Problems of Social Hygiene, Public Health and History of MedicineProblems of Social Hygiene, Public Health and History of Medicine0869-866X2412-2106Joint-Stock Company Chicot265710.32687/0869-866X-2026-34-s1-371-377Научная статьяTHE STUDY OF INVOLVEMENT IN THE EDUCATIONAL PROCESS KNOWLEDGE FATIGUE AND THE LEVEL OF EMOTIONAL INTELLIGENCE OF STUDENTS USING NEURAL NETWORKSBazhenovaG. A. Bazhenova S. A. Voblaya I. N. Strizhak M. S. Perevalova A. A.Clinical psychologist private practice 353915 Novorossiysk RussiaNovorossiysk Branch of the Financial University under the Government of the Russian Federation 353900 Novorossiysk Russia270620263437137729062026Copyright © 1970,1970The relevance of the study is as follows. Traditional methods of pedagogy do not allow objective and continuous monitoring of the emotional state of each student. The teacher usually relies on subjective observations — facial expressions behavior in a group — which may be inaccurate. At the same time modern technologies provide new opportunities: cameras and sensors backed by AI algorithms are able to automatically recognize facial expressions voice intonations and other signs of an emotional state. There are already commercial solutions for facial emotion recognition which have been used in marketing and security. Their potential application in education is an important topic as automated emotion analysis could provide educators with objective data on how engaged a group is whether students are overworked and who is experiencing difficulties or stress. It is the problem of mass learning fatigue and emotional burnout according to empirical studies that makes the introduction of such systems modern and practically significant and is the topic of this article. The article notes that the introduction of AI systems that can monitor both behavioral and physiological indicators opens up new opportunities for objective registration of cognitive states. For example sensors and wearable devices can measure heart rate heart rate variability brain activity and other parameters related to the level of concentration and mental stress. Computer vision can track eye gaze direction blinking frequency and posture which indirectly indicates the level of attention or fatigue. The study presents the results of a psychometric testing study using validated tools for emotional involvement in the educational process and a study of the factors of burnout and knowledge fatigue among full-time students at the Novorossiysk branch of the Financial University under the Government of the Russian Federation. The sample consisted of 125 respondents.knowledge fatigueinclusion in the educational processpsychometric testingemotion recognitionemotional artificial intelligenceemotion recognition programsstudy of students' emotional levels using neural networksусталость от знанийвключённость в образовательный процесспсихометрическое тестированиераспознавание эмоцийэмоциональный искусственный интеллектпрограммы распознавания эмоцийисследование эмоционального уровня обучающихся с помощью нейросетей1.Zeng H., Shu X., Wang Y. et al. EmotionCues: Emotion-Oriented Visual Summarization of Classroom Videos // IEEE Transactions on Visualization and Computer Graphics. 2021. Vol. 27, N 7. P. 3168—3181. doi: 10.1109/TVCG.2019.29636592.Mayer J. D., Salovey P. What is emotional intelligence? // Emotional development and emotional intelligence: educational implications. New York; 1997. P. 3—31.3.Гоулман Д. Ключевые идеи книги: Эмоциональный интеллект. Почему он может значить больше, чем IQ. М.; 2020.4.Bustos-López M., Cruz-Ramírez N., Guerra-Hernández A. et al. Wearables for engagement detection in learning environments: a review // Biosensors (Basel). 2022. Vol. 12, N 7. P. 509. doi: 10.3390/bios120705095.Маракшина Ю. А., Исматуллина В. И., Лобаскова М. М. Стресс и стратегии совладания у студенческой молодежи: обзор исследований // Клиническая и специальная психология. 2024. Т. 13, №2. С. 5—33. doi: 10.17759/cpse.20241302016.Janssens M., Meslec N., Leenders R. T.A. J. Collective intelligence in teams: Contextualizing collective intelligent behavior over time // Front Psychol. 2022. Vol. 13. P. 989572. doi: 10.3389/fpsyg.2022.9895727.Яшкова А. Н. Изучение мотивов и мотивации учебной деятельности: учебно-методическое пособие. Саранск; 2016.8.AI can read your emotions. Should it? // The Guardian. 2019.9.Woolley A. W., Chabris C. F., Pentland A. et al. Evidence for a collective intelligence factor in the performance of human groups // Science. 2010. Vol. 330, N 6004. P. 686—688.