Understanding the factors that influence early science achievement is crucial for developing effective educational policies and ensuring equity within the education system. Despite its importance, research on the patterns of young children achieving science learning milestones and the factors that can reduce disparities between students with and without disabilities remains limited. This study analyzes data from the Early Childhood Longitudinal Study of Kindergarten Cohort 2011 (ECLS-K: 2011), which includes 18,174 children from 1328 schools across the United States, selected through a complex sampling process and spanning kindergarten to 5th grade. Utilizing survival analysis, the study finds that children with disabilities achieve science milestones later than their peers without disabilities, with these disparities persisting from early grades. The research highlights the effectiveness of center-based programs in enhancing science learning, particularly in narrowing the achievement gap between children with and without disabilities. These findings contribute to the broader discourse on equity in the education system and policy by introducing novel methodologies for assessing the frequency and duration of science learning milestones, and by providing insights into effective strategies that support equitable science education.
This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.
The objective of the research is twofold. The study examines the role of public finance in promoting sustainable development in SSA. Secondly, the study investigates the optimal level of public finance beyond which public finance crowds out investment and hinders sustainable development in SSA. The study adopts a battery of econometric techniques such as the traditional ordinary least square (OLS) estimation technique, Driscoll-Kraay covariance matrix estimator, and the dynamic panel threshold model. The study found that an increase in public debts lead to a decline in sustainable development. In contrast, the results show that increase in spending on health and education, and tax can engender sustainable development in SSA. Further, we uncover the optimal levels of public spending on health and education, and public debts that engenders sustainable development in SSA. One main implication of the findings is that governments across SSA needs to reduce public debts levels and increase public spending on health and education to within the threshold levels established in this study to aid sustainable development in SSA.
Background: Various studies have demonstrated the usefulness of Google search data for public health-monitoring systems. The aim of this study is to be estimated interest of public in infectious diseases in infectious diseases in South Korea, the five other countries. Methods: We conducted cross-country comparisons for queries related to the H1N1 virus and Middle East respiratory syndrome coronavirus (MERS-CoV). We analyzed queries related to the novel coronavirus disease (COVID-19) from 20 January to 13 April 2020, and performed time-descriptive and correlation analyses on trend patterns. Results: Trends in H1N1, MERS-CoV, and COVID-19 queries in South Korea matched those in the five other countries and worldwide. The relative search volume (RSV) for the MERS-CoV virus increased as the cumulative number of confirmed cases in South Korea increased and decreased significantly as the number of confirmed cases decreased. The volume of COVID-19 queries dramatically increased as South Korea’s confirmed COVID-19 cases grew significantly at the community level. However, RSV remained stable over time. Conclusions: Google Trends provides real-time data based on search patterns related to infectious diseases, allowing for continuous monitoring of public reactions, disease spread, and changes in perceptions or concerns. We can use this information to adjust their strategies of the prevention of epidemics or provide timely updates to the public.
To fight inflation, European Central Bank (ECB) announced 10 successive interest rate hikes, starting on 27 July 2022, igniting an unprecedented widening of interest rate spreads in the euro area (ΕΑ). Greek banks, however, recorded among the highest interest rate spreads, far exceeding ΕΑ median and weighted average. Indeed, we document a strong asymmetric response of Greek banks to ECB interest rate hikes, with loan interest rates rising immediately, whilst deposit interest rates remained initially unchanged and then rose sluggishly. As a result, the interest rate spread hit one historical record after another. Greek systemic banks, probably taking advantage of the high concentration and low competition in the domestic sector benefited from key ECB interest rate hikes, recording gigantic increases in net interest income (NII), and consequently, substantial profits (almost €7.4 billion in the 2022–2023 biennium). Such excessive accumulation of profits (that deteriorates the living conditions of consumers) by the banking system could be called the inflation of “banking greed”, or bankflation. This new source of inflation created by the oligopolistic structure of the Greek banking sector counterworks the very reason for ECB interest rate increases and requires certain policy analysis recommendations in coping with it.
The objective of this paper is to analyze the impact of infrastructure financing on economic growth in emerging markets through the application of both quantitative and qualitative research methodologies. In this study, the research will employ both primary and secondary data to investigate the impact of different structures of infrastructure financing on the performance of the economy through interviews with the stakeholders and policy documents alongside quantitative data from the World Bank and the IMF. The quantitative analysis employs the econometric models to establish the effect of infrastructure investment on the GDP growth of the selected countries, India, China, Brazil, and Nigeria. Additional secondary qualitative data obtained from interviews with policymakers and financial specialists from Brazil, India, and South Africa offer more practical information regarding the efficiency of the discussed financing approaches. This paper is therefore able to conclude that appropriate management of infrastructure investments, particularly those that involve the PPP, are central to the development of the economy. However, certain drawbacks such as the lack of regularity of data and the disparity in the effectiveness of financing instruments by the regions are pointed out. The research provides policy implications to policymakers and investors who wish to finance infrastructure in the emerging economy to enhance economic growth in the long run.
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