859 resultados para disabilities in college students
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In 1995, a pioneering MD-PhD program was initiated in Brazil for the training of medical scientists in experimental sciences at the Federal University of Rio de Janeiro. The program’s aim was achieved with respect to publication of theses in the form of papers with international visibility and also in terms of fostering the scientific careers of the graduates. The expansion of this type of program is one of the strategies for improving the preparation of biomedical researchers in Brazil. A noteworthy absence of interest in carrying out clinical research limits the ability of young Brazilian physicians to solve biomedical problems. To understand the students’ views of science, we used qualitative and quantitative triangulation methods, as well as participant observation to evaluate the students’ concepts of science and common sense. Subjective aspects were clearly less evident in their concepts of science. There was a strong concern about "methodology", "truth" and "usefulness". "Intuition", "creativity" and "curiosity" were the least mentioned thematic categories. Students recognized the value of intuition when it appeared as an explicit option but they did not refer to it spontaneously. Common sense was associated with "consensus", "opinion" and ideas that "require scientific validation". Such observations indicate that MD-PhD students share with their senior academic colleagues the same reluctance to consider common sense as a valid adjunct for the solution of scientific problems. Overcoming this difficulty may be an important step toward stimulating the interest of physicians in pursuing experimental research.
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The purpose of the present study was first to determine what influences international students' perceptions of prejudice, and secondly to examine how perceptions of prejudice would affect international students' group identification. Variables such as stigma vulnerability and contact which have been previously linked with perceptions of prejudice and intergroup relations were re-examined (Berryman-Fink, 2006; Gilbert, 1998; Nesdale & Todd, 2000), while variables classically linked to prejudicial attitudes such as right-wing authoritarianism and openness to experience were explored in relation to perceptions of prejudice. Furthermore, the study examined how perceptions of prejudice might affect the students' identification choices, by testing two opposing models. The first model was based on the motivational nature of social identity theory (Tajfel & Turner, 1986) while the second model was based on the cognitive nature of self-categorization theory/ rejection-identification model (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987; Schmitt, Spears, & Branscombe,2003). It was hypothesized that stigma vulnerability, right-wing authoritarianism, openness to experience and contact would predict both personal and group perceptions of prejudice. It was also hypothesized that perceptions of prejudice would predict group identification. If the self-categorizationlrejection-identification model was supported, international students would identify with the international students. If the social mobility strategy was supported, international students would identify with the university students group. Participants were 98 international students who filled out questionnaires on the Brock University Psychology Department Website. The first hypothesis was supported. The combination of stigma vulnerability, right-wing authoritarianism, openness to experience and contact predicted both personal and group prejudice perceptions of international students. Furthermore, the analyses supported the self-categorizationlrejectionidentification model. International identification was predicted by the combination of personal and group prejudice perceptions of international students.
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In the last few decades, there have been significant changes in the way people with intellectual disabilities (ID) live in many countries around the world. Large isolated institutions have been replaced by community-based housing. This study examined the deinstitutionalization process in Ontario and it's effects on the lives of three individuals with ID. A case analysis approach was used allowing for in depth evaluation of the quality of life of these participants following their discharge with a focus on family involvement, community engagement, and choice making. A discrepancy analysis between the Essential Elements Plan (EEP), constructed when they were entering the community placement, and the current living arrangements was also done. The results of this study suggested that with community living comes improvements in family interactions, community engagement, and decision-making. However, these improvements were found to be minimal. Also, little discrepancy was found between the EEPs and their actual placements.
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This research offered children with disabilities the opportunity to express their voices in the description of their movement experiences. Three children aged 10-13 shared their experiences in school physical education and adapted physical activity. Observations of participants using interactive media activities in an adapted physical activity program were used to supplement interviews. The aim of this research was to discover how future professionals are prepared to design and implement physical activity and physical education programs for children with disabilities. A document analysis of Ontario university course calendars in the fields of physical education and kinesiology, disability studies, and teacher education was utilized. Data from each data context underwent four levels of reduction: 1) content, 2) categorical, 3) thematic, and 4) indigenous typologies. Findings are presented at each level leading to the presentation of indigenous typologies. Typologies of Forbidden-ness and Dichotomous Thinking were identified in the research.
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The deinstitutionalization of individuals with developmental disabilities to community-based residential services is a pervasive international trend. Although controversial, the remaining three institutions in Ontario were closed in March of 2009. Since these closures, there has been limited research on the effects of deinstitutionalization. The following retrospective study evaluated family perceptions of the impact of deinstitutionalization on the quality of life of fifty-five former residents one year post-closure utilizing a survey design and conceptual quality of life framework. The methods used to analyze the survey results included descriptive statistical analyses and thematic analyses. Overall, the results suggest that most family members are satisfied with community placement and supports, and report an improved quality of life for their family member with a developmental disability. These findings were consistent with previously published studies demonstrating the short-term and long-term benefits of community living for most individuals with developmental disabilities and their families.
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This study attempted to manipulate self-presentational efficacy to examine the effect on social anxiety, social physique anxiety, drive for muscularity, and maximal strength performance during a one-repetition maximum (1-RM) chest press and leg press test. Ninety-nine college men with a minimum of six months of previous weight training experience were randomly assigned to complete a 1-RM protocol with either a muscular male trainer described as an expert or a lean male trainer described as a novice. Participants completed measures of self-presentation and body image prior to meeting their respective trainer, and following the completion of the 1-RM tests. Although the self-presentational efficacy manipulation was not successful, the trainers were perceived significantly differently on musculature and expertise. The group with the muscular, expert trainer reported higher social anxiety and attained higher 1-RM scores for the chest and leg press. Thus, trainer characteristics can affect strength performance and self-presentational concerns in this population.
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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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Resumen tomado de la publicaci??n. Resumen tambi??n en ingl??s
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Resumen tomado de la publicaci??n
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This study examines the effects in university students of a psycho-educational program in full awareness (mindfulness) on certain personality variables. A quasi-experimental (group comparison) design with pretest and postest measurements was employed in an experimental (n = 26) and a control group (n = 27). Barratt impulsiveness Scale (BiS- 11), Acceptance and Action Questionnaire (AAQ), Social Avoidance and Distress Scale (SAD), and the Profile of Mood States (POMS) were applied to experimental and control groups. The results show statistically significant changes in impulsivity variables, experiential avoidance, social avoidance, social anxiety, tension and fatigue when comparing the posttest mean scores of the groups.
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The present investigation tries to establish the descriptive profile of the academic stress of the students of the masters in education and to identify which sociodemographic and situational variables play a modulator role. This investigation is based on the Person-Surroundings Research Program and the systemical cognitive model of academic stress. The study can be characterized as transectional, correlational and non experimental. The collection of the information was made through the SISCO inventory of Academic Stress which was applied to 152 students. The main results suggest that 95% of the master students report having felt academic stress a few times but with medium-high intensity. Variables gender, civil state, attending masters and institutional support of the attending masters act as modulators in academic stress.
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The object of this study is to identify the learning styles (LS) used by the students of the subject of physiology of the exercise of the program of Physiotherapy, with the purpose of establishing a direct relationship later on between the learning styles and the possible pedagogic strategies that but they favor the compression of the physiology of the exercise 48 subject of second and third year of career they were interviewed through the instrument standardized compound number (CHAEA). This study carried out an analysis descriptive and of typical deviation of the data. They were differences statistically significant in the styles of active and reflexive learning, in front of the Theoretical and pragmatic styles what puts in evidence the necessity to generate pedagogic strategies inside the subject that this chord with the tendency of the active and reflexive learning of the students.