5 resultados para Law, John: After method : mess in social science research
em Universidad de Alicante
Resumo:
Los arquitectos y urbanistas tienen una larga tradición en el aprendizaje de las herramientas de las ciencias sociales, especialmente las que les permiten analizar y describir mejor los entornos y las personas para las que trabajan. Esto ha llevado a los arquitectos a desarrollar mejores herramientas de observación y descripción del ámbito social y no sólo el material. Sin embargo, la mayoría de las veces este acercamiento interdisciplinar ha identificado las ciencias sociales, especialmente la antropología, con la etnografía. Este artículo parte de la crítica a esta identificación hecha por el antropólogo Tim Ingold y se centra en lo que él propone como el método central de la antropología, la observación participante. Para después revisar varias propuestas actuales de científicos sociales que tratan de desarrollar una disciplina no representacional y orientada al futuro, un objetivo más cercano al de la arquitectura. El artículo intenta imaginar cómo esta práctica transdisciplinar podría desarrollarse.
Resumo:
El objetivo de este estudio fue realizar un análisis bibliométrico de la producción científica publicada entre el año 2000 y 2011 sobre familia y discapacidad intelectual, con la finalidad de ofrecer una descripción global del estado actual de la investigación en dicho ámbito. La base de datos empleada ha sido Social Science Citation lndex extrayendo una muestra de 952 artículos. Fueron analizados el año de publicación, las revistas, el índice de autoría, las temáticas, el tipo de investigación, las citas y el idioma. A por1ir de los resultados, se observó una periodicidad estable en cuanto a los indicadores de producción y una identificación de temáticas que mantienen una relación con la realidad social y las necesidades que envuelve este campo de conocimiento. El presente trabajo permite conocer la evolución que ha seguido el estudio de la familia y la discapacidad intelectual en el periodo temporal indicado y ofrece un amplio conocimiento sobre las investigaciones realizadas al respecto.
Resumo:
Este documento es un artículo inédito que ha sido aceptado para su publicación. Como un servicio a sus autores y lectores, Alternativas. Cuadernos de trabajo social proporciona online esta edición preliminar. El manuscrito puede sufrir alteraciones tras la edición y corrección de pruebas, antes de su publicación definitiva. Los posibles cambios no afectarán en ningún caso a la información contenida en esta hoja, ni a lo esencial del contenido del artículo.
Resumo:
The adaptation of the Spanish University to the European Higher Education Area (EEES in Spanish) demands the integration of new tools and skills that would make the teaching- learning process easier. This adaptation involves a change in the evaluation methods, which goes from a system where the student was evaluated with a final exam, to a new system where we include a continuous evaluation in which the final exam may represent at most 50% in the vast majority of the Universities. Devising a new and fair continuous evaluation system is not an easy task to do. That would mean a student’s’ learning process follow-up by the teachers, and as a consequence an additional workload on existing staff resources. Traditionally, the continuous evaluation is associated with the daily work of the student and a collection of the different marks partly or entirely based on the work they do during the academic year. Now, small groups of students and an attendance control are important aspects to take into account in order to get an adequate assessment of the students. However, most of the university degrees have groups with more than 70 students, and the attendance control is a complicated task to perform, mostly because it consumes significant amounts of staff time. Another problem found is that the attendance control would encourage not-interested students to be present at class, which might cause some troubles to their classmates. After a two year experience in the development of a continuous assessment in Statistics subjects in Social Science degrees, we think that individual and periodical tasks are the best way to assess results. These tasks or examinations must be done in classroom during regular lessons, so we need an efficient system to put together different and personal questions in order to prevent students from cheating. In this paper we provide an efficient and effective way to elaborate random examination papers by using Sweave, a tool that generates data, graphics and statistical calculus from the software R and shows results in PDF documents created by Latex. In this way, we will be able to design an exam template which could be compiled in order to generate as many PDF documents as it is required, and at the same time, solutions are provided to easily correct them.
Resumo:
Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.