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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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Incidental findings in relation to subsequent search misses in visual search

Psychology. Journal of the Higher School of Economics. 2022. Vol. 19. No. 4. P. 725–735.
O. S. Rubtsova, E. S. Gorbunova

Incidental findings defined as valuable findings that are not searched purposely by the experts were originally discovered by radiologists. Despite the importance and great practical value of this phenomenon for visual search, it was almost not studied by cognitive psychologists and vision science experts. The current study aimed to examine experimentally incidental findings in visual search. The main objective was to clarify independence of incidental findings from subsequent search misses, another well-known visual search phenomenon. In order to do that, the standard experimental paradigm for detecting subsequent search misses was used. At the same time the stimuli material and tasks were created to closely fit the definition of incidental findings. The participants were asked to find the images of plastic bags and paper wastes (targets) among the images of leaves and snags (distractors) on the computer screen in a simulated “garbage collection” task. Their accuracy and reaction times were analyzed. Specifically, the trials with a single target were compared with dual-target trials. The findings revealed that subsequent search misses, but not incidental findings, were observed. The results suggest that incidental findings may be closely related to subsequent search misses. As well as that, the difficulty of the task, particularly induced by target-distractor similarity, may be one of the major factors leading to the emergence of subsequent search misses instead of incidental findings.

Research target: Psychology
Language: English
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Keywords: зрительный поискvisual attentionsubsequent search missesпропуски при продолжении поискаВизуальное внимание visual searchincidental findingsвнезапные находки
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