943 resultados para rural education


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The holistic conception of the troika, as described in the first chapter, centres on the relationship between the implicit and explicit teaching of values the nurturing of the specific dimensions of quality teaching and the opportunity to ‘walk the talk’ of the values education program through aspects such as practical citizenship (Lovat, Toomey, Clement, Crotty & Nielsen, 2009). It is proposed in this chapter that the conception can be realized through the embedding of Philosophy in the Classroom within pre-service teaching programs. The troika, a Russian sleigh with three horses, only function well when there is complete synergy and balance between all Classroom is a scaffold for ensuring that all three elements of the troika, namely, quality teaching, values education and service learning in the form of education for citizenship, exist within the classroom to achieve an optimal learning, growth and wellbeing for all students. For this to be more widely accomplished Philosophy in the Classroom and discusses how it constitutes a successful synergy and balance of the troika for effective teaching. It then proposes how it might be embedded into pre-service teacher education.

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Safety interventions (e.g., median barriers, photo enforcement) and road features (e.g., median type and width) can influence crash severity, crash frequency, or both. Both dimensions—crash frequency and crash severity—are needed to obtain a full accounting of road safety. Extensive literature and common sense both dictate that crashes are not created equal, with fatalities costing society more than 1,000 times the cost of property damage crashes on average. Despite this glaring disparity, the profession has not unanimously embraced or successfully defended a nonarbitrary severity weighting approach for analyzing safety data and conducting safety analyses. It is argued here that the two dimensions (frequency and severity) are made available by intelligently and reliably weighting crash frequencies and converting all crashes to property-damage-only crash equivalents (PDOEs) by using comprehensive societal unit crash costs. This approach is analogous to calculating axle load equivalents in the prediction of pavement damage: for instance, a 40,000-lb truck causes 4,025 times more stress than does a 4,000-lb car and so simply counting axles is not sufficient. Calculating PDOEs using unit crash costs is the most defensible and nonarbitrary weighting scheme, allows for the simple incorporation of severity and frequency, and leads to crash models that are sensitive to factors that affect crash severity. Moreover, using PDOEs diminishes the errors introduced by underreporting of less severe crashes—an added benefit of the PDOE analysis approach. The method is illustrated with rural road segment data from South Korea (which in practice would develop PDOEs with Korean crash cost data).

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Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.

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It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

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Understanding the expected safety performance of rural signalized intersections is critical for (a) identifying high-risk sites where the observed safety performance is substantially worse than the expected safety performance, (b) understanding influential factors associated with crashes, and (c) predicting the future performance of sites and helping plan safety-enhancing activities. These three critical activities are routinely conducted for safety management and planning purposes in jurisdictions throughout the United States and around the world. This paper aims to develop baseline expected safety performance functions of rural signalized intersections in South Korea, which to date have not yet been established or reported in the literature. Data are examined from numerous locations within South Korea for both three-legged and four-legged configurations. The safety effects of a host of operational and geometric variables on the safety performance of these sites are also examined. In addition, supplementary tables and graphs are developed for comparing the baseline safety performance of sites with various geometric and operational features. These graphs identify how various factors are associated with safety. The expected safety prediction tables offer advantages over regression prediction equations by allowing the safety manager to isolate specific features of the intersections and examine their impact on expected safety. The examination of the expected safety performance tables through illustrated examples highlights the need to correct for regression-to-the-mean effects, emphasizes the negative impacts of multicollinearity, shows why multivariate models do not translate well to accident modification factors, and illuminates the need to examine road safety carefully and methodically. Caveats are provided on the use of the safety performance prediction graphs developed in this paper.

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A study was done to develop macrolevel crash prediction models that can be used to understand and identify effective countermeasures for improving signalized highway intersections and multilane stop-controlled highway intersections in rural areas. Poisson and negative binomial regression models were fit to intersection crash data from Georgia, California, and Michigan. To assess the suitability of the models, several goodness-of-fit measures were computed. The statistical models were then used to shed light on the relationships between crash occurrence and traffic and geometric features of the rural signalized intersections. The results revealed that traffic flow variables significantly affected the overall safety performance of the intersections regardless of intersection type and that the geometric features of intersections varied across intersection type and also influenced crash type.

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Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

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This paper is concerned with the general issues of ageing, learning, and education for the elderly. It also examines the more specific issues of why, how and what elders want to learn. The world's population is ageing rapidly. For example, it is estimated that by 2020 20% of the population in the USA will be 65 years old and over. It is predicted that 24% of the Hong Kong population will be over 65 years old by 2025 (Bartlett & Phillips, 1995). The phenomenon has been described in colorful terms as the "silver tsunami" (Pew Report, 2001 cited in Summer, 2007). Ageing has an impact on all aspects of human life including the social, economic, cultural and political domains. Understanding and providing for ageing is, therefoer, an important issue for the twenty-first century. The World Health Organisation ([WHO], 2002) has proposed a model of active ageing based on optimizing opportunities for health, particulation, and security in order to enhance quality of life for people as they age. The focus in this paper is on the education and learning aspect of participation as people age.

