Training System Research Articles

In this article, the authors examine the features of the organization of pre-university training in the context of globalization. Summarizing the Russian experience of strategies for preparing students for admission, the authors conclude that the dominant focus is on the comprehensive and harmonious development of the individual at the pre-university stage. In the Chinese system, on the other hand, there is an emphasis on intensive training in specialized subjects. The article analyzes the challenges and prospects of integrating international cooperation into the pre-university training system and concludes that there is a need for cooperation and exchange of experience to improve the quality of education.

The article considers current issues of publishing activity in the scientific training system of Russia under conditions of modern challenges. The geopolitical situation has led to the restriction of participation of Russian scientists in international scientific collaborations and access to leading world publications indexed in Scopus and Web of Science. The analysis shows that while the quantitative indicators of publication activity remain important as a criterion for evaluating the effectiveness of scientific organizations, their growth does not correlate with the improvement in the quality of research. Special attention is paid to the little-known problem of publication activity of students and young researchers. There is a lack of systematic mechanisms for accounting their scientific results, underestimation of the contribution to the academic environment and lack of elaboration of methodological approaches to the analysis of their research activities. A set of measures is proposed, including improvement of the scientific management system, optimization of organizational conditions and creation of effective mechanisms to stimulate research activity at all levels of academic training.

The article identifies modern trends, challenges, and strategies for the formation of competencies of future specialists in the field of physical culture and sports in the context of dynamic social transformations. It is determined that the formation of professional competence among future specialists in physical culture and sports is a multilevel process that involves the integration of cognitive, motivational, activity-based, and value components, combining theoretical, practical, and innovative aspects of professional training. The key trends in the transformation of the training system are described: competence-oriented education, digitalization of the educational process, internationalization, and multidisciplinarity of education. The main challenges in the training of future professionals are defined, including the rapid pace of scientific and technological innovation, insufficient funding, and low readiness for innovation. The directions for modernizing professional training are substantiated, which include updating educational programs and methods of their implementation, investing in infrastructure and personnel development, stimulating scientific research and practical implementation, and deepening international cooperation. It is emphasized that the successful formation of competencies in future specialists is possible only under the condition of a systematic renewal of the educational process, the introduction of innovative technologies, and the improvement of teachers’ qualifications.

This article explores the integration of Industrial–Organizational Psychology and Human Factors to enhance human performance, safety, and decision-making in aviation. The study draws upon empirical and theoretical foundations to analyze how cognitive, behavioral, and organizational processes affect pilot efficiency and flight safety. Using a mixed methodological approach that combines qualitative observation and quantitative data, the paper identifies critical determinants of human reliability, including fatigue, stress, workload management, and mental health. The analysis highlights the central role of psychological assessment, training systems, and leadership culture in fostering resilience and adaptive expertise among aviation professionals. Findings indicate that applying evidence-based psychological principles within aviation environments improves decision quality, reduces human error, and supports proactive safety management. The proposed integrated framework emphasizes the continuous interaction between individual capabilities and organizational systems, offering a scientific basis for optimizing performance, minimizing risk, and cultivating psychological well-being in high-reliability aviation contexts.

This study addresses the critical skills gap between Technical and Vocational Education and Training (TVET) systems and industry needs by proposing a conceptual framework for Public-Private Partnerships (PPPs) in TVET. Despite TVET's potential to enhance employability, many systems—particularly in developing economies—struggle with outdated curricula, inadequate infrastructure, and weak industry linkages. Through a mixed-methods approach combining literature review, case studies (e.g., Malaysia’s Penang Skills Development Centre and Bangladesh’s SEIP program), and stakeholder interviews, the study identifies key mechanisms for effective industry–academia collaboration: joint curriculum design, shared infrastructure, faculty exchanges, and standardized apprenticeships. Findings reveal that institutionalized PPPs significantly improve graduate employability (e.g., SEIP’s 70% placement rate) but face challenges like cultural mismatches and funding asymmetries. The proposed framework integrates governance, resource-sharing, and monitoring components to align TVET with labor market demands. Recommendations include policy incentives for private-sector engagement, phased pilot testing, and robust M&E systems. This research contributes a scalable model for bridging the skills gap while emphasizing contextual adaptation for low- and middle-income settings.

