The educational-instructional process, specific to the preschool age of 4–5 years, is oriented towards the formation of children’s motor and cognitive skills. As part of physical activities in preschool education, various exercises are performed to strengthen motor and verbal responses. Light physical exercises and movement games are used to improve motor skills and verbal ability. The present research was carried out on a group of 20 preschoolers, using an experimental methodology, with the help of One-Group Pre-test and Post Test Design. Based on the statistical analysis of the data obtained from the motor skills evaluation tests and the cognitive skills evaluation tests, the value p < 0.001 indicates a positive statistical significance between the pre-test and the post-test. The values of Cohen’s D coefficient by which the effect size was evaluated indicate its great influence (D = 0.893). In conclusion, the differences between the pre-test and post-test values show significant progress, which underlines the effectiveness of the intervention aimed at improving motor and cognitive skills in preschoolers.

The issue of policy changes to support teacher professional development is an important factor shaping the career trajectory, efficacy, and ultimately the success of Junior Reserve Officer Training Corps (JROTC) instructors and the performance of the secondary students they serve and whose lives they affect. Although a rich body of research associated with policies regarding teacher preparation and professional development exists, a more closely related area of research focused specifically on the policies regarding preparation and professional development of JROTC instructors is limited. This lack of research presents a unique opportunity to explore the experiences of JROTC instructors and their perspectives on policies affecting teacher preparation and professional development. This qualitative exploratory single-case study can help to advance understanding of the complexities and nuances of teacher preparation and professional development policies supporting the JROTC instructors serving in high schools across the United States and overseas. One-on-one interviews with 14 JROTC personnel who had completed required teacher preparation requirements and professional development initiatives were conducted. Data analysis revealed 11 themes. Recommendations for improving policies concerning JROTC instructor preparation and professional development, including placing greater emphasis on the unique requirements, as well as suggestions for future research, are provided.

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.

This study analyzes the role of innovation in the development of smart cities in Latin America. It focuses on how emerging technologies and sustainable strategies are being integrated into urban planning and urban development. In this sense, this study seeks to contribute to the smart city literature by answering the following research questions: (i) To what extent smart city innovative initiatives have been addressed in Latin America? and (ii) To what extent scholars have addressed sustainable innovation strategies in the smart city literature? To this end, this is the first comprehensive bibliometric analysis of smart city research in Latin America, with a structured and systematized review of the available literature. This methodological approach allows cluster visualization and detailed analysis of inter-node relationships using the VOSViewer software. The research comprises 4 stages: (a) search criteria; (b) selection of documents; (c) software and data extraction; and (d) analysis of results and trends. Results indicate that studies on the Latin America region began to develop in 2012, with Brazil as a leader in this field and the tourism sector as the most relevant. Nevertheless, strong international collaboration was identified in co-authoring studies, underscoring a cooperative approach to solving common urban problems. The most active research area is technological innovation and sustainability, with focus on solutions for urban mobility, quality of life and smart governance. Finally, this work underlines the need to continue exploring the integration of technology in urban development, suggesting an agenda to guide future research to evaluate the sustainability and long-term impacts of smart city initiatives in Latin America. From the policy perspective, smart city initiatives need to be human-centered to boost smart solutions adoption and to guarantee long term local impacts.

This paper is the third in a series focused on bridging the gap between secondary and higher education. Our primary objective is to develop a robust theoretical framework for an innovative e-business model called the Undergraduate Study Programme Search System (USPSS). This system considers multiple criteria to reduce the likelihood of exam failure or the need for multiple retakes, while maximizing the chances of successful program completion. Testing of the proposed algorithm demonstrated that the Stochastic Gradient Boosted Regression Trees method outperforms the current method used in Lithuania for admitting applicants to 47 educational programs. Specifically, it is more accurate than the Probabilistic Neural Network for 25 programs, the Ensemble of Regression Trees for 24 programs, the Single Regression Tree for 18 programs, the Random Forest Regression for 16 programs, the Bayesian Additive Regression Trees for 13 programs, and the Regression by Discretization for 10 programs.