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Subject
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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Which Peers Matter: How Social Ties Affect Peer-Group Effects

Research in Higher Education. 2016. Vol. 57. No. 4. P. 448–468.
Poldin O. V., Valeeva D., Yudkevich M. M.

We study how the achievements of university students are influenced by the characteristics and achievements of peers in individuals’ social networks. Defining peer group in terms of friendship and study partner ties enables us to apply a network regression model and thereby disentangle the influence of peers’ performance from that of peers’ background. We find significant positive peer effects via the academic achievements of friends and study partners. Students’ grades increase with the abilities of study partners, who may or may not also be friends; no such effect is observed for friends who are not also study partners. Additionally, the effects of the abilities of other classmates are found to be insignificant. The results support the claim that peer influence acts mainly through knowledge-sharing channels between students who are connected by social ties

Research target: Economics and Management Education
Priority areas: economics
Language: English
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DOI
Text on another site
Keywords: социальные сетивысшее образованиеsocial networksstudent achievementpeer effectsэффекты сообученияhigher educationобразовательные достижения студентов
Publication based on the results of:
Institutional Determinants of Agent Behavior in Various Markets (2016)
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