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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
Ragimova A., Imanaeva M., Nieto Doval C. M. et al., Frontiers in Human Neuroscience 2026 Vol. 20 P. 1–15
Background: Motor resonance reflects the activation of the motor system during the observation of others’ actions and is considered a physiological marker of the human mirror neuron system (MNS). This study investigated whether the excitatory and inhibitory balance in the primary motor cortex, driven by glutamatergic and GABAergic mechanisms, is linked to the strength of ...
Added: October 2, 2026
Sorokin P., Morozova E., Goshin M. E. et al., Высшее образование в России 2026 Т. 35 № 3 С. 63–89
The purpose of this study is to empirically identify the potential of contemporary educators involved in university entrepreneurship support initiatives as potential drivers of ecosystem development. This is achieved through an analysis of their key individual characteristics, professional experience, pedagogical practices, and the institutional context of the university environment. To this end, based on a ...
Added: October 2, 2026
Nisskaya A., Беляевская Е. С., Современная зарубежная психология 2026 Т. 3 № 15 С. 89–97
Context. The preschool period is a critical stage for the development of prosocial behavior. Children begin to understand the feelings of others, and the foundations of empathy and mutual assistance are formed. Situation-specific expressions of care can develop into more stable forms when children are embedded in a system of social relationships. However, the specific characteristics ...
Added: October 2, 2026
Pavlova A., Тихомирова Т. Н., Исматуллина В. et al., Вестник Санкт-Петербургского университета. Психология 2025 Т. 15 № 4 С. 610–632
Представлены результаты анализа психометрических свойств русскоязычной версии Шкалы личностной тревожности (STAI-T) на масштабной выборке студентов вузов Российской Федерации. Личностная тревожность отражает предрасположенность к чрезмерному проявлению тревоги в отношении широкого круга событий, восприятие их как потенциально опасных, что приводит к трудностям адаптационного характера, в том числе на этапе перехода в систему высшего образования. Уровень проявления тревожности ...
Added: October 2, 2026
Lubashevsky I., Lubashevskiy V., Physica D: Nonlinear Phenomena 2026 Vol. 498 Article 135441
We develop a novel cloud-function formalism describing the dynamical relationship between sensory-information processing in large-scale brain networks (supraliminal processing) and the content of the mental representation of an observed object. The formalism combines elements of neural field theory for large-scale neural activity with the spatial characteristics of perceived objects and their embedding in the environment ...
Added: October 2, 2026
Белов Б. П., Kocharian R., Самойлов И. А. et al., Стандарты и качество 2026 № 10 С. 105–109
Acceptance of enterprise AI search requires checking answer correctness and access controls, defining acceptable errors, and assessing whether testing is sufficient. A record for individual acceptance criteria was developed. Its eight fields link requirements and risks to system configuration, testing, and the acceptance decision. The fields are mapped to provisions in four Russian standards. The ...
Added: October 1, 2026
М.: Национальный исследовательский университет "Высшая школа экономики", 2026.
The next collection “Cases of Russian Universities” contains cases developed in the master’s program “Management in Higher Education,” which has been offered since 2011 by the Institute of Education at the National Research University Higher School of Economics. The program is intended for university staff aiming for a managerial career or seeking to develop their ...
Added: October 1, 2026
Мичурина А. А., Гуманитарные науки и образование 2026 Т. 17 № 3 С. 82–87
China pays special attention to the application of artificial intelligence (AI) technologies in various spheres of life, including education. The integration of AI into the field of education carries many opportunities. At the same time, this process is associated with a large number of risks, which raises the issue of the need for legal regulation ...
Added: October 1, 2026
Kotov A. A., Матушкина В., Котова Т. Н., Современная зарубежная психология 2026 Т. 15 № 2 С. 111–119
Контекст и актуальность. В обзоре рассматривается эффект выученного невнимания (трудности в обраще-нии внимания на информацию, которая ранее была нерелевантной) на примере категориального науче-ния. Цель теоретического обзора: сформулировать основные этапы изучения данного эффекта, обозначитьключевые работы, объясняющие факторы, влияющие на данный эффект (фактор задачи и семантическойнагруженности). Результаты. Приводятся доказательства того, что эффект рассматривается в настоящеевремя в разных ...
Added: October 1, 2026
Kotov A. A., Зайцева Е. С., Новые психологические исследования 2026 № 3 С. 35–54
Эффект категориальной различимости выражается во влиянии окружения целевого объекта при его запоминании: эффективность запоминания целевого объекта выше в условии его окружения объектами из той же суперординатной категории, к которой он относится, чем объектами из другой суперординатной категории.
Целью исследования было изучение эффекта категориальной различимости в условиях различной загрузки рабочей памяти – вербальной и визуальной.
Категориальная репрезентация играет ...
Added: October 1, 2026
Klochko O., Кузнецова М. П., Пространственная экономика 2026 Т. 22 № 3 С. 73–103
The article assesses China’s technological sovereignty in high-tech industries that form the ecosystem of physical artificial intelligence and its readiness to develop intelligent robotics. The aim of the study is to identify changes in China’s position in the global value chains of these industries through a comprehensive analysis of foreign value added used in production, ...
Added: October 1, 2026
Латыпов А. Ф., Психология и право 2026 Т. 16(3) № 3 С. 259–272
Abstract Context and relevance. The simultaneous presence of three to five age cohorts within a single organizational space makes intergenerational tension in contemporary organizations increasingly systemic, raising the need for a theoretical understanding of the nature and mechanisms of intergenerational conflicts. Objective. The article aims to provide a theoretical analysis of the phenomenon of intergenerational ...
