Technical Pedagogical Content Knowledge (TPACK) encompasses teachers’ understanding of the intricate interplay among technology, pedagogy, and subject matter expertise, serving as the essential knowledge base for integrating technology into subject-specific instruction. Over the decade, advancements in information technology have led to the consistent application of the TPACK framework within studies on instructional technology and technology-enhanced learning, significantly advancing the evolution of contemporary teacher education in technology integration. In this paper, we utilize the Teaching and Learning Knowledge of Subjects Based on Integrated Technology (TPACK) framework to administer a questionnaire survey to teacher trainees at Chinese colleges and universities. This survey aims to evaluate the current status of their integrated technology-based subject teaching and learning knowledge. Based on the research findings, we propose strategies aimed at enhancing the educational technology integration knowledge of students pursuing integrated technology courses in colleges and universities. Furthermore, we integrate the smart classroom setting to develop a comprehensive TPACK-integrated model teaching framework. Our final objective is to offer valuable references for the progress of modern teaching skills among education students in higher education institutions.

Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.

The learning of English courses is not only a process for students to master language knowledge and skills, but also a process for improving students' comprehensive humanistic quality. The integration of moral education in English teaching can not only cultivate students' good study habits, improve the efficiency of English learning, but also help to cultivate students' excellent moral quality. Through the research on the organic integration strategy of primary school English teaching and moral education, this paper aims to provide an effective method for the effective integration of primary school English teaching and moral education, so as to promote the improvement of the level of primary school moral education and achieve the goal of building morality and cultivating people.

In the human and economic development context, this study examines the relationship between human capital, life expectancy, labor force participation rate, and education level in Indonesia, Malaysia, and Thailand. The World Bank’s 2001–2021 data are examined using a panel vector autoregressive model. The findings demonstrate the substantial influence of health expenditure from the prior period on present health expenditure. Though not significantly different, life expectancy and education levels from earlier periods also impact present health spending. A slight positive correlation exists between prior labor force involvement and present healthcare costs. An increase in current health expenditure supports an increase in life expectancy. Health expenditure in the previous period had a significant positive effect on education, although insignificant. Life expectancy in the previous period harms current education but is also insignificant. Education in the previous period significantly positively affects current education, indicating a sustained impact of education investment. Labor force participation in the previous period also positively affected education, although not significantly. The prior period’s health spending, life expectancy, and educational attainment impact the current labor force participation rate. The length of life has a significant favorable impact on entering the labor sector. Currently being in the job field has a good correlation with prior education as well. These findings support that higher education levels lead to higher labor force participation rates. Life expectancy, health care costs, education level, and prior work experience all influence current life expectancy. While prior life expectancy significantly influences current life expectancy, health expenditures have a negligible negative impact. Prior education positively impacts life expectancy but negatively impacts prior labor force engagement. These results reject the hypothesis that increasing life expectancy causes current health expenditure to increase.

This study examines the relationship between macroeconomic determinants and education levels in eight selected African oil-exporting countries (AOECs) over the period 2000–2022. Drawing on human capital theory, the paper scrutinizes the impact of factors such as income inequality, health outcome, economic growth, human development, unemployment, education expenditure, institutional quality, and energy consumption on education levels. Employing robust estimation techniques such as fixed effects (FE), random effects (RE), pooled mean group (PMG) and cross-section autoregressive distributed lag model (CS-ARDL), the study unveils vital static and dynamic interactions among these determinants and education levels. Findings reveal notable positive and significant connections between education levels and some of the variables—human capital development, institutional quality, government expenditure on education, and energy consumption, while income inequality demonstrates a consistent negative relationship. Unexpectedly, health outcomes exhibit a negative impact on education levels, warranting further investigation. Furthermore, the analysis deepens understanding of long-run and short-run relationships, highlighting, for example, the contradictory impact of gross domestic product (GDP) and unemployment on education levels in AOECs. Finally, the study recommends targeted human development programs, enhanced public investment in education, institutional reforms for good governance, and sustainable energy infrastructure development.