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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.
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.
Keywords: uncertaintyсамоэффективностьучебная мотивацияRussian studentsроссийские студентынеопределённостьeducational motivationself-efficacyacademic integrityакадемическая добросовестность artificial intelligenceискусственный интеллект (ИИ)psychometric adaptationAI anxietyAI anxiety scaleИИ-тревожностьшкала ИИ-тревожностипсихометрическая адаптация
Voronina Y., Kuryan M., Вестник Мининского университета 2025 Т. 13 № 4 Статья 2
Introduction. The use of artificial intelligence (AI) tools in the educational process is expanding, particularly in teaching English writing. Despite this growth, there remains a need for deeper exploration into how AI can enhance the effectiveness of teacher feedback received by students on their written works. This study aims to investigate collaborative approaches between teacher ...
Added: July 6, 2026
Dvoeglazova M., Visual Cognition 2026 P. 1–16
Rectangularity can be an a priori constraint for the visual system to recover a 3D shape from a 2D image. Two psychophysical experiments (n = 16 each) were conducted to test whether observers are biased to perceive trihedral corners as rectangular and whether this bias is perceptual rather than a response bias. The results of ...
Added: July 6, 2026
Grebnev L., Вопросы философии 2025 № 6 С. 105–116
The relevance of the topic is related to the fact that after the complete abandonment of real values in the 1970s of the main means of international settlements - the US dollar – there is a growing feeling that money increasingly represents an illusory reality. The article begins with an analysis of the illusions associated ...
Added: July 6, 2026
М.: Институт консультативной психологии и консалтинга (ФПК-Институт), 2024.
The sixth volume of this year book on client-centered psychotherapy and person-centered approach, published by PCA Russia and the institute of counselling psychology and consulting (FPC institute) gathers the translations of Carl Rogers’ articles and his followers from Russia. They observe the peculiarities of client-centered psychotherapy and person-centered approach. The key components of Rogers’ triad ...
Added: July 6, 2026
Stoyanova O., Окусков И. С., Бизнес-информатика 2026 Т. 20 № 2 С. 81–93
The integration of artificial intelligence (AI) into information technologies is reshaping competency requirements for IT specialists. However, AI competency penetration into the early phases of the Software Development Life Cycle (SDLC) – requirements analysis and planning – remains underexplored. Existing studies either rely on static competency models lacking empirical validation or analyze the labor market ...
Added: July 5, 2026
Volkova N., Кочетков Н. В., Чикер В. А., Психологическая наука и образование 2026 Т. 31 № 3 С. 35–49
Context and relevance. Artificial intelligence is a technology with the potential to fundamentally transform all spheres of human life. Its rapid integration into everyday reality intensifies research dedicated to the psychology of using neural networks. However, the development of empirical research in the Russian scientific field is limited by the lack of validated psychodiagnostic tools that ...
Added: July 5, 2026
Хилинская О. С., Leykina A., Журнал клинического и прикладного психоанализа 2026 Т. VII № 2 С. 104–121
Questions of the interrelation of manifestations played out on the psychic stage and at the level of
the body have been the object of research in both psychiatry and psychoanalytic psychopathology
for a long time, since the time of Hippocrates. With the advent of psychoanalysis, a revolution took
place in the
fi
eld of psychosomatics, Freud brought something that would ...
Added: July 4, 2026
Velikaya E. V., Baranova T., Джахангирова В. С. et al., Национальный книжный центр, 2026.
Учебное пособие предназначено для обучения академическим навыкам чтения, говорения и письма на основе статей из научно-популярных журналов по различным профилям: образование, программирование, лексика гейм-дизайна, продуктовые исследования, создание цифровых продуктов для различных сфер жизни, UX-исследования и юзабилити-тестирование, маркетинг игр и цифровых продуктов. Упражнения, разработанные для каждого урока, ориентированы на развитие профессионального вокабуляра, написание обобщений (summary) и ...
Added: July 3, 2026
Imbault C., Slioussar N., Ivanenko A. et al., The Mental Lexicon 2026 P. 1–23
The study examines emotional responses to words representing a wide range of psychological valence and focuses on gender-related differences. We aimed to find out whether men and women differ in their emotional responses, and whether they can take the perspective of another gender. We used the slider paradigm (Warriner et al., 2017): participants saw a humanoid ...
Added: July 2, 2026
Oluwafemi K. M., NORDIC JOURNAL OF COMPARATIVE AND INTERNATIONAL EDUCATION 2026 Vol. 10 No. 2
This study examines post-pandemic changes in professional development, teaching practices, and well-being in Denmark, Finland, Norway, and Sweden using data from the Teaching and Learning International Survey (TALIS) 2018 and 2024. Drawing on the Job Demands-Resources (JD-R) framework and informed by governance typologies as a comparative contextual lens, the study uses a repeated cross-sectional design ...
