950 resultados para Education, Urban


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OBJECTIVE. The purpose of this study was to examine occupational therapists' use and perceptions of written education materials for clients and the factors that therapists consider before distributing written materials to clients This study also aimed to determine whether use and perceptions of these materials differed for older clients METHOD. A random sample of 50 occupational therapists from Queensland, Australia, working in adult physical disabilities settings was surveyed with a structured questionnaire Data were analyzed descriptively and with nonparametric statistics RESULTS. Of 49 participants who used written materials, 54% had given them to more than halt of their last 10 clients, regardless of the clients' age Written materials, most often information sheets developed by the participants themselves; handwritten notes; and pamphlets were principally used to reinforce verbal information. Clients' cognitive abilities, primary language, communication skills, vision, and level of education most often were considered before distributing written materials Although participants generally were positive about the content and effectiveness of materials, ratings were significantly less positive related to older clients CONCLUSION. Client education was a core treatment modality for participants in this study, with written media most commonly being used to supplement verbal education Because participants were least positive about the effectiveness of written materials for older clients, further development of materials for this audience may be indicated.

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Today's challenge to medical educators is to provide continuing education that supports excellence in clinical practice while finding new approaches to make learning more stimulating, motivating, and entertaining. At our hospital we are experimenting with innovative teaching techniques, incorporating games and debate, which encapsulate core concepts of the theory of adult learning: active participation by learners, application of knowledge, informal presentation, and feedback(1).

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The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.