Anthracnose commonly known as “Bird’s Eye Spot,” is a major fungal disease of grape primarily affecting young leaves, shoots, tendrils and berries, causing leaf fall, stunted growth, reduced yield and significant yield and economic losses. An intensive roving survey was conducted during Kharif 2024 and rabi season of 2024-25 across Vijayapura, Kalaburagi, Koppal and Bagalkot districts to assess disease severity. Anthracnose of grapes was prevalent in all surveyed districts of Northern Karnataka, with higher severity during back pruning (April) than fore pruning (October). The taluk wise severity ranged from 47.83 (Kukanoor) to 72.75 (Raichur) per cent in back pruning and 6.50 (Mudhol) to 23.16 (Aland) per cent in fore pruning. The district wise mean severity was highest in Raichur during back pruning (72.75%) and lowest in Kalaburagi (58.70%), whereas, in fore pruning highest severity was recorded in Raichur (22.15%) and lowest in Bagalkot (7.63%). While at the village level, the highest village level severity (80.25%) was observed in Rugi of Vijayapura district during back pruning, whereas the lowest severity (45.25%) was recorded in Talakal village of Koppal district. During the fore pruning season, the maximum severity (25.75%) was recorded in Kerur village of Kalaburagi district, while the minimum severity (4.50%) was observed in Mudhol Rural of Bagalkot district. Variation in disease severity was influenced by climatic factors, pruning stage, training systems and vine susceptibility.

Metabolic syndrome (MS) components, mainly correlated with insulin resistance and diabetes, constitute physiological disturbances that are objectively detectable based on physiological and anatomical measurements. In particular, the scientific literature indicates clear associations between features extracted from electrocardiograph (ECG) signals and MS. However, there exist few scientific studies related to MS detection by means of ECG signals, specially in automatic computer aided systems. This paper aims at developing and evaluating automatic tools for possible MS detection based on ECG signals. To evaluate how accurately and precisely the developed classifier systems detect MS from ECG signals, we use the following procedures. Initially, we use algorithms that automatically extract Q, R, and S peaks from ECG waveforms. Subsequently, we extract temporal features mainly associated with averages and variances of intervals and ratios between successive Q, R, and S peaks. We also use features describing the cardiac axis. The features are then used for training and testing classifier systems, including Support Vector Machines (SVMs) and RobustBoost classifiers. We also test the use of classifiers operating on raw ECG signals, without preliminary explicit feature extraction. The tested models constitute different configurations of Convolutional Neural Networks (CNNs). Our results indicate that it is possible to classify ECG signals in two different classes, separating people with MS from a control group, with statistically significant results. SVM, RobustBoost, and CNN models obtained average accuracy values equal to 94%, 89%, and 98%, respectively. These results indicate that automatic computer-aided diagnositcs of MS can be added to standard ECG clinical exams.

In this work, we propose a new physics-informed neural network framework based on the method of separation of variables (SVPINN) to solve the distributed-order time-fractional advection–diffusion equation. We develop a new method for calculating the distributed-order derivative, which enables the fractional integral to be modeled by a network and directly solved by combining automatic differentiation technology. In this way, the approximation of the distributed-order derivative is integrated into the parameter training system of the network, and the data-driven adaptive learning mechanism is used to replace the numerical discretization scheme. In the SVPINN framework, we decompose the kernel function of the Caputo integral into three independent functions using the method of separation of variables, and apply a neural network as a surrogate model for the modified integral and the function related to the time variable. The new physical constraint generated by the modified integral serves as an extra supervised learning task for the network. We systematically evaluated the feasibility of the SVPINN on several numerical experiments and demonstrated its performance.

BackgroundIn many countries, including Canada, employers have a legal obligation to provide training programs to the new workers to reduce the risk of musculoskeletal disorders (MSDs). However, current safety and health training modalities, including those specific to ergonomic and MSD prevention, have shown limited success in promoting safe motions patterns. As workers gain more experience, they develop the knowledge and skills necessary to consistently demonstrate safer and more productive performance in tasks within their areas of expertise compared to novices and apprentices. Training apprentices using expert work strategies is a potential intervention that can reduce MSD risk while balancing productivity needs. By understanding the perspectives of experts in the field, we investigate the specific needs of masonry workers and their employers to improve masons’ safety and health.MethodsThis study conducted qualitative user interviews with eight masonry instructors with more than 20 years of experiences from the Ontario Masonry Training Centre. The eight instructors had an average of 23.9 years of experience as masons with a range between 10- and 43-years. As instructors, they had an average of 6.9 years’ experience with a range between 1.5- and 18-years.ResultsThematic analysis using template methodology was carried out on the data collected and identified six key themes: knowledge of muscle injury risks and prevention, safety in masonry, physical demands and MSD risk, the impact of physical demands, safety culture and attitudes, and the role of safety in apprentice training. The instructors’ exposure to high physical demands within masonry was a major theme during the interviews. Instructors discussed the high forces, repetition and awkward postures which take a toll on their bodies. Another large theme was about the safety culture and attitudes within the trade. Younger apprentices often think themselves invincible and show less concern towards musculoskeletal safety, whereas the older masons are more concerned.ConclusionThe findings highlight the need for apprenticeship training programs to include modules on safe lifting practices, ergonomic awareness, and long-term injury prevention. They also emphasize the importance of mentorship from experienced masons, structured rehabilitation support after injuries, and connecting ergonomic practices to productivity outcomes. Instructors’ perspectives provide valuable context to guide the development of ergonomic training systems that are both relevant to masonry work and tailored to the needs of apprentices and their employers.

