This study examined the impact of transition programs on the post-school outcomes of Saudi adolescents with special needs. The study examines the impact of vocational training, career counseling, and community participation on job outcomes, the pursuit of further education, and the acquisition of independent living skills. The research is conducted on a diverse sample of 500 students (260 girls and 240 boys). The data is analyzed using descriptive statistics, regression analysis, and ANOVA, revealing positive perceptions of transition services and identifying significant predictors of post-school performance. Post-hoc testing enhances understanding of nuanced differences between groups. The findings underscore the need for tailored transition programs that prioritize the extent of vocational training and apply culturally responsive approaches. Proposed approaches include enhancing vocational training programs, enhancing career counseling services, encouraging community involvement, and performing continuous research and evaluation. This study makes substantial additions to the current corpus of knowledge and provides crucial information to influence policy and practice in Saudi Arabia.
This article evaluates the Didactic Strategies for Teaching Mathematics (DSTM) program, designed to enhance the teaching of mathematical content in primary and secondary education in a hybrid modality. In alignment with SENACYT’s Gender-STEM-2040 Policy, which emphasizes gender equality as a foundational principle of education, this study aims to assess whether initial teacher training aligns with this policy through the use of mathematical strategies promoting gender equality. A descriptive-correlational approach was applied to a sample of 64 educators, selected based on their responses during the training, with the goal of improving teaching and data collection methodologies. Findings indicate that, although most teachers actively engage in training, an androcentric approach persists, with sexist language and a curriculum that renders girls invisible, hindering the fulfillment of the National Gender Equality Policy in Science, Technology, and Innovation of Panama (Gender-STEM Policy 2040). Additionally, through a serendipitous finding, a significant gap in student activity levels, especially in secondary school, was discovered. While in primary school, activity levels were similar between genders, a decline in active participation among girls in secondary school was observed. This discovery, not initially contemplated in the study’s objectives, provides valuable insights into gender differences in active participation, particularly in higher educational stages. The serendipity suggests the need for further exploration of social, environmental, and family factors that may influence this decrease in girls’ active participation. The article concludes with a preliminary diagnosis and a call to deepen gender equality training and the effective implementation of coeducation in Panama’s educational system.
This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.
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.
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 world has never been more developed, yet humanity is on the brink of irreversible environmental loss. Despite the urgency of the situation, there is a limited body of studies addressing environmental concerns in higher education institution, particularly in developing countries, i.e., Saudi Arabia. Sustainable development is the only viable solution, albeit it requires the courage to initiate and sustain efforts dedicated to preserving the environment for the well-being of future generation. The article delves into this issue and examines the impact of environmental education program (EEP) on environmental performance (EP) via waste minimization behaviour (WMB). The research involved meticulous data collection from a sample of 597 students, representing diverse genders and academic specialties at the esteemed public university—King Faisal University (KFU) in Saudi Arabia. The study used statistical software (including SPSS and AMOS, v 25) for rigorous analysis and revealed significant findings. Firstly, the study showed a significant and positive relationship between EEP and EP. Secondly, it revealed a significant and positive association between EEP and WMB. Thirdly, the study ascertained a significant and positive association between WMB and EP. Finally, the study found that the relationship between EEP and EP remains significant even after presenting WMB as a mediator, proposing that WMB has a partial mediation role between EEP and EP. The results highlighted the significance role of EEP in stimulating WMB and achieving EP in the Saudi universities, which contributes to national initiative of green Saudia.
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