755 resultados para Computer Uses in Education


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An essential aspect of school effectiveness theory is the shift from the social to the organisational context, from the macro- to the micro-culture. The school is represented largely as a bounded institution, set apart, but also in a precarious relationship with the broader social context. It is ironic that at a time when social disadvantage appears to be increasing in Britain and elsewhere, school effectiveness theory places less emphasis on poverty, deprivation and social exclusion. Instead, it places more emphasis on organisational factors such as professional leadership, home/school partnerships, the monitoring of academic progress, shared vision and goals. In this article, the authors evaluate the extent to which notions of effectiveness have displaced concerns about equity in theories of educational change. They explore the extent to which the social structures of gender, ethnicity, sexualities, special needs, social class, poverty and other historical forms of inequality have been incorporated into or distorted and excluded from effectiveness thinking.

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The third chapter, data mining in education, examines potentials and constraints in the use of data mining in education, summarizing the potential they have to offer meaningful support to: students, teachers, tutors, authors, developers, researchers, and the education and training institutions in which they work and study.

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This paper examines the wage premium to computer use in Sweden in the early 1990’s. I use simple regression model and interaction terms in my paper to examine the effect of computer use at work. Although the data is only one-year cross-section data, my results clearly show a wage premium to computer use in Sweden. There are also interesting findings in my paper by using Swedish data. From the results, I find wage premium to be related to intensity of computer use at work.

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The recently released "Educational PAC" attempts to place basic education at the center of the social debate. We have subsidized this debate, offering a diagnosis of how different education levels can impact individuals' lives through broad and easily interpreted indicators. Initially, we analyze how much each educational level reaches the poorest population. For example, how are those in the bottom strata of income distribution benefited by childcare centers, private secondary education, public university or adult education. The next step is to quantify the return of educational actions, such as their effects on employability and an individual's wages, and even health as perceived by the individual, be that individual poor, middle class or elite. The next part of the research presents evidence of how the main characters in education, aka mothers, fathers and children, regard education. The site available with the research presents a broad, user-friendly database, which will allow interested parties to answer their own questions relative to why people do not attend school, the time spent in the educational system and returns to education, which can all be cross-sectioned with a wide array of socio-demographic attributes (gender, income, etc.) and school characteristics (is it public, are school meals offered, etc.) to find answers to: why do young adults of a certain age not attend school? Why do they miss classes? How long is the school day? Aside from the whys and hows of teaching, the research calculates the amount of time spent in school, resulting from a combination between absence rates, evasion raters and length of the school day. The study presents ranks of indicators referring to objective and subjective aspects of education, such as the discussion of the advantages and care in establishing performance based incentives that aim at guiding the states in the race for better educational indicators.

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In this paper, we try to rationalize the existence of one of the most common affirmative action policies: educational quotas. We model a two period economy with asymmetric information and endogenous human capital formation. Individuals may be from two different groups in the population, where each group is defined by an observable and exogenous characteristic. The distribution of skills differ across groups. We introduce educational quotas into the model by letting the planner reduce the effort cost that a student from one of the groups has to endure in order to be accepted into a university. Affirmative action policies can be interpreted as a form of ``tagging" since group characteristics are used as proxies for productivity. We find that although educational quotas are usually efficient, they need not subsidize the education of the low skill group.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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We studied the statistical distribution of student's performance, which is measured through their marks, in university entrance examination (Vestibular) of UNESP (Universidade Estadual Paulista) with respect to (i) period of study - day versus night period (ii) teaching conditions - private versus public school (iii) economical conditions - high versus low family income. We observed long ubiquitous power law tails in physical and biological sciences in all cases. The mean value increases with better study conditions followed by better teaching and economical conditions. In humanities, the distribution is close to normal distribution with very small tail. This indicates that these power law tails in science subjects axe due to the nature of the subjects themselves. Further and better study, teaching and economical conditions axe more important for physical and biological sciences in comparison to humanities at this level of study. We explain these statistical distributions through Gradually Truncated Power law distributions. We discuss the possible reason for this peculiar behavior.

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We studied the statistical distribution of candidate's performance which is measured through their marks in university entrance examination (Vestibular) of UNESP (Universidade Estadual Paulista) for years 1998, 1999, and 2000. All students are divided in three groups: Physical, Biological and Humanities. We paid special attention to the examination of Portuguese language which is common for all and examinations for the particular area. We observed long ubiquitous power law tails in Physical and Biological sciences. This indicate the presence of strong positive feedback in sciences. We are able to explain completely these statistical distributions through Gradually Truncated Power law distributions which we developed recently to explain statistical behavior of financial market. The statistical distribution in case of Portuguese language and humanities is close to normal distribution. We discuss the possible reason for this peculiar behavior.

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The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

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Includes bibliography