This research is based on a systematic review of machine learning (ML) approaches for the cognitive load (CL) assessment of applications for unmanned aerial system (UAS) operator training. The review synthesises evidence on how ML techniques have been applied to assess CL using diverse data sources, including physiological signals (e.g., EEG, HRV), behavioural measures (e.g., eye-tracking), and performance indicators. It highlights the effectiveness of models such as Support Vector Machines (SVMs), Random Forests (RFs), and advanced deep learning (DL) architectures such as Long Short-Term Memory (LSTM), as well as how the use of different methods affects the performance of ML models, with studies reporting accuracies of up to 98%. The findings also indicate that, compared with traditional UAS training approaches, ML approaches can enhance training by providing adaptive assessment, with methodological factors such as model selection, data preprocessing, and validation being central to ML assessment performance. These findings highlight the value of accurate CL assessment as a foundation for adaptive training systems, supporting enhanced UAS operator performance and operational safety. By consolidating the methodological insights and identifying research gaps, this review provides valuable background information for advancing ML-based CL assessment and its integration into adaptive UAS operator training systems to enhance UAS operator training.

The subject of the study is the interaction of the banking system and government authorities in achieving the national development goals of the Russian Federation. The purpose of the work is to identify factors hindering the strengthening of the economy, ensuring financial sovereignty, import substitution, creating conditions conducive to industrial growth at a rate exceeding the global average, clarifying the role and responsibility of government authorities in achieving national development goals in cooperation with the Bank of Russia, as well as making proposals to resolve contradictions between credit and government organizations in strengthening economy and reduction of inflation. The analysis of empirical data provided by ROSTEC State Corporation, the Russian Union of Industrialists and Entrepreneurs, the Center for Macroeconomic Analysis and Short-term Forecasting, Ministry of Economic Development, current and forecast data on Industry and agriculture in the Nizhny Novgorod region, with a grouping of production facilities based on their dependence on lending rates and government support, is carried out. The experience of the USA and Turkey in regulating inflation is considered. Proposals have been put forward to reduce inflation and strengthen the economy through financial and legal methods, as well as improving the system of cognitive training for students. It is concluded that the high inflation rate is due to the lag in the growth of production and supply of goods on the market from consumer demand, largely due to the high lending rate.

The increasing demand for customized products has raised the significant challenges of increasing performance and reducing costs in the industry. Facing that demand requires operators to enhance their capabilities to cope with complexity, demanding skills, and higher cognitive levels, performance, and errors. To overcome this scenario, a virtual instructor framework is proposed to instruct operators and support procedural quality, enabled by the use of You Only Look Once (YOLO) models and by equipping the operators with Magic Leap 2 as a Head-Mounted Display (HMD). The framework relies on key modules, such as Instructor, Management, Core, Object Detection, 3D Modeling, and Storage. A use case in the automotive industry helped validate the Proof-of-concept (PoC) of the proposed framework. This framework can contribute to guiding the development of new tools supporting assembly operations in the industry.

This study aims to critically examine Western educational philosophy theories and highlight the urgency of Islamization of educational knowledge as a response to the value crisis caused by secular approaches in modern education systems. Western educational philosophy, dominated by rationalism, empiricism, pragmatism, and existentialism, tends to reduce the human being to a rational or material entity, neglecting the spiritual dimension and the ultimate purpose of life. In the context of the Muslim world, the uncritical adoption of Western educational theories can lead to value disorientation, secularization of educational goals, and the weakening of students’ Islamic identity. Therefore, the Islamization of educational knowledge is an urgent necessity to establish an educational paradigm rooted in divine revelation, integrating both rational ('aqlī) and scriptural (naqlī) knowledge, and oriented toward the development of the ideal human being (insān kāmil). This research employs a qualitative approach using library research methods, analyzing the thoughts of key Western educational thinkers and the concept of Islamization as articulated by Muslim scholars. The findings indicate that Islamization is not merely a process of purifying the curriculum from secular elements, but an epistemological project aimed at restoring education to its essential nature—as a means of tazkiyah (soul purification) and the cultivation of adab (proper conduct). The practical implications of educational Islamization call for curriculum reform, teacher training, and evaluation systems grounded in Islamic values in a holistic and sustainable manner.

