815 resultados para Practical training in school


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The purpose of this study was to determine if there were differences between in-school and out-of-school day care centres. Five centres housed in public schools and five housed in other locations were selected for the research. Aquality assessment was administered in each centre which examined the following components - physical environment, adult social structure and socia-emotional environment, children's socia-emotional environment, cognitive stimulation program and toys and equipment. Quantitative analysis using simple t-tests showed a significant difference between in-school and out-of-school day cares for the physical environment variable. Differences approached significance for the children's socia-emotional environment variable as well as overall quality. Qualitative analysis using a triangulated methodology revealed noticeable differences for every variable. The researcher concluded that both the quality of the physical environment and the capabilities of the administrators strongly influence the quality of the day care environment. This study also included an assessment of children's attitude toward learning. No significant difference was found between in-school and out-of-school centres.

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Background: Soil-transmitted helminth (STH) infections are endemic in Honduras but their impact on children’s health is not well studied. Objectives: To evaluate the prevalence and intensity of STH infections and their association with nutrition and growth in a sample of Honduran children. Methodology: A cross-sectional study was done among Honduran rural school-age children in 2011. Blood and stool samples and anthropometric measurements were obtained to determine nutritional status, STH infection and growth status, respectively. Results: The STH prevalence among 320 studied children was 72.5%. Prevalence by species was 30%, 67% and 16% for Ascaris, Trichuris and 16% hookworms, respectively. High intensity infections were associated with decreased growth scores but regardless of intensity, co-infections negatively affected growth indicators. Conclusions: The health burden of STH infections is related to high parasitic load but also to the presence of low-intensity concurrent infections. The synergistic effects of polyparasitism in underprivileged children warrants more attention.

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Interventions using applied behaviour analysis (ABA) are widely used with children with autism spectrum disorders (ASD). Individuals who work with this population are important to target for ABA education. This study evaluated the efficacy of a self-directed program in increasing parent and student ABA knowledge and skills, self-efficacy, and new skill development in children with ASD. Study 1 was a pilot study of the newly developed evaluation materials. Study 2 tested the self-instructional package with three parents of children with ASD, three university students, and eight children diagnosed with ASD. Parents and students were given the Simple Steps ABA training package to use independently and were measured using a multiple baseline across participants and/or skills design. After training, ABA knowledge scores and self-efficacy showed variable improvement as did children’s appropriate behaviours. These results suggest that more research is needed to determine the efficacy of a self-instructional ABA package.

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Background: Soil-transmitted helminth (STH) infections are endemic in Honduras and efforts are underway to decrease their transmission. However, current evidence is lacking in regards to their prevalence, intensity and their impact on children’s health. Objectives: To evaluate the prevalence and intensity of STH infections and their association with nutritional status in a sample of Honduran children. Methodology: A cross-sectional study was done among school-age children residing in rural communities in Honduras, in 2011. Demographic data was obtained, hemoglobin and protein concentrations were determined in blood samples and STH infections investigated in single-stool samples by Kato-Katz. Anthropometric measurements were taken to calculate heightfor- age (HAZ), BMI-for-age (BAZ) and weight-for-age (WAZ) to determine stunting, thinness and underweight, respectively. Results: Among 320 children studied (48% girls, aged 7–14 years, mean 9.7661.4) an overall STH prevalence of 72.5% was found. Children .10 years of age were generally more infected than 7–10 year-olds (p = 0.015). Prevalence was 30%, 67% and 16% for Ascaris, Trichuris and hookworms, respectively. Moderate-to-heavy infections as well as polyparasitism were common among the infected children (36% and 44%, respectively). Polyparasitism was four times more likely to occur in children attending schools with absent or annual deworming schedules than in pupils attending schools deworming twice a year (p,0.001). Stunting was observed in 5.6% of children and it was associated with increasing age. Also, 2.2% of studied children were thin, 1.3% underweight and 2.2% had anemia. Moderate-to-heavy infections and polyparasitism were significantly associated with decreased values in WAZ and marginally associated with decreased values in HAZ. Conclusions: STH infections remain a public health concern in Honduras and despite current efforts were highly prevalent in the studied community. The role of multiparasite STH infections in undermining children’s nutritional status warrants more research.

