In order to create the possibility of economic breakthrough development, remove economic institutional bottlenecks, release resources, and develop the economy quickly and sustainably in Vietnam in the coming time, it is impossible not to mention solutions to improve the quality, create breakthroughs in training and fostering talents. This is one of the important solutions in the context that the Party and State require the application and development of science and technology more and more extensively in all fields and all sectors in Vietnam. The article focuses on researching the the political basis, legal basis, and practical basis for training, fostering, attracting and employing talents in Vietnam. Meanwhile, statistics on undergraduate and postgraduate training in the period of 2016–2022, the training level of the workforce and the Global Talent Competitiveness Index show that Vietnam has not achieved many positive changes in training, fostering, attracting and employing talents as expected. The article is approached from many different aspects, including the perspective of leaders and managers at the head of state agencies, the perspective of businesses and the perspective of the university teaching staff and scientific research workers themselves. On that basis, the article points out the key contents that need addressing so as to build solutions to improve quality, create breakthroughs in training, fostering, attracting and employing talents in Vietnam in the context of international integration and science and technology development. The main contributions of the article focus on the identification of the concept of “talent”, the criteria for determining “talent” and the renewal of awareness of policies and laws on training, fostering, attracting, employing, introducing and recommending talents.
The purpose of this study is to analyze issues related to the use of green technology and to provide a theoretical basis for how the application of green technology in agriculture can reduce inequality. Additionally, the study aims to explore policy alternatives based on the analysis of inequality reduction issues through farmer surveys. For this purpose, this study used survey data to analyze farmers’ perceptions, acceptance status, willingness to accept green technology, and perceptions of inequality. The quantitative analysis was performed to analyze the relationship between the acceptance of green technology and perceptions of inequality. The results confirmed that access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions are major factors. In particular, the higher the satisfaction with policies regarding the introduction of green technology, the lower the perception of inequality. Specifically, the acceptance of green technology showed a significant positive correlation with access to information, perception of climate change, and awareness of the need to reduce greenhouse gas emissions, while perceptions of inequality showed a significant negative correlation with policy satisfaction. In conclusion, green technology in agriculture is vital for reducing climate change damage and inequality. However, targeted policy support for small-scale farmers is essential for successful adoption. This study provides policy implications related to the application of green technology in the agricultural sector, which can promote sustainable agricultural development.
The root of the problem in this research is the fact that scientific writing with a national reputation is still low and the publication of scientific writing with a national reputation is also low, thus affecting the quality of lecturers at the University. To overcome this problem, this research developed a training management model that can improve the scientific writing skills of lecturers and familiarize lecturers to actively conduct nationally reputable scientific writing. The training management model in question is called the “National Reputable Scientific Writing Training Management” model. This type of research is development research or R&D to produce a valid, practical, and effective model, as well as all devices and research instruments related to the application of the model at the University. The results showed that: (1) the National Reputable Scientific Writing Training Management model is suitable for improving the scientific writing ability of lecturers; (2) the output of the National Reputable Scientific Writing Training Management model in the model group is significantly higher than the initial group (pre-model); (3) The average value of IP/IO from experts is 4.4 with a high category, from observers at stage I test is 4.0 with a high category, at stage II test is 4.7 with a high category and stage III test is 4.77 with a high category, so it is concluded that the National Reputable Scientific Writing Training Management model meets the criteria of effectiveness, practicality and implementation; (4) The response of university managers and respondents to the implementation of the model is quite satisfactory, both regarding the concept of the model, the application in technical implementation and their perception of the National Reputable Scientific Writing Training Management model; and (5) the National Reputable Scientific Writing Training Management model can be developed as an alternative implementation in training management at the university.
Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.
This study investigates the role of property quality in shaping booking intentions within the dynamic landscape of the hospitality sector. A comprehensive approach, integrating qualitative and quantitative methodologies, is employed, utilising Airdna’s dataset spanning from July 2016 to June 2020. Multiple regression models, including interaction terms, are applied to scrutinise the moderating role of property quality. The study unveils unexpected findings, particularly a counterintuitive negative correlation between property quality and booking intentions in Model 7, challenging conventional assumptions. Theoretical implications call for a deeper exploration of contextual nuances and psychological intricacies influencing guest preferences, urging a re-evaluation of established models within hospitality management. On a practical note, the study emphasises the significance of continuous quality improvement and dynamic strategies aligned with evolving consumer expectations. The unexpected correlation prompts a shift towards more context-specific approaches in understanding and managing guest behavior, offering valuable insights for both academia and the ever-evolving landscape of the hospitality industry.
Purpose: This study explores the impact of quality of life (QoL) on the happiness of female healthcare professionals, focusing on the moderating roles of family dynamics and education. Method: A descriptive and exploratory design was used with data from 503 female healthcare professionals. Various quantitative analyses, including regression and correlation, were conducted using SPSS and AMOS. Findings: The study found a positive relationship between QoL and happiness. Family dynamics and education significantly moderated this relationship, highlighting the influence of these factors on happiness levels. Implications: The research offers insights into the well-being of female healthcare professionals and calls for policies that support QoL through flexible work arrangements and wellness programs, considering diverse family structures and educational backgrounds. Originality: This study provides a focused analysis of the role of family and education in shaping the relationship between QoL and happiness for female healthcare professionals.
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