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Background: Poor feeding practices in early childhood contribute to the burden of childhood malnutrition and morbidity. Objective: To estimate the key indicators of breastfeeding and complementary feeding and the determinants of selected feeding practices in Sri Lanka. Methods: The sample consisted of 1,127 children aged 0 to 23 months from the Sri Lanka Demographic and Health Survey 2000. The key infant feeding indicators were estimated and selected indicators were examined against a set of individual-, household-, and community- level variables using univariate and multivariate analyses. Results: Breastfeeding was initiated within the first hour after birth in 56.3% of infants, 99.7% had ever been breastfed, 85.0% were currently being breastfed, and 27.2% were being bottle-fed. Of infants under 6 months of age, 60.6% were fully breastfed, and of those aged 6 to 9 months, 93.4% received complementary foods. The likelihood of not initiating breastfeeding within the first hour after birth was higher for mothers who underwent cesarean delivery (OR = 3.23) and those who were not visited by a Public Health Midwife at home during pregnancy (OR = 1.81). The rate of full breastfeeding was significantly lower among mothers who did not receive postnatal home visits by a Public Health Midwife. Bottlefeeding rates were higher among infants whose mothers had ever been employed (OR = 1.86), lived in a metropolitan area (OR = 3.99), or lived in the South-Central Hill country (OR = 3.11) and were lower among infants of mothers with secondary education (OR = 0.27). Infants from the urban (OR = 8.06) and tea estate (OR = 12.63) sectors were less likely to receive timely complementary feeding than rural infants. Conclusions: Antenatal and postnatal contacts with Public Health Midwives were associated with improved breastfeeding practices. Breastfeeding promotion strategies should specifically focus on the estate and urban or metropolitan communities.

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This paper explores models of teaching and learning music composition in higher education. It analyses the pedagogical approaches apparent in the literature on teaching and learning composition in schools and universities, and introduces a teaching model as: learning from the masters; mastery of techniques; exploring ideas; and developing voice. It then presents a learning model developed from a qualitative study into students’ experiences of learning composition at university as: craft, process and art. The relationship between the students’ experiences and the pedagogical model is examined. Finally, the implications for composition curricula in higher education are presented.

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In rural low-voltage networks, distribution lines are usually highly resistive. When many distributed generators are connected to such lines, power sharing among them is difficult when using conventional droop control, as the real and reactive power have strong coupling with each other. A high droop gain can alleviate this problem but may lead the system to instability. To overcome4 this, two droop control methods are proposed for accurate load sharing with frequency droop controller. The first method considers no communication among the distributed generators and regulates the output voltage and frequency, ensuring acceptable load sharing. The droop equations are modified with a transformation matrix based on the line R/X ration for this purpose. The second proposed method, with minimal low bandwidth communication, modifies the reference frequency of the distributed generators based on the active and reactive power flow in the lines connected to the points of common coupling. The performance of these two proposed controllers is compared with that of a controller, which includes an expensive high bandwidth communication system through time-domain simulation of a test system. The magnitude of errors in power sharing between these three droop control schemes are evaluated and tabulated.

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Despite some segments of the creative industries in Australia performing better than other segments in terms of earnings and employment growth, they all rely on highly skilled workers and face similar workforce challenges. Workers typically experience multiple entry attempts, spells of unemployment, short-term contracts, high degrees of mobility, casual/part-time employment within and outside the creative industries, and pressure to ensure their skills remain relevant. Skills shortages and gaps, an insufficient supply of high quality industry-ready graduates, difficulties in predicting demand for skills, weak linkages between industry and education providers, reliance on overseas talent in some segments, limited opportunities for workers to engage in skill development, and pressure on workers to keep abreast of technological developments are ongoing issues in the creative industries workforce. In response to these concerns, the Australian Research Council, three State Governments, industry, and a large vocational education and training (VET) provider funded Queensland University of Technology (QUT) to conduct the 60Sox project. This three-year project investigated the education, training, and work experiences of aspiring creatives defined as new entrants, recent graduates, and students enrolled in creative industries courses. It involved the largest survey of aspiring creatives ever undertaken in Australia, attracting 507 respondents, and a survey of 50 employers. Using the framework proposed by Hannan, Raffe, and Smyth (1996), this article presents findings from an analysis of the macro and micro labour market outcomes of aspiring creatives using data from the two 60Sox project surveys and publicly available sources. The analysis confirmed that many graduates of creative industries courses who participated in the 60Sox survey and the national surveys for the National Centre for Vocational Education Research and Graduate Careers Australia were struggling to make a successful transition from education to work. This article also discusses the causes of this key finding and possible solutions to address transition issues.

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In Australian universities, journalism educators usually come to the academy from the journalism profession and consequently place a high priority on leading students to develop a career-focussed skill set. The changing nature of the technological, political and economic environments and the professional destinations of journalism graduates place demands on journalism curricula and educators alike. The profession is diverse, such that the better description is of many ‘journalisms’ rather than one ‘journalism’ with consequential pressures being placed on curricula to extend beyond the traditional skill set, where practical ‘writing’ and ‘editing’ skills dominate, to the incorporation of critical theory and the social construction of knowledge. A parallel set of challenges faces academic staff operating in a higher education environment where change is the only constant and research takes precedent over curriculum development. In this paper, three educators at separate universities report on their attempts to implement curriculum change to imbue graduates with better skills and attributes such as enhanced team work, problem solving and critical thinking, to operate in the divergent environment of 21st century journalism. The paper uses narrative case study to illustrate the different approaches. Data collected from formal university student evaluations inform the narratives along with rich but less formal qualitative data including anecdotal student comments and student reflective assessment presentations. Comparison of the three approaches illustrates the dilemmas academic staff face when teaching in disciplines that are impacted by rapid changes in technology requiring new pedagogical approaches. Recommendations for future directions are considered against the background or learning purpose.