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Boys in the Kingdom of Saudi Arabia consistently and significantly underperform compared to girls across different grades and subjects, forming one of the largest gender gaps in student achievement in the world. Saudi Arabia offers a unique setting in which boys and girls attend separate schools on a universal basis starting from grade 1. This means that boys and girls are educated only by male and female teachers, respectively, in effect inhabiting parallel education systems. In this context, this study examines the factors that are associated with student achievement in mathematics and science in grades 4 and 8 and the extent to which these associations are different for boys and girls, in an effort to gain insights into boys' underachievement in mathematics and science in Saudi Arabia. The paper employs data from two recent large-scale assessments of education: Trends in International Mathematics and Science Study (TIMSS) 2019 and Saudi Arabia's National Assessment of Learning Outcomes (NALO) 2018. A series of hierarchical two-level linear regression models showed that in grade 4, school climate was more strongly associated with boys' compared with girls' achievement in both mathematics and science, with boys attending schools of poorer school climate having a considerably lower performance compared with girls attending such schools. The findings also indicated that although greater literacy and numeracy readiness was linked with higher science achievement among boys and girls, grade 4 boys tended to benefit more from this readiness than girls. In addition, the results show that student absenteeism in grade 4 is particularly strongly associated with decreases in mathematics achievement among boys. In grade 8, significant interactions between gender and the extent to which students feel confident in science, the degree of schools' emphasis on academic success, and teachers' age are observed. The paper concludes by discussing some of the implications of these findings for educators and policy makers in Saudi Arabia. [ABSTRACT FROM AUTHOR]

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers. [ABSTRACT FROM AUTHOR]

This paper develops an agent-based computational model of violent political revolutions in which a subjugated population of citizens and an armed revolutionary organisation attempt to overthrow a central authority and its loyal forces. The model replicates several patterns of rebellion consistent with major historical revolutions, and provides an explanation for the multiplicity of outcomes that can arise from an uprising. The relevance of the heterogeneity of scenarios predicted by the model can be understood by considering the recent experience of the Arab Spring involving several rebellions that arose in an apparently similar way, but resulted in completely different political outcomes: the successful revolution in Tunisia, the failed protests in Saudi Arabia and Bahrain, and civil war in Syria and Libya. [ABSTRACT FROM AUTHOR]

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. [ABSTRACT FROM AUTHOR]

This study aimed to identify the (closed classroom environment, CCE) and the (open classroom environment, OCE) in teaching mathematics to female university students through the validity and reliability implications used by the female students. The study sample included (31) female students, divided into (17) female students in (OCE), and (14) female students in (CCE) in the Kingdom of Saudi Arabia. A purposive sample was chosen, and a mathematics scale was applied to detect the effect of the closed and (OCE) on mathematical operations, which include (Differentiation and Integration, algebra, probability and statistics, and geometric shapes). For Differentiation and Integration (-0.144), teaching algebra (-0.033), teaching statistics (0.094), and teaching geometric shapes (-0.105), the values are not statistically significant at the significance level (0.05). The results showed that the reliability of the split-half method on (CCE) was (Part1 = 0.951), and on (OCE) it was (Part2 = 0.919), meaning that the split-half method was (0.978). And the Cronbach's alpha reliability coefficient was (0.959). The results showed that there are no statistically significant differences at the significance level (0.05) between (CCE) and (OCE) for Differentiation and Integration. There are differences in algebra in favor of (CCE), there are differences in statistics and probability in (OCE), and there are differences in geometric shapes in (OCE). The results showed that there are no statistically significant differences at the significance level (0.05) between (CCE) and (OCE) due to the teacher type variable. The study recommends conducting more studies and research related to (OCE) and (CCE) and their impact on mathematics. [ABSTRACT FROM AUTHOR]

