Жарияланымдар / Публикации
Постоянный URI для этого сообществаhttps://cris.qyzpu.kz/handle/123456789/2
Просмотр
4 результаты
Результаты поиска
- Некоторые метрики заблокированы вашиминастройками согласия
Тип записи:Публикация, Psychological prevention of teenager’s psychoactive substances use by means of self-control methods(Publishing Center Science and Practice, 2019-03-13); - Некоторые метрики заблокированы вашиминастройками согласия
Тип записи:Публикация, Полиция қызметкерлерінің психикалық қажуы мен өмір сүру сапасын бағалауThe article deals with the problem of professional burnout of police officers. Scientific and practical interest in burnout syndrome is due to the fact that this syndrome is a direct manifestation of the ever-increasing problems associated with the well-being of employees, the effi-ciency of their work and the stability of the business life of the organization. The main purpose of the study is to identify the relationship between the levels of professional burn-out of police officers of the Ministry of Internal Affairs in relation to the quality of life and factors affecting the staff on the part of the administration. The methods used were translated into Kazakh. The practical significance of the study is that the data obtained as a result of the work carried out contribute to improving the quality of work in the development of psychological recommendations, psychoprophylactic measures, including programs aimed at strengthening and preserving the mental health of law enforcement officers, reducing their emotional burnout and improving self-regulation skills. As a result, a connection was revealed between the results of methods for assessing mental burnout and the quality of life of not all, namely, only on one scale of mental burnout between "professional motivation" and all scales of quality of life. And in the quality of life assessment questionnaire, only 4 out of 8 scales had high results. Key words: professional burnout, emotional burnout, quality of life, mental health, police officers. - Некоторые метрики заблокированы вашиминастройками согласия
Тип записи:Публикация, A Multi-Modal Deep Learning Framework for Student Soft Skills Development in Adaptive Learning Environments(Science and Information Organization, 2026-01-01); ; Nuraim IbragimovaThe rapid evolution of artificial intelligence and adaptive educational technologies has created increasing demand for intelligent systems capable of automatically assessing and enhancing student soft skills within digital learning environments. This study proposes MST-SoftNet, a multimodal transformer-based deep learning framework designed for adaptive soft skill assessment and personalized educational recommendation. The proposed architecture integrates heterogeneous educational modalities, including textual interactions, speech signals, facial expressions, behavioral engagement patterns, performance indicators, and feedback information, within a unified hierarchical transformer fusion framework. Modality-specific encoders, cross-modal attention mechanisms, explainable attention visualization modules, and adaptive recommendation components were incorporated to improve both predictive performance and interpretability. Experimental evaluation was conducted using multiple baseline deep learning architectures, including CNN, LSTM, Transformer, and multimodal CNN-LSTM models. The proposed MST-SoftNet framework achieved superior performance across all evaluation metrics, attaining 93.67% accuracy, 92.11% F1-score, and 96.05% AUC, while simultaneously demonstrating reduced inference latency and improved computational efficiency. Attention visualization analysis further confirmed the capability of the framework to identify semantically meaningful multimodal behavioral patterns associated with communication, collaboration, leadership, creativity, emotional intelligence, and self-regulation competencies. Longitudinal adaptive learning experiments additionally demonstrated substantial improvement in student soft skill progression over time. The obtained results indicate that MST-SoftNet establishes a robust, interpretable, and scalable foundation for next-generation intelligent educational systems focused on personalized soft skill development and adaptive learning optimization. - Некоторые метрики заблокированы вашиминастройками согласия
Тип записи:Публикация, Fostering emotional intelligence and self-regulation in gifted high school students: experimental evidence from a soft skills development program(Frontiers Media, 2026-01-12)Цитирования (OpenAlex) 7