Artificial Intelligence Anxiety in the Educational Context: Psychometric Adaptation of the Scale on a Sample of Russian Students
Journal
Vysshee Obrazovanie v Rossii = Higher Education in Russia
Date Issued
2026-06-24
Author(s)
Maksimenko, A. A.
Zabelina, E. V.
Kurapov, S. V.
Pevneva, A. N.
Type
Article
Abstract
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. © Максименко А.А., Круз-Карденес Х., Забелина Е.В., Курапов С.В., Певнева А.Н., 2020. Creative Commons Attribution 4.0 License.