The subject of the article is the methodology for developing a hybrid three-tier software architecture for adaptive VR driving training systems with real-time biometric feedback, which ensures the distribution of functional components between the client, peripheral and microservice levels. The goal is to develop an architecture that provides a balance between minimal latency of biometric data processing for a comfortable VR experience, reduced costs, and the possibility of gradual scaling. Tasks to be solved: performing a comparative analysis of existing architectural approaches according to the criteria of latency, cost and scalability; developing a hybrid software architecture model; experimental verification of the proposed architecture; determining the scope of application of the hybrid architecture. The methods used include architectural design methods, synthesis and decomposition methods. The following results were obtained. A hybrid architecture was developed with a client layer for rendering and collecting biometric data, a peripheral layer for classifying user state and adapting training scenarios, and a microservice layer for asynchronous traffic simulation and data analytics with possible scalability. Experimental verification demonstrated a reduction in the latency of biometric data processing. The scope of application of the developed hybrid model was determined. Conclusions. The results of the study confirmed the relevance of a hybrid approach to architectural design with the placement of computationally intensive components on a peripheral server in the local network of the educational institution instead of a centralized cloud server to eliminate global network delays, and also provided an opportunity to justify the choice of software architecture taking into account the number of users, budget constraints, and latency requirements. The scientific novelty of the results obtained lies in the creation of a hybrid architecture model that involves the distribution of functional components of the system by levels based on constraints on processing speed, implementation cost, and the degree of independence of auxiliary calculations, which makes it possible to increase the efficiency of resource use in training using virtual reality, as well as to increase the efficiency of training by adapting to the current state of the learner

Geographic distribution of healthcare workers is an issue most countries are challenged with. Regionalisation of surgical training in Ireland has emerged as a hot topic over the past number of years in an effort to address the balance between professional progression, adequacy of surgical training and personal responsibility/circumstance. This issue has been reported on within the NHS, but the way in which it may apply to Irish surgical specialties is now being considered. Our aim was to examine the sentiments of Irish Trauma and Orthopaedic trainees towards a number of issues as they pertain to regionalisation of training. We distributed a questionnaire amongst the HST Trauma and Orthopaedic group of trainees and assimilated the results. We found that 69.1% of trainees felt the current structure of the Irish Trauma and Orthopaedic training system was fit for purpose. Ninety percent of respondents said the current structure of the training scheme puts strain on their personal life and work-life balance. When asked if trainees felt that regionalisation of the training programme would benefit their training, 43.9% replied no, 31% yes and 26.2% were unsure. When asked if, overall, the trainee would be in favour of a regionalised training structure for Trauma and Orthopaedics, 43% said 'No', 40% said 'Yes' and 17% were unsure. An equilibrium of professional surgical progression, optimal patient care and work-life balance is a goal held in the highest regard amongst key stakeholders of Irish surgical training. The solution amongst the various surgical subspecialties may not be a one-size-fits-all approach in pursuit of the optimisation of this balance. Further engagement of key stakeholders in how surgical training will evolve over time is crucial in order to achieve this.

This community service program aims to enhance the capacity and self-reliance of the Seruni Women Farmer Group (KWT Seruni) in supporting food security through training on urban farming and hydroponic cultivation, implemented using a Participatory Action Research (PAR) approach. The program engaged lecturers, students, and group members in stages of socialization, training, technology implementation, mentoring, and sustainability planning. Evaluation results indicated a 12% improvement in participants’ understanding based on pre-test and post-test scores, demonstrating the program’s effectiveness in strengthening technical competence. Technological implementation, including the construction of a seed house and the use of pH and TDS meters, resulted in 1,500 high-quality seedlings and a hydroponic pakcoy harvest of 18.4 kg. Participants successfully applied practical skills independently, particularly in nutrient management and the cultivation of economically valuable crops. The program also fostered an internal training system for new members and generated socio-economic benefits, such as increased household income and strengthened women’s roles in agriculture. Overall, this activity aligns with SDGs 1, 2, 5, and 12.

