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July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
July 15, 2026
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Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.

 

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They Think They Use AI: Assessing the Relations Between Attitudes Toward AI and AI Proficiency Among University Students

Ch. 6. P. 26–29.
Ivanova A., Tarasova K., Talov D.

As AI becomes an integral part of education and the future job market, understanding how students perceive and use it is more important than ever. This study explores Russian university students' attitudes toward AI and examines the relationship between their attitudes and their actual skill to use AI effectively. To assess students' AI perceptions, researchers used a questionnaire covering four key factors: interest in AI, perceived AI experience, AI's value for the future, and AI-related risks. AI proficiency was measured through a practical test in which students had to create an effective prompt for a large language model. The results revealed that many students actually struggled with prompting. Those who had more perceived experience with AI performed slightly better (r = 0.20), as did students who showed a stronger interest in AI (r = 0.12). However, the overall connection between AI attitudes and actual proficiency was weak. Notably, students who viewed AI as a risk were less likely to see it as valuable for the future (r = −0.09), but this did not significantly impact their interest in AI or their perceived experience with it. Ultimately, while students express a high level of interest in AI, their ability to use it effectively remains limited.

Language: English
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Keywords: AIpromptingAI risksAI values AI attitudes

In book

2025 5th International Conference on Artificial Intelligence and Education (ICAIE)
Suzhou: Institute of Electrical and Electronics Engineers Inc., 2025.
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