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  • Тревожность относительно искусственного интеллекта в образовательной среде: психометрическая адаптация шкалы на выборке российских студентов
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News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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Тревожность относительно искусственного интеллекта в образовательной среде: психометрическая адаптация шкалы на выборке российских студентов

Высшее образование в России. 2026. Т. 35. № 6. С. 102–126.
Maksimenko A., Круз-Карденес Х., Забелина Е. В., Курапов С. В., Певнева А. Н.

Today, there is a growing anxiety about artificial intelligence in the educational space, which greatly affects the willingness to make technological decisions and plan for one’s professional future. In empirical studies, AI anxiety is defined as a complex phenomenon including a range of negative emotional responses that shapes in people due to development and potential impact of artificial intelligence on various spheres of life. Given the impact of AI anxiety on learning, career choices, participation in the digital economy, and mental well-being, there is a need for its holistic conceptual description and reliable diagnosis. The aim of the study is to present a reliable and valid Russian-language tool for diagnosing AI anxiety in students. The adopted basis and modified for a student sample (N = 521) “Artificial Intelligence Anxiety Scale” (M.H. Alkhaibani et al.) showed an acceptable level of the external and internal validity as well as reliability on internal consistency. The factor analysis confirmed the five-factor structure of the questionnaire: concerns related to AI accuracy and reliability; concerns related to academic integrity (plagiarism); and concerns stemming from regulatory uncertainty (guidelines), fears of loss of learning and cognitive skills, as well as a decrease in motivation. External validity is confirmed by the correlations with neuroticism and conscientiousness as personality traits, image of the future, attitude towards artificial intelligence, and some socio-demographic characteristics. Adapted and modified psychodiagnostic tool for studying AI anxiety opens up opportunities for research on a Russian-speaking student sample.

Research target: Psychology Education
Language: Russian
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Keywords: uncertaintyсамоэффективностьучебная мотивацияRussian studentsроссийские студентынеопределённостьeducational motivationself-efficacyacademic integrityакадемическая добросовестность artificial intelligenceискусственный интеллект (ИИ)psychometric adaptationAI anxietyAI anxiety scaleИИ-тревожностьшкала ИИ-тревожностипсихометрическая адаптация
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