Technical and Vocational Education and Training (TVET) systems face both significant opportunities and complex challenges amid rapid global digital transformation. This systematic literature review (SLR) sought to identify and examine the key challenges associated with digitalisation of TVET. Central to the investigation was the persistent gap between the increasing demand for digital competencies and the capacity of TVET institutions to effectively adopt and implement digital tools and pedagogical practices. To address this issue, a search was conducted comprehensively across three academic databases, Scopus, Web of Sciences, and ERIC targeting peer-reviewed literature published from year 2022 to 2024. Searches employed combinations of keywords such as “TVET”, “digitalisation”, “vocational”, “technical” and “skills”. Inclusion criteria comprise English-language, peer-reviewed journal articles focusing on TVET and digitalisation, while non-articles and unrelated studies were excluded. From initial pool of 599 records, the final of 37 primary studies was selected for in-depth analysis. The findings were organised into three themes which were (1) digital transformation and curriculum development, (2) digital competence and skills development, and (3) digital inequality and inclusivity. The analysis revealed that while digital transformation offers substantial benefits, it also worsens existing inequalities and poses significant challenges in curriculum design and skill acquisition. Digital transformation in TVET offers substantial benefits such as flexible learning access and industry- relevant training, but also presents significant challenges in curriculum alignment, educator digital competence, and equitable resource distribution. These insights are crucial for policymakers, educators, and stakeholders aiming to optimise the digitalisation process within TVET systems.

The rapid integration of artificial intelligence (AI) in Security Operations Centers (SOCs) has created both opportunities and challenges for cybersecurity teams. This paper explores the effects of the levels of AI automation on trust of the analysts, decision-making quality, and skill development. The study delves into three main areas: alert trust, automation bias, and skill adaptation. Using an experimental SOC simulator, participants had to use AI detection tools that generated alerts with varied prediction accuracy to examine the effects on trust and performance. Findings suggest that moderate automation promotes healthy trust and improved decision-making accuracy, while high automation could induce excessive reliance and less alertness. Feedback also aids independent detection skill and confidence in analysts. These studies illustrate the imperative to design trust-sensitive adaptive training systems that can allow for better analyst-AI collaboration in cybersecurity.

BackgroundThe challenge of increasing demands on healthcare and a less available workforce requires new approaches to retain and develop healthcare professionals. One way of addressing this challenge is by instituting competency-based continuing professional development based on self-directed learning (SDL) principles. We investigated the feasibility of a mobile training system in a clinical and peer-to-peer, SDL setting.MethodsThe study used mixed methods with surveys, observations, and interviews to gain comprehensive insights into how healthcare professionals (nurse, assistant nurse) and managers experienced the investigated educational tool.ResultsHealthcare professionals’ experiences of SDL were illustrated in four main themes: (1) leadership required for learning, (2) conditions for learning, (3) effects of continuing professional development, and (4) suggestions for improving training methods. In surveys, healthcare professionals self-assessed their confidence in executing care tasks before and after undergoing SDL for those tasks. The results indicated a significant increase in self-efficacy post-SDL training. Engaging in care tasks through SDL, which includes checklists aligned with evidence-based practices, enhances healthcare professionals’ awareness of their own competence. Additionally, it provides managers with the means to ensure that employees meet core competence requirements. The role of a clinical skills centre to support managers and staff in their learning efforts was seen as important for sustained learning.ConclusionA mobile training system, implemented within a clinical and peer-to-peer SDL framework, facilitates and complements competency-based continuing professional development and reduces the perceived length of time healthcare professionals spend away from direct patient care. Access to clinical educators for guidance during implementation, along with support from the clinical skills centre during the planning and follow-up stages, proved essential for facilitating accessible learning. Managers play a crucial role in prioritizing continuous learning for their employees and establishing a culture of ongoing education among managers and healthcare professionals.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12909-025-08127-1.

The article examines the organizational and methodological foundations of modern physical training of servicemen of the Armed Forces of Ukraine under the conditions of armed aggression. The main problems of the current training system are analyzed, in particular the shortcomings in regulatory support, personnel resources, infrastructure, and individualization of physical loads. Special attention is paid to the necessity of implementing innovative approaches in the training process, such as functional military fitness, psychophysical practices, digital monitoring systems, and combat simulation-based exercises. The importance of integrating physical training into combat routines is emphasized, ensuring its relevance and continuity even under active military service. The article outlines priority directions for improvement, including personalized training programs based on psychophysiological characteristics of military personnel, integration of physical training with tactical and combat activities, the development of qualified instructor staff, and the modernization of training infrastructure. A conceptual model of physical training is proposed, which ensures servicemen’s adaptation to high-stress combat conditions, improvement of functional resilience, injury prevention, and operational efficiency. The implementation of this model is expected to increase the general level of physical readiness and psychological stability of the Ukrainian Armed Forces personnel. Thus, the modernization of the physical training system based on evidence-based methods and adaptive strategies is a key component of strengthening national defense capability. The development and scientific substantiation of such systems should be a priority for military pedagogy and physical education science in wartime and post-war reconstruction.