Added: July 1, 2026
Shilmanskaya A., Leontiev D., Культурно-историческая психология 2026 Т. 22 № 2 С. 86–97
Context and relevance. The issue of personality changes has become a significant trend in personality research over the past decade. Traditional approaches to assessing the effectiveness of psychotherapeutic work are based on comparing measurement results before and after intervention. Objective. To test the visual “Trajectory” method for assessing the perceived trajectory of individual development and to verify its ...
Added: July 1, 2026
Selskiy A., Snegirev A., Колбин Е. И. et al., В кн.: Цифровая клиентоцентричность. Как современные технологии помогают компаниям и государству сделать шаг навстречу потребителям.: М.: ИСИЭЗ ВШЭ, 2026. Гл. 2 С. 71–142.
The second chapter of the monograph analyzes the current megatrends of customer centricity, shaped by digital technologies and transforming the approaches of companies and government bodies to customer and citizen engagement. Based on semantic big data analysis (using the iFORA system) and expert interviews, the authors identify four key megatrends.
The first megatrend, proactive engagement and personalization, describes ...
Added: June 26, 2026
Kosmarsky A., Напреенко И. В., Journal of Cultural Economy 2026 P. 1–4
Added: June 23, 2026
Pruzhinin B. I., Afanasov N., Буданов В. Г. et al., Вопросы философии 2026 № 5 С. 5–35
In December 2025, the Institute of Philosophy of the Russian Academy of Sciences hosted an international roundtable on the topic “Social Programming as a Methodological Tool of Network Self-Organization: Problems and Trends”.
The roundtable was organized by the journal “Voprosy Filosofii” and representatives of the research project No. 25-28-00707, “Social Programming as a Problem of Network ...
Added: June 18, 2026
Romanova T. V., Бинштейн М. М., Медиалингвистика 2026 Т. 13 № 1 С. 28–50
В данной статье противопоставляется узкое и широкое понимание содержание термина ИИ, фиксируется история его появления. Функционирование термина ИИ рассматривается в сопоставительном аспекте по данным российских и китайских медийных источников: ...
Added: June 14, 2026
Barkhatova L., Социологические исследования 2026 № 5 С. 71–83
The article conceptualizes the methodological potential of hyperlink network analysis as a tool of empirical reconstruction of social interaction through digital traces. Using the partnership network of Russia’s artificial intelligence (AI) ecosystem as a case, the paper presents an original analytical framework for translating technical hyperlink data into sociological categories. The study describes a full ...
Added: June 12, 2026
Butorova A., Bobakov V., Sergeev A. et al., European Physical Journal: Special Topics 2026 P. 1–19
This paper presents a review of artificial intelligence (AI) methods for failure prediction in data center cooling systems, with a focus on the integration of digital twins (DTs), physics-informed learning, and graph-based models. Positioned within complex network science, this review addresses a limitation of conventional graph approaches—their reliance on pairwise connectivity—whereas real-world failures often arise ...
Added: June 10, 2026
Fonotov A., Kosychev A., Управление наукой: теория и практика 2026 Т. 8 № 1 С. 12–31
The study compares the national artificial intelligence (AI) strategies of the United States, China and Russia, assessing their substantive completeness and governance logics. It employs a hybrid framework that combines governance approaches (anticipatory, reflexive, experimentalist and tentative) with a content analysis of the structures of the strategies. The results show that the United States relies ...
Added: June 4, 2026
Seul: PMLR, 2026.
Added: June 4, 2026
Levin J., Oprea T. I., Davidovich S. et al., Nature Biotechnology 2020 P. 1127–1131
The COVID-19 pandemic has transformed the way scientific and clinical results are shared and disseminated. According to a recent analysis, an average of 367 COVID-19 papers are being published every week, with a median time from submission to acceptance of just 6 days (compared with 84 days for non-COVID-19 content)1. These unprecedented peer review turnaround ...
Added: June 1, 2026
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Milovidov S., Bulgakov V., Информатика и образование 2026 Т. 41 № 2 С. 32–43
Research continues the academic discussion regarding the implementation of deep machine learning technologies, commonly referred to as artificial intelligence, into the educational process, and their impact on established practices within the Russian higher education system. Over recent years, a substantial body of research has emerged, focusing on interaction with these algorithms in the context of ...
Added: May 18, 2026
Федоров Н. С., Финансовый журнал 2025 Т. 17 № 6 С. 99–112
The DCF model is one of the most commonly used models in valuing companies for investment deci sions. Nevertheless, estimating the accuracy of this model remains an important research question. This article presents an assessment of the accuracy of DCF model specifications based on analyzing the variance of fair share prices of companies listed on ...
Added: May 15, 2026
Федоров Н. С., Финансы и бизнес 2025 Т. 21 № 3 С. 34–50
Currently, the role of artificial intelligence is increasingly playing a significant role in various fields, including the increasing role of machine learning in finance. On the other hand, company valuation remains an important part of research due to its difficulty in correctly predicting the accuracy of target stock prices. This study provides an analysis of ...
Added: May 15, 2026