Lifelong learning (LLL) is progressively recognized as a crucial component of personal and professional development, particularly for adult students. As a heavily populated developing country, China requires profound national education reform to support its economic development and maintain its competitive advantage on the global economic stage. The governmental policy endorses the execution of diverse forms of lifelong learning programs to bolster the national education reform. However, implementing such programs can be challenging for all the stakeholders of the programs, especially for adult students. The weaker foundational knowledge and insufficient online learning abilities of adult students particularly highlight the academic challenges they face. This study explores the academic challenges faced by adult learners in a Chinese vocational college’s LLL program. Focusing on ex-soldiers, unemployed individuals, migrant workers, and new professional farmers (aged 22–44), data were collected from 16 adult students via purposive sampling. Semi-structured interviews and document analysis revealed recurring thematic academic challenges. Additionally, the study found that adult student attributes (highest education level, age) significantly influenced the unique academic challenges they encountered. This research provides practical solutions to improve LLL programs and promote successful lifelong learning experiences for adult students. 

Artificial intelligence (AI) has rapidly evolved, transforming industries and addressing societal challenges across sectors such as healthcare and education. This study provides a state-of-the-art overview of AI research up to 2023 through a bibliometric analysis of the 50 most influential papers, identified using Scopus citation metrics. The selected works, averaging 74 citations each, encompass original research, reviews, and editorials, demonstrating a diversity of impactful contributions. Over 300 contributing authors and significant international collaboration highlight AI’s global and multidisciplinary nature. Our analysis reveals that research is concentrated in core journals, as described by Bradford’s Law, with leading contributions from institutions in the United States, China, Canada, the United Kingdom, and Australia. Trends in authorship underscore the growing role of generative AI systems in advancing knowledge dissemination. The findings illustrate AI’s transformative potential in practical applications, such as enabling early disease detection and precision medicine in healthcare and fostering adaptive learning systems and accessibility in education. By examining the dynamics of collaboration, geographic productivity, and institutional influence, this study sheds light on the innovation drivers shaping the AI field. The results emphasize the need for responsible AI development to maximize societal benefits and mitigate risks. This research provides an evidence-based understanding of AI’s progress and sets the stage for future advancements. It aims to inform stakeholders and contribute to the ongoing scientific discourse, offering insights into AI’s impact at a time of unprecedented global interest and investment.

The goal of this research is to determine whether hospital financial performance is impacted by particular management accounting techniques, such as departmental revenue budgeting, specific costing, and departmental costing. We analyzed several sets of performance indicators for 146 hospitals whose management accounting adoption status is available. An outlier test was used to determine which data were outliers at the 0.1% significance level, and the results were then eliminated in order to see if any extremely outlier values (hospitals) were present for each indicator. To determine whether there were any noteworthy variations in the average values of the several performance measures, we employed a t-test (two-tailed probability). The results suggest that departmental revenue budgeting and departmental and specific costing improve hospital financial performance.

Background and introduction: The East and Southeast Asian newly industrialized economies have shown spectacular economic development by their export-oriented development policies during recent decades, which resulted in not only economic wealth but enabled them to be technology exporters and investors. Their products, their flagship brands today are well-known and recognized throughout the world. It is not surprising that the Hungarian government—by its Hungarian Eastern Opening strategy—intended to focus on these economies, even though that with most of them there were intensive and broad co-operation in the fields of business, investment, culture, education and tourism. The new strategy gave a focus on increasing the diplomatic and trade relationship with the wider region, new embassies and trade representation offices were opened or re-opened in several locations with the view of intensifying the business and the people-to-people contacts. Even though the pandemic of Covid 19 and the energy crisis caused disruption in international trade, it can be said the trade and investment relations with these economies have still been growing, especially on the import side. The prospects of the growth of Hungarian exports to these destinations are modest which is hindered by the huge geographic distance, the peculiar consumer preferences, the merely different market conditions and the sharp competition. Objective: The aim of this paper to illustrate by statistical figures the state of the trade and investment relations between Hungary and the Republic of Korea, Taiwan, Singapore and Thailand. Methodology: Bibliographic and data analysis, focusing on the relevant international and Hungarian literature and databases, especially the trade and investment statistics of the Hungarian Central Statistical Office (HCSO/KSH).

In order to explore how hygiene factors and motivational factors indirectly affect job satisfaction through teacher self-efficacy. Based on the two factor theory and Teacher Job Satisfaction Survey (TJS), this study analyzes how hygiene factors and motivational factors indirectly affect job satisfaction through teacher self-efficacy. The study collects valid questionnaires from 120 teachers and conducts mediation analysis using structural equation modeling. From the results, teacher self-efficacy had obvious mediating effects between hygiene factors and job satisfaction (β > 0.6, P < 0.001), as well as between motivational factors and job satisfaction (β > 0.6, P < 0.001). This discovery not only provides new perspectives and strategies for improving teacher job satisfaction, but also emphasizes the importance of enhancing teacher self-efficacy in improving job satisfaction. In addition, the study provides strong empirical evidence for education management departments and school leaders to formulate more effective teacher development policies and management measures, which has positive theoretical and practical significance for improving education quality and promoting education reform.