In 2020, coronavirus (COVID-19) was declared a global pandemic and it remains prevalent today. A necessity to model the transmission of the virus has emerged as a result of COVID-19's exceedingly contagious characteristics and its rapid propagation throughout the world. Assessing the incidence of infection could enable policymakers to identify measures to halt the pandemic and gauge the required capacity of healthcare centers. Therefore, modeling the susceptibility, exposure, infection, and recovery in relation to the COVID-19 pandemic is crucial for the adoption of interventions by regulatory authorities. Fundamental factors, such as the infection rate, mortality rate, and recovery rate, must be considered in order to accurately represent the behavior of the pandemic using mathematical models. The difficulty in creating a mathematical model is in identifying the real model variables. Parameters might vary significantly across models, which can result in variations in the simulation results because projections primarily rely on a particular dataset. The purpose of this work was to establish a susceptible–exposed–infected–recovered (SEIR) model describing the propagation of the COVID-19 outbreak throughout the Kingdom of Saudi Arabia (KSA). The goal of this study was to derive the essential COVID-19 epidemiological factors from actual data. System dynamics modeling and design of experiment approaches were used to determine the most appropriate combination of epidemiological parameters and the influence of COVID-19. This study investigates how epidemiological variables such as seasonal amplitude, social awareness impact, and waning time can be adapted to correctly estimate COVID-19 scenarios such as the number of infected persons on a daily basis in KSA. This model can also be utilized to ascertain how stress (or hospital capacity) affects the percentage of hospitalizations and the number of deaths. Additionally, the results of this study can be used to establish policies or strategies for monitoring or restricting COVID-19 in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Aim/Purpose: This research aimed to measure the effectiveness of using thinking maps through the Edmodo network to develop achievement and mathematical connections skills among middle school students. Background: One of the most important and major problems in education is reduced levels of academic achievement among students generally and in mathematics specifically. This is having a negative impact on academic outcomes. As mentioned in statement of the problem, several studies have identified weaknesses in academic achievement in mathematics. The results and recommendations of previous studies have referred to the effectiveness of thinking maps in developing numerous variables. Previous studies have identified weaknesses in mathematical connections skills. No Arabic studies have addressed the effectiveness of thinking maps through the Edmodo network in developing achievement and mathematical connections skills among middle school students. Methodology: The participants were a purposive sample of 102 second-year middle school students. These were divided into two groups: experimental (n = 49) and control (n = 53). To achieve the research objectives, the experimental approach in its quasiexperimental design was adopted with (pre-post) measurement for both groups. Data were analyzed using the Statistical Package for Social Sciences (SPSS). Contribution: This study added information to the literature on the effectiveness of the thinking maps strategy through the Edmodo network in developing achievement and mathematical connections skills. Devising a modern teaching strategy to help students solve mathematical problems and thus can be generalized to various fields of life. This also the first study on this subject in Saudi Arabia. Findings: The results showed there was a significant difference between the mean post-test scores of the experimental and control groups on the achievement test in favor of the experimental group. Additionally, there was a significant difference between the mean post-test scores of the experimental and control groups on the mathematical connections skills test in favor of the experimental group. There was also a positive correlation between the development of achievement and mathematical connections skills among middle school students who used thinking maps through the Edmodo network. Recommendations for Practitioners: At a practice level, holding courses and training workshops for middle school mathematics teachers that include training on how to use modern learning models enhanced with technology, including the thinking Maps strategy, in the mathematics curriculum. Preparing guidelines for middle school mathematics teachers on how to use Thinking Maps via the Edmodo Network and how to train students in its use. Recommendation for Researchers: Further research is needed to study the Effectiveness of the Thinking Maps strategy via the Edmodo network on developing achievement and mathematical connections skills in other subjects and at different educational stages. Impact on Society: Our findings encourage teachers and educational supervisors to adopt the use of thinking maps on learning platforms for mathematics teaching as an effective method for developing achievement and mathematical connections skills. Benefiting from the applications and experiences of developed countries who have used e-learning in teaching curricula in order to keep pace with contemporary developments. Future Research: Future studies could be extended to identify the effectiveness of maps of strategic thinking across Edmodo network variables within other subsidiaries, such as mathematical communication, creative thinking, mathematical proof, mind habits, and so on. Assess the effectiveness of play-based learning strategies via the Edmodo network in developing achievement and mathematical connection skills. Conduct a study that measures teachers' and students' attitudes toward using the Thinking Maps strategy via the Edmodo network. Assessing the effectiveness of using the Thinking Maps strategy via an Edmodo network in achieving and developing creative skills among secondary school students. [ABSTRACT FROM AUTHOR]

The underrepresentation of women in the STEM workforce is a global issue. In Saudi Arabia, women constitute 48% of undergraduates in STEM, but their participation in STEM careers remains particularly low. We explored the current state of e-mentoring, and the potential for co-designing to enhance e-mentoring experiences for youth in the Saudi context. We report on how we sought to understand the opportunities, barriers and requirements of e-mentoring for young women in Saudi Arabia through (1) the application of a traditional programme of STEM e-mentoring, (2) workshops on the redesign of e-mentoring, and (3) a co-design activity as the first phase of an alternative e-mentoring process. The study demonstrated that the traits of the participants' generation had a major effect on the findings; more so than cultural norms. This means that the findings have wider implications than just within the Saudi context. We identify a number of recommendations for designing e-mentoring programmes for young women and teenagers, including un-platforming traditional approaches to e-mentoring and the inclusion of co-design activities as a first step in the e-mentoring process. [ABSTRACT FROM AUTHOR]

Recent studies have proposed using well-defined relationships between network productivity and accumulation—otherwise known as Network or Macroscopic Fundamental Diagrams (network MFDs)—to model the dynamics of large-scale urban traffic networks. Network MFDs have been used to develop a variety of network-wide traffic control policies to improve a network’s operational efficiency. However, the relationship between a network’s MFD and its safety performance has not been well explored. This study proposes the existence of a Macroscopic Safety Diagram (MSD) that relates safety performance (e.g., likelihood of a crash occurring or number of vehicle conflicts observed) with the current network state (i.e., average density) in an urban traffic network. We theoretically posit a relationship between a network’s MSD and its MFD based on the average maneuver envelop of vehicles traveling within the network. Based on this model, we show that the density associated with maximum crash propensity is always expected to be larger than the density associated with maximum network productivity. This finding suggests that congested states are not only inefficient, but they might also be associated with more crashes, which can be both more unsafe and lead to decreased network reliability. These theoretical results are validated using surrogate safety assessment metrics in microsimulation and limited field empirical data from a small arterial network in Riyadh, Kingdom of Saudi Arabia. The existence of such MSDs can be used to develop more comprehensive network-wide control policies that can ensure both safe, efficient and reliable network operations. [ABSTRACT FROM AUTHOR]

This study focused on comparing mathematics teachers’ qualifications, practices, and perceptions between Saudi and Taiwanese schools. Data analyzed in this study were the responses of mathematics teachers to the Teacher Background Questionnaire—8th Grade from the Trends in International Mathematics and Science Study (TIMSS) in 2007. The Saudi sample consisted of 171 teachers while the Taiwanese sample consisted of 152 teachers. The comparison between the two countries revealed that there were significant differences in teachers’ preparation for teaching specific mathematics topics, professional development programs, and in teachers’ perceptions about the effects of school environment on students’ TIMSS scores. In addition, the two countries’ results differed in the mathematics topics that had not been taught to students, in assessment tools commonly used in mathematics, and in the type of questions used in tests. Some teachers’ qualifications and practices were found to be related to students’ scores. Results are discussed and recommendations for educators and policymakers are proffered. [ABSTRACT FROM PUBLISHER]