Objective/Aim: In the context of a constantly changing legislative environment and the necessity for professionals to develop their skills, the research focuses on identifying effective methods and tools that facilitate efficient learning and professional development in the field of labour law. This study aimed to propose a pedagogical technology for the preparation and training of specialists in the field of labour law and to assess the effectiveness of the training based on the specified technology. Method: The study involved 124 participants, with 63 in the experimental group and 61 in the control group. Statistical analysis was performed using Microsoft Excel. The student’s t-test indicated significant improvements in the experimental group’s training effectiveness, confirming the proposed pedagogical technology’s efficacy. Results: Consequently, implementing training and education technology for specialists in the labour law field was proposed to enhance the indicators. The criteria for the preparation of specialists in the field of labour law were delineated, including knowledge of labour legislation, consulting and support skills, analytical skills, communication skills, and continuous learning. According to the criteria above, levels of preparation for specialists in the field of labour law were established, namely high, medium, and essential. The proposed training and education technology for specialists in the field of labour encompasses the following tools: The utilisation of online platforms and educational resources, virtual classes and simulations, the incorporation of multimedia materials, the integration of adaptive learning technologies, the implementation of project- and problem-oriented teaching methodologies, the incorporation of interactive methodologies, the incorporation of cloud technologies and mobile applications, and the provision of assessment and feedback. Conclusion: The proposed pedagogical technology effectively enhances the training and education of labour law specialists. The experimental group’s significant improvement in learning outcomes confirms the technology’s efficacy. Implication: The findings of this research hold significant social implications. Improved training and education of labour law specialists leads to a more competent and effective legal workforce. This, in turn, ensures better protection of workers’ rights and fairer employer-employee relations, contributing to overall social stability.
This article scrutinizes the multifaceted challenges inherent in intergovernmental coordination across various sectors, with a particular emphasis on sustainable development and entrepreneurial activity within the Republic of Moldova. It argues that despite the existence of intergovernmental cooperation, it often manifests as deficient, contradictory, incomplete, and inefficient. Through a meticulous analysis, this study delineates the roles of pertinent authorities and institutions in fostering the sustainable development of entrepreneurial activities, identifying critical inter-institutional coordination issues and challenges. The discourse extends to examining institutional processes and the extent to which policies, laws, and international standards are implemented to nurture and sustain business activities. Moreover, the paper explores various strategies to cultivate responsible, transparent, and effective dialogue between institutions, thereby promoting innovative practices, expanding cooperation, and fostering partnerships with national and civil society organizations, including international bodies.
This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.
In the context of globalization and integration of world markets, import operations occupy an important place in the activities of enterprises, forming a significant part of their economic processes. Effective management of these operations requires accurate and timely accounting and high-quality auditing, which becomes especially relevant in modern conditions. The study of methodological features of accounting and auditing of import operations is a relevant and timely area that helps improve the quality of financial reporting and management decisions. The purpose of the study is to analyze the problems and prospects of methodological features of accounting and audit of import operations, as well as to develop recommendations for their improvement. The study examined the main methodological approaches, existing problems and challenges, and proposed solutions aimed at increasing the efficiency and reliability of accounting and auditing in a global economy. The improvement of methodological approaches to the accounting and auditing of import operations will improve the accuracy and reliability of financial reporting, reduce the risks of non-compliance with regulatory requirements, as well as improve management decision-making and the overall financial stability of companies. The development and implementation of effective accounting and auditing methods that comply with international standards and best practices will minimize financial risks and increase the competitiveness of enterprises in the global market. A study of the problems and prospects of methodological features of accounting and auditing of import operations has revealed a number of key issues that require attention and solutions. The main challenges are the complexity and diversity of regulatory requirements, currency fluctuations, the diversity of imported goods and services, difficulties in assessing and recognizing imported goods, and the lack of qualified specialists.
Intelligent toy design and development talents need to master certain electronic intelligent control, arts and crafts design, product modeling design and other skills. There is a shortage of intelligent toy designers in our country, and toy enterprises are in urgent need of professional and technical personnel engaged in toy product modeling and functional design. Therefore, it is urgent to cultivate intelligent toy design and development talents. This paper explores the necessity of cross-professional training of intelligent toy design and development talents, relies on teachers' scientific research and enterprise projects, etc., takes graduation projects as a breakthrough, pushes back the talent training curriculum system, and proposes an cross-professional collaborative training model. Through cross-professional combination training intelligent toy design talents, so that they have the design thinking of toy designers and a certain degree of electronic engineer design thinking, can better adapt to the rapid development of modern toy design industry, enterprises changing new requirements.
The concept of output-oriented education has been introduced for many years in our country and has been widely used in the process of personnel training in Chinese universities. This paper discusses how the concept of Outcome Based Education can be fully integrated into the process of developing talents in an interdisciplinary and collaborative manner in the context of new engineering. We have made useful explorations in various aspects from curriculum system integration, online teaching resources construction, studio-style course organization mode, rich teaching project library to school-enterprise cooperation project practice, etc., which have improved students' learning effect.
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