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News
September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.

 

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Между интересом и умением: как студенты воспринимают и применяют ИИ

Высшее образование в России. 2025. Т. 34. № 8-9. С. 9–32.
Ivanova A., Tarasova K., Talov D.

As AI becomes an integral part of education and the future labor market, it is important to understand how students perceive and use it. This study explores Russian university students’ attitudes toward AI and examines the relationship between their beliefs and actual skills in effectively using AI. A specially developed questionnaire was used to assess students’ conceptions of AI, covering four dimensions: interest in AI, subjective experience with AI, perceived future value of AI, and perceived risks associated with AI. Skills of using AI were measured through a practical task involving the creation of an effective prompt for a large language model to solve an authentic work-related problem. Results showed that many students struggled to create effective prompts. Those who considered themselves more experienced with using AI performed only slightly better (r = 0,20), as did students with a higher level of interest in AI (r = 0,12). Overall, the connection between attitudes and actual skills was weak. Students who perceived AI as risky tended to assign it less value for the future (r = –0,09), but this perception did not affect their interest in AI or their sense of personal experience. Ultimately, despite students’ strong interest in AI, their ability to use it effectively remains limited.

Research target: Education
Language: Russian
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DOI
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Keywords: AI (artificial intellence)ИИpromptingAI risksAI valuesзапросы к ИИценность ИИриски ИИустановки к ИИ
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