This research article explores the relationship between psychological well-being and satisfaction with life among young, athletically talented students educated through individualised programs. The primary objective is to assess whether a safe educational environment, emphasising psychological safety and individual support, positively impacts the general satisfaction and academic performance of these students. Using Ryff and Keyes’ Psychological Well-Being Scale and Diener’s Satisfaction with Life Scale, data were collected from 188 participants—Secondary and university students engaged in rigorous athletic training while completing their studies in the Czech Republic. Key findings reveal a strong correlation between self-acceptance, autonomy, coping with the environment, and enhanced satisfaction with life, indicating that well-being in young athletes is significantly influenced by psychological resilience, emotional support, and control over one’s educational journey. Research highlights that individually tailored learning environments, which provide flexibility for training and access to mental health support, contribute to a balanced development between academic and athletic goals. Additionally, the results suggest that a positive correlation within the educational environment, both with peers and instructors, further strengthens the satisfaction with life and reduces the risk of burnout. Implications underscore the need for educational institutions to adopt holistic approaches that support psychological well-being and accommodate the unique needs of athletically talented students. Recommendations include structured mentorship, flexibility in academic scheduling, and access to professional counselling. Future research should investigate the long-term impacts of such environments on academic and athletic success, considering factors such as social inclusion and the effects of digital education.
The purpose of this study is to explore factors influencing the blockchain adoption in agricultural supply chains, to make a particular focus on how security and privacy considerations, policy support, and management support impact the blockchain adoption intention. it further investigates perceived usefulness as a mediating variable that potentially amplifies the effects of these factors on blockchain adoption intention, and sets perceived cost as a moderating variable to test its influence on the strength and direction of the relationship between perceived usefulness and adoption intention. through embedding the cost-benefit theory into the integrated tam-toe framework and utilizing the partial least squares structural equation modeling (PLS-SEM) method, this study identifies the pivotal factors that drive or impede blockchain adoption in the agricultural supply chains, which fills the gap of the relatively insufficient research on the blockchain adoption in agriculture field. the results further provide empirical evidence and strategic insights that can guide practical implementations, to equip stakeholders or practitioners with the necessary knowledge to navigate the complexities of integrating cutting-edge technologies into traditional agricultural operations, thereby promoting more efficient, transparent, and resilient agricultural supply chains.
This research investigates the relationship between the variables of public service reform (PSR) and bureaucratic revitalization and the relationship between digital leadership (DL) and bureaucratic revitalization. The research method used in this research is quantitative survey research which aims to determine the relationship between two or more variables. The research method for this research is quantitative associative, the population of this study is senior immigration officers. The data analysis method uses structural equation modeling (SEM) partial least squares (PLS), the respondents for this study were 634 senior immigration office employees who were determined using the simple random sampling method—non probability sampling, the questionnaire was designed to contain statement items using a 7 point Likert scale. A closed questionnaire is a list of questions or statements that are equipped with multiple answer choices expressed in scale form. The Likert scale used in this research is (1) strongly disagree, (2) disagree, (3) quite disagree, (4) neutral, (5) quite agree, (6) agree, (7) strongly agree. Data processing in this research used SmartPLS software. The independent variables of this research are digital leadership and public service reform and the dependent variable is bureaucratic revitalization. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research show that public service reform has a positive and significant relationship to bureaucratic revitalization and digital leadership has a positive and significant relationship to bureaucratic revitalization. This research implies that leaders focus on engaging, using, and handling the uncertainty of emerging technologies, digital tools, and data, leaders to support bureaucratic revitalization, the immigration department must implement digital leadership, immigration leaders should encourage the use of digital platforms in their organizations, support and facilitate digital transformation. The immigration department should increase the revitalization of the bureaucracy, the immigration department should carry out public service reforms. Public services are to be good if they fulfill several principles of public interest, legal certainty, equal rights, balance of rights and obligations, professionalism, participativeness, equality of treatment/non-discrimination, openness, accountability, facilities and special treatment for vulnerable groups, timeliness, speed, convenience and affordability.
This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.
This study investigated the changing land use patterns and their impacts on ecosystem in the Teesta River Basin of northwestern Bangladesh. Although anthropocentric land use patterns, including agricultural land use, settlements, built areas, and waterbody loss, have been increasing in the Nilphamari district, by negatively affecting local ecosystems, they have not been identified by prior research. Limitations of contemporary literature motivated me to work on this crucial ground in the Teesta River Basin in Northwestern Bangladesh. This study applied a mixed research approach to identify the study objectives. Firstly, the land use and land cover (LULC) changes which occurred between 2000 and 2020 were detected using satellite imagery and supervised classification method. In addition to the detection of LULC changes, the study explored the people’s perceptions and experiences about the ecosystem changes resulted from the LULC changes over the last 20 years, conducting stakeholders’ consultations and household surveys utilizing a semi-structured questionnaire. The findings indicated that waterbodies in Nilphamari district have significantly decreased from 378 km2 in 2000 to 181 km2 in 2020. In the same way, the vegetation coverage has reduced 187 km2 between the years 2000 and 2020. On the contrary, agricultural lands (croplands) have increased from 595 km2 to 905 km2 and settlements have increased from 81 km2 to 206 km2 between the years 2000 and 2020. From the chi-square test, it was found a significant association between ecosystem change and biodiversity loss. It was further identified that waterbody decreases have significant impacts on aquatic ecosystems. The results of this study also indicated that due to the introduction of foreign tree species, local and native species have been significantly decreasing over the time. This study emphasizes the non-anthropocentric and inclusive land use policy implications for protecting life on land and preserving the aquatic ecosystem in Bangladesh.
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