № 11. С. 108–131.
Melikyan A.

  Development of high-tech industries is an important task for the Russian economy, the solution of which requires the joint efforts of educational, research and production organizations with the governmental support. Nowadays significant results have been achieved in the field of cooperation between universities and business. Their systematization and analysis will make it possible to determine both the most effective areas of interaction and those requiring further development.

   The purpose of the research presented in the article is to identify typical models of cooperation between universities and business based on analyzing the results of their scientific and educational interaction.

   To realize it, clustering of Russian universities was carried out. The cluster analysis identified 6 groups of universitates, each of which has specific features. Universities in the first two clusters are focused on commercializing income from R&D. Universities of cluster 1 are distinguished by a high share of extra-budgetary income from R&D, and from cluster 2 are distinguished by high extra-budgetary income from R&D based on the number of academic staff members. Universities from cluster 3 have high results of joint publication activities with business companies. In universities from clusters 4 and 5 educational cooperation with business is more developed. Universities from cluster 4 have an extensive network of partnerships with enterprises to organize internships for students. Universities from cluster 5 actively cooperate with business to train specialists on a contractual basis. Cluster 6 includes universities that have low results in all areas of cooperation with business. The results of the study demonstrate the main approaches of universities to interact with business companies. The research task was implemented for the first time on a representative sample of Russian universities based on an analysis of the quantitatively assessed results of their cooperation with business. The article may be of interest to universities aimed at developing partnerships with business companies, as well as government authorities developing projects to support university-industry interaction. Support measures could become more diversified, considering the specific features of each cluster, and be aimed at stimulating the development of priority areas of cooperation with business for a particular university.

Research target: Education
Language: Russian
DOI
Text on another site
Keywords: research projectsнаучно-исследовательские проектыuniversity clusterseducational cooperationобразовательное сотрудничествоtriple helix modelresearch fundingмодель тройной спираликластеры вузовсотрудничество вузов и бизнесафинансирование научных исследованийuniversity-business cooperationquadruple helix modelinternships for studentsмодель четверной спиралипрактики и стажировки студентов
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