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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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The role of social influence in generative artificial intelligence ChatGPT adoption intentions among undergraduate and graduate students

Innovations in Education and Teaching International. 2025. Vol. 62. No. 5. P. 1559–1573.
Korchak A., Al Murshidi G., Getman A., Raouf N., Arshe M., Al Meheiri N., Shulgina G., Costley J.

This study explores the role of social influence in the adoption strategies of generative artificial intelligence (GenAI) among graduate and undergraduate students. Using the Unified Theory of the Acceptance and Use of Technology (UTAUT) and its key behaviour intention determinant, social influence, the relationship between GenAI popularity among peers and its use intention was examined. Survey data (271 UAE university students) revealed a significant relationship between social influence and GenAI use intention, with undergraduate students being more affected by peers than graduates. This difference may be explained by higher autonomy, level of independence, and less cohesive peer networks among graduate students. The increased GenAI popularity among undergraduate students can also be attributed to some degree to the non-voluntary nature of their environment and a stronger peer influence. The study contributes to UTAUT advancement by extending the social influence construct to voluntary and non-voluntary GenAI use settings.

Research target: Education
Language: English
DOI
Text on another site
Keywords: graduate studentsundergraduate studentstechnology acceptancepeer influenceGenerative artificial intelligence (GenAI)GenAI use intention
Publication based on the results of:
Using digital traces to study learners' behavioral strategies (2025)
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