597 resultados para Student attributes
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2e Prix du concours d'initiation à la recherche organisé par le Regroupement Droit et Changements. L'auteure était étudiante au baccalauréat en droit à l'Université McGill lors de la rédaction de cet article.
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La présente recherche porte sur l’existence d’un décalage entre la création artistique dans l’art contemporain et l’enseignement des arts plastiques au primaire au Québec. Plus précisément, après avoir observée l’importance de l’intention artistique dans les mécanismes de création des artistes en art contemporain, cette recherche étudie la place que les enseignants spécialisés en arts plastiques lui accordent dans leur enseignement. En partant de la question de recherche, « Au Québec, les enseignants spécialisés en arts plastiques au primaire entretiennent-ils ou non le décalage entre la création artistique contemporaine et l’enseignement des arts, en prenant ou non en compte le développement d’intention artistique chez les élèves lorsque ceux-ci réalisent des créations personnelles dans les cours d’arts plastiques? », ce mémoire est constitué de plusieurs ensembles d’analyses. La distinction des principaux paradigmes artistiques dans cette recherche définit des attributs pour comprendre respectivement leurs impacts sur l’enseignement des arts et pour saisir les différentes représentations que les enseignants spécialisés en arts plastiques au primaire ont de la création artistique, et plus particulièrement dans le paradigme artistique contemporain. Cette distinction permet de confronter deux représentations de la dynamique de création : celle présente dans la notion de processus de création et celle présente dans la notion d’intention artistique. Ainsi, les entretiens semi-dirigés de douze enseignants spécialistes en arts plastiques dans des écoles primaires au Québec renforcent l’existence du décalage, mais aussi nous renseigne sur la faiblesse des acteurs à définir les enjeux actuels de la création artistique. De plus, cette recherche démontre une absence dans le Programme de formation de l’école québécoise (PFEQ) des mécanismes de pensée de la création observée dans le paradigme artistique contemporain.
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Université de Montréal implemented an interprofessional education (IPE) curriculum on collaborative practice in a large cohort of students (>1,100) from 10 health sciences and psychosocial sciences training programs. It is made up of three one-credit undergraduate courses (CSS1900, CSS2900, CSS3900) spanning the first 3 years of training. The course content and activities aim for development of the six competency domains identified by the Canadian Interprofessional Health Collaborative. This paper describes the IPE curriculum and highlights the features contributing to its success and originality. Among main success key factors were: administrative cooperation among participating faculties, educators eager to develop innovative approaches, extensive use of clinical situations conducive to knowledge and skill application, strong logistic support, close cooperation with health care delivery organizations, and partnership between clinicians and patients. A distinguishing feature of this IPE curriculum is the concept of partnership in care between the patient and caregivers. Patients’ representatives were involved in course planning, and patients were trained to become patients-as-trainers (PT) and cofacilitate interprofessional discussion workshops. They give feed- back to students regarding integration and application of the patient partnership concept from a patient’s point of view. Lire l'article/Read the article : http://openurl.ingenta.com/content?genre=article&issn=0090-7421&volume=42&issue=4&spage=97E&epage=106E
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The study was carried out with the broad objective to understand the quality attributes of Kerala as a global tourism destination. It also sheds some light on the nature of international travel market for Kerala in terms of activities , benefit sought , country and trip profile. For understanding the difference in level of tourists perception , the study also tried to compare overall trip satisfaction and impression with destination for different tourists groups categorized into country of origin and various socio-demographic groups.
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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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Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.
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With this document, we provide a compilation of in-depth discussions on some of the most current security issues in distributed systems. The six contributions have been collected and presented at the 1st Kassel Student Workshop on Security in Distributed Systems (KaSWoSDS’08). We are pleased to present a collection of papers not only shedding light on the theoretical aspects of their topics, but also being accompanied with elaborate practical examples. In Chapter 1, Stephan Opfer discusses Viruses, one of the oldest threats to system security. For years there has been an arms race between virus producers and anti-virus software providers, with no end in sight. Stefan Triller demonstrates how malicious code can be injected in a target process using a buffer overflow in Chapter 2. Websites usually store their data and user information in data bases. Like buffer overflows, the possibilities of performing SQL injection attacks targeting such data bases are left open by unwary programmers. Stephan Scheuermann gives us a deeper insight into the mechanisms behind such attacks in Chapter 3. Cross-site scripting (XSS) is a method to insert malicious code into websites viewed by other users. Michael Blumenstein explains this issue in Chapter 4. Code can be injected in other websites via XSS attacks in order to spy out data of internet users, spoofing subsumes all methods that directly involve taking on a false identity. In Chapter 5, Till Amma shows us different ways how this can be done and how it is prevented. Last but not least, cryptographic methods are used to encode confidential data in a way that even if it got in the wrong hands, the culprits cannot decode it. Over the centuries, many different ciphers have been developed, applied, and finally broken. Ilhan Glogic sketches this history in Chapter 6.
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Organic food is increasingly available in the conventional food retail, where organic products are offered alongside with various other types of products and compete mainly with conventional and the so-called conventional-plus products. The latter are conventional products displaying particular quality attributes on the product packaging, such as ‘no artificial additives’, or ‘from animal welfare husbandry’. Often, these quality attributes also apply to organic products. Occasional organic consumers might prefer such conventional-plus alternatives that are perceived to be ‘between’ organic and conventional products. The overall objective of this PhD thesis was to provide information about the segment of occasional organic consumers. In particular, the thesis focussed on consumer perceptions and attitudes towards the quality of, and preferences for, organic, conventional and conventional-plus products in two countries: Germany and Switzerland. To achieve these objectives, qualitative and quantitative consumer research was combined in order to explore occasional organic consumers’ perceptions and attitudes as well as to observe their preferences and buying behaviour regarding different types of food products: organic, conventional and conventional-plus products. The qualitative research showed that, depending on single criteria, organic production was both positively as well as negatively assessed by consumers. Consumer perception of organic food was found to be highly selective and primarily focussed on the final stage of the particular production process. A major problem is that consumers are still mostly unfamiliar with factors associated with organic production, have a lack of confidence, and often confuse organic with conventional products. Besides this, consumer expectations of organic products are different from the expectations of conventional products. The quantitative research revealed that attitudes strongly determine consumers’ preferences for organic, conventional and conventional-plus products. Consumer attitudes tended to differ more between organic and conventional choices rather than conventional-plus and conventional choices. Furthermore, occasional organic consumers are heterogeneous in their preferences. They can be grouped into two segments: the consumers in one segment were less price sensitive and preferred organic products. The consumers in the other segment were more price sensitive and rather preferred conventional-plus or conventional products. To conclude, given the selective and subjective nature of consumer perception and the strong focus of consumer perception on the final stage of the food production process, specific additional values of organic farming should be communicated in clear and catchy messages. At the same time, these messages should be particularly focussed on the final stage of organic food production. The communication of specific added values in relation with organic products to improve the perceived price-performance-ratio is important since conventional-plus products represent an interesting alternative particularly for price sensitive occasional organic consumers. Besides this, it is important to strengthen affirmative consumer attitudes towards organic production. Therefore, policy support should emphasise on long-term communication campaigns and education programmes to increase the consumer awareness and knowledge of organic food and farming. Since consumers expect that organic food is regionally or at least domestically produced while they less accept organic imports, policy support of domestic and regional producers is a crucial measure to fill the current gap between the increasing consumer demand of organic food and the stagnation of the domestic and regional organic food supply.
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Aquest quadern forma part de la Guia per a l'adaptació a l'espai europeu d'educació superior