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Many position stands and review papers have refuted the myths associated with resistance training (RT) in children and adolescents. With proper training methods, RT for children and adolescents can be relatively safe and improve overall health. The objective of this position paper and review is to highlight research and provide recommendations in aspects of RT that have not been extensively reported in the pediatric literature. In addition to the well-documented increases in muscular strength and endurance, RT has been used to improve function in pediatric patients with cystic fibrosis, cerebral palsy and burn victims. Increases in children’s muscular strength have been attributed primarily to neurological adaptations due to the disproportionately higher increase in muscle strength than in muscle size. Although most studies using anthropometric measures have not shown significant muscle hypertrophy in children, more sensitive measures such as magnetic resonance imaging and ultrasound have suggested hypertrophy may occur. There is no minimum age for RT for children. However the training and instruction must be appropriate for children and adolescents involving a proper warm-up, cool-down and an appropriate choice of exercises. It is recommended that low-to-moderate intensity resistance should be utilized 2-3 times per week on non-consecutive days, with 1-2 sets initially, progressing to 4 sets of 8-15 repetitions for 8-12 exercises. These exercises can include more advanced movements such as Olympic style lifting, plyometrics and balance training, which can enhance strength, power, co-ordination and balance. However specific guidelines for these more advanced techniques need to be established for youth. In conclusion, a RT program that is within a child’s or adolescent’s capacity, involves gradual progression under qualified instruction and supervision with appropriately sized equipment can involve more advanced or intense RT exercises which can lead to functional (i.e. muscular strength, endurance, power, balance and co-ordination) and health benefits.

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Affiliation: Augustin Zeba & Hélène Delisle : Département de nutrition, Faculté de médecine, Université de Montréal

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Indian marine engineers are renowned for employment globally due to their knowledge, skill and reliability. This praiseworthy status has been achieved mainly due to the systematic training imparted to marine engineering cadets. However, in an era of advancing technology, marine engineering training has to remain dynamic to imbibe latest technology as well as to meet the demands of the shipping industry. New subjects of studies have to be included in the curriculum in a timely manner taking into consideration the industry requirements and best practices in shipping. Technical competence of marine engineers also has to be subjected to changes depending upon the needs of the ever growing and over regulated shipping industry. Besides. certain soft skills are to be developed and improved amongst the marine engineers in order to alter or amend the personality traits leading to their career success.If timely corrective action is taken. Indian marine engineers can be in still greater demand for employment in global maritime field. In order to enhance the employability of our mmine engineers by improving their quality, a study of marine engineers in general and class IV marine engineers in particular was conducted based on three distinct surveys, viz., survey among senior marine engineers, survey among employers of marine engineers and survey of class IV marine engineers themselves.The surveys have been planned and questionnaires have been designed to focus the study of marine engineer officer class IV from the point of view of the three distinct groups of maritime personnels. As a result of this, the strength and weakness of class IV marine engineers are identified with regard to their performance on board ships, acquisition of necessary technical skills. employability and career success. The criteria of essential qualities of a marine engineer are classified as academic, technical, social, psychological. physical, mental, emergency responsive, communicative and leadership, and have been assessed for a practicing marine engineer by statistical analysis of data collected from surveys. These are assessed for class IV marine engineers from the point of view of senior marine engineers and employers separately. The Endings are delineated and graphically depicted in this thesis.Besides. six pertinent personality traits of a marine engineer viz. self esteem. learning style. decision making. motivation. team work and listening self inventory have been subjected to study and their correlation with career success have been established wherever possible. This is carried out to develop a theoretical framework to understand what leads a marine engineer to his career attainment. This enables the author to estimate the personality strengths and weaknesses of a serving marine engineer and eventually to deduce possible corrective measures or modifications in marine engineering training in India.Maritime training is largely based on International Conventions on Standard of Training. Certification and Watch keeping for Seafarers 1995. its associated Code and Merchant Shipping (STCW for Seafarers) Rules 1998. Further, Maritime Education, Training and Assessment (META) Manual was subjected to a critical scrutiny and relevant Endings of thc surveys arc superimposed on the existing rule requirement and curriculum. Views of senior marine engineers and executives of various shipping companies are taken into account before arriving at the revision of syllabus of marine engineering courses. Modifications in the pattern of workshop and sea service for graduate mechanical engineering trainees are recommended. Desirable age brackets of junior engineers and chief engineers. use of Training and Assessment Record book (TAR Book) during training etc. have also been evaluated.As a result of the pedagogic introspection of the existing system of marine engineering training in India. in this thesis, a revised pattern of workshop training of six months duration for graduate mechanical engineers. revised pattern of sea service training of one year duration and modified now diagram incorporating the above have been arrived at. Effects of various personality traits on career success have been established along with certain findings for improvement of desirable personality traits of marine engineers.

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Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

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This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

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This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

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Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

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Abstract Google and YouTube are quickly becoming the training resource of choice for the IT literate, especially in relation to computer based applications. Many businesses are addressing this training issue in a number of ways, some more successful than others. Find out what the IT services at the university are doing to adapt to this change and contribute to the discussion on how the approach could be improved. Before the talk you could have a look at the following; * One service that has been licenced is Lynda http://go.soton.ac.uk/lynda or lynda.com (note you have to enter www.southampton.ac.uk as the organisation if you don’t log in through the go.soton link) * The IT training team publish a portfolio of systems and courses at http://www.southampton.ac.uk/isolutions/computing/training/portfolio/index.php. * More and more internal systems are being supported through online guides such as http://go.soton.ac.uk/bgsg