This paper explores the distribution of educational resources from the perspective of public service equalization in China, with a particular focus on government responsibility and fiscal input. Initially, the paper reviews the theoretical foundations and empirical studies concerning the distribution of educational resources, analyzing the role of government in educational equity and the impact of fiscal expenditure. By employing quantitative analysis methods, this study utilizes data on provincial education expenditures over several years to examine the relationship between government fiscal input and the equalization of educational resources. Empirical results indicate that increasing educational fiscal input and optimizing the allocation mechanism significantly enhance the level of equalization in educational resources. Furthermore, through case analyses of several local governments, effective policy recommendations are proposed to promote the fair distribution and optimization of educational resources. Lastly, the paper discusses potential obstacles in policy implementation and suggests corresponding strategies.

There are a number of issues that can influence elderly life satisfaction, which can mirror their welfare. This study aims to explore the differences in elderly parents’ life satisfaction across socioeconomic characteristics and investigates how the traits of both children and parents associate with elderly parents’ life satisfaction in Thailand. This study uses individual data obtained from Thailand’s National Statistical Organization covering 2008–2015, 2018 and 2020, with a total sample size of 28,494. To investigate the association between children’s and parents’ characteristics, particularly formal education and parental life satisfaction, this study uses ordered logistic regression for the analysis. Our results show that male parents are more likely to have higher life satisfaction than their female counterparts. Parents who are employed, holding a bachelor’s degree, and living with female children are more satisfied with their life. Statistically, children’s formal education demonstrates its importance for their elderly parents’ life satisfaction. This documents the vital role of schooling in improving parental life satisfaction. Moreover, facing the challenge of entering an aging society, government agencies must take a proactive stance on creating jobs suitable for the elderly or retirees to maintain their sense of independence. The evidence of intergenerational mobility reaffirms the importance of children’s education along with their caring ability, which should be strengthened.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.

This research investigates the impact of modern technological methods of knowledge management (KM) and total quality management (TQM) on the performance of faculty members in educational colleges in Jordan. Drawing on a survey conducted with 306 faculty members, the study examines the influence of technology on teaching methodologies and academic quality within the Jordanian higher education context. The study utilizes the Technology Acceptance Model (TAM) to back up the modern technological methods of knowledge management (KM) and total quality management (TQM) models. The findings reveal a generally positive perception among respondents regarding the beneficial effects of modern technological tools on teaching effectiveness, collaboration, and innovation. Additionally, technology-enhanced TQM practices were found to contribute to improvements in curriculum design, student engagement, and administrative processes. Regression and correlation analyses support significant relationships between technology-enabled KM and TQM practices and faculty performance, highlighting the transformative role of technology in shaping the future of higher education in Jordan. Recommendations are provided for educational institutions to enhance the integration of technology and foster a culture of innovation and continuous improvement among faculty members.

The growing interconnectedness of the world has led to a rise in cybersecurity risks. Although it is increasingly conventional to use technology to assist business transactions, exposure to these risks must be minimised to allow business owners to do transactions in a secure manner. While a wide range of studies have been undertaken regarding the effects of cyberattacks on several industries and sectors, However, very few studies have focused on the effects of cyberattacks on the educational sector, specifically higher educational institutions (HEIs) in West Africa. Consequently, this study developed a survey and distributed it to HEIs particularly universities in West Africa to examine the data architectures they employed, the cyberattacks they encountered during the COVID-19 pandemic period, and the role of data analysis in decision-making, as well as the countermeasures employed in identifying and preventing cyberattacks. A total of one thousand, one hundred and sixty-four (1164) responses were received from ninety-three (93) HEIs and analysed. According to the study’s findings, data-informed architecture was adopted by 71.8% of HEIs, data-driven architecture by 24.1%, and data-centric architecture by 4.1%, all of which were vulnerable to cyberattacks. In addition, there are further concerns around data analysis techniques, staff training gaps, and countermeasures for cyberattacks. The study’s conclusion includes suggestions for future research topics and recommendations for repelling cyberattacks in HEIs.