Added: September 30, 2026
Dvoinin A., Развитие личности 2025 № Спецвыпуск С. 17–20
The article outlines A.M. Dvoinin’s personal reminiscences of his teacher, the prominent psychologist Valeria Sergeevna Mukhina ...
Added: September 30, 2026
Dvoinina V. K., Dvoinin A., Natural Systems of Mind 2026 Vol. 6 No. 3 P. 18–38
Background and research problem. The prevalence of epistemically unwarranted beliefs makes it critically important to study human cognitive capacities to resist indoctrination by pseudoscientific, conspiracist, and paranormal doctrines. The research problem addressed the question of whether cognitive abilities and rationality protect against susceptibility to epistemically unwarranted beliefs. Objective. To present a theoretical analysis of contemporary ...
Added: September 30, 2026
Patarakin Y., Kutuzov A., Искусственные общества 2026 Т. 21 № 3 Статья 10
This paper presents STiMUS (Stigmergy and Mutualism in Socio-Technical Systems), an agent-based model implemented in NetLogo 7.0. The model formalises two complementary coordination mechanisms in digital project teams. The first is stigmergy: contributor agents select shared artefacts to work on by following traces left by previous editors, without explicit communication. The second is mutualism: artefacts ...
Added: September 30, 2026
Сапожникова М. А., Новые психологические исследования 2026 № 3 С. 115–134
Russian psychology lacks validated instruments for the comprehensive assessment of commitment in romantic relationships. Existing measures primarily focus on relationship satisfaction while overlooking key determinants of relationship stability, such as accumulated investments and the perceived quality of alternatives, as conceptualized in Caryl Rusbult’s Investment Model.
The objective was to adapt and psychometrically validate the Russian-language version of the ...
Added: September 29, 2026
Akhmedjanova D., М.: Издательский дом НИУ ВШЭ, 2026.
Восемнадцатый выпуск серии учебно-методических пособий «Подготовка профессионалов для нового образования» посвящен преподаванию курса по метакогнитивной регуляции обучения на магистерской программе «Педагогическое образование» Института образования НИУ ВШЭ. Пособие систематизирует современные знания о природе, диагностике и развитии саморегуляции в образовании и призвано восполнить дефицит качественных русскоязычных публикаций, интегрирующих достижения отечественной научной школы и передовые международные исследования. Пособие ...
Added: September 29, 2026
Almugren I., Chotia V., Habib M. D. et al., Journal of Knowledge Management 2026 P. 1–22
Purpose
The convergence of artificial intelligence (AI) and immersive digital environments has positioned these systems as a potential knowledge infrastructure. However, prior research largely assumes that immersive experience and intelligent systems naturally translate into effective knowledge use and strategic outcomes. This study aims to examine how experiential, perceptual and strategic factors shape the cognitive internalization and ...
Added: September 25, 2026
Festa G., D'Amato A., Palladino R. et al., European Journal of Innovation Management 2026 Vol. 29 No. 3 P. 728–744
Purpose
Artificial intelligence (AI) is vastly impacting the digital transformation of societies, economies, businesses, markets and enterprises, at a very fast pace, mostly after the global success of the generative algorithms. In this respect, this study, with an exploratory intention, aims to provide evidence about the fundamental issues of AI, particularly if generative, when adapted to ...
Added: September 24, 2026
Snegirev A., Sychev S., Futures 2026 Vol. 183 P. 1–22
This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, ...
Added: September 23, 2026
Кузнецова М. П., Klochko O., Современная мировая экономика 2026 Т. 4 № 2 С. 6–25
The article examines the positions of the world’s largest countries in the industrial robotics sector as one of the key areas for the physical artificial intelligence (AI). The aim of the study is to conduct a comparative assessment of the readiness of leading economies to develop physical AI based on an analysis of production, foreign ...
Added: September 23, 2026
Тыров И. А., Васильев Ю. А., Владзимирский А. В. et al., Труды Института системного анализа Российской академии наук 2026 Т. 76 № 3 С. 79–89
Large language models (LLMs) in healthcare currently attract significant interest. This study compared GigaChat and YandexGPT by evaluating 1,200 LLM-generated responses to physician queries from outpatient and inpatient settings across 7 topics. Thirteen expert physicians assessed the responses using a 5-point scale across five criteria: relevance, correctness, safety, completeness, and language literacy. We performed paired ...
Added: September 22, 2026
Ulyanina O. A., Vikhrova E. N., RUDN Journal of Psychology and Pedagogics 2025 Vol. 22 No. 2 P. 337–360
Rapid digitalization of higher education and the rise of artificial intelligence (AI) in instruction call for careful evaluation of their impact on students. Traditional face-to-face lectures and those given by an AI-avatar, remote online courses, each create distinct conditions that shape the classroom psychological climate and comfort. Prior research shows AI integration increases engagement, but ...
Added: September 21, 2026
Моисеев Г. В., Гуманитарные исследования в Восточной Сибири и на Дальнем Востоке 2026 № 2 (76) С. 58–68
The article presents a philosophical analysis of the transformation of labor in the context of the spread of AI technologies. Criticizing the notion of AI as an autonomous and neutral technology leading to the replacement of human labor, the author proposes to analyze the social consequences of AI development within the framework of automation processes ...
Added: September 17, 2026