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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.
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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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Non-academic staff and technical efficiency of Russian universities 2012–2021

Applied Economics. 2025.
Agasisti T., Akuneeva T., Egorov A., Platonova D., Serebrennikov P.

This paper investigates the relationship between the proportion of non-academic staff in universities

and their organizational efficiency of Russian universities. Recognizing the differing production

functions of research-intensive and teaching-intensive universities, we implement two distinct

model specifications in efficiency estimation. A novel panel conditional order-m efficiency estimator

is applied, incorporating the share of non-academic staff and the time variable (2012–2021) as

simultaneous exogenous factors. The findings demonstrate that the inclusion of these exogenous

variables affects the variance of efficiency scores differently in teaching-intensive and research-

intensive universities. For research-intensive universities, no robust evidence emerges to suggest

a statistically significant relationship between the share of non-academic staff and institutional

efficiency. In contrast, teaching-intensive universities exhibit a positive relationship between the

proportion of non-academic staff and efficiency, both in the full sample and in analyses of specific

years. An extension of the empirical analysis (possible only for 2019) reveals a positive association

between the proportion of specifically administrative staff and efficiency.

Research target: Economics and Management Education
Language: English
DOI
Text on another site
Keywords: university efficiencyconditional efficiencyUniversity productivitynon-academic staffadministrative staff
Publication based on the results of:
The formation of a national higher education system: key changes and their effects (2025)
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