How to improve the formal analytic reasoning and scientific motivation in the intellectual training of medical students

A review article of the The New England Journal of Medicine refers that almost a century ago, Abraham Flexner, a research scholar at the Carnegie Foundation for the Advancement of Teaching, undertook an assessment of medical education in 155 medical schools in operation in the United States and Canada. Flexner’s report emphasized the nonscientific approach of American medical schools to preparation for the profession, which contrasted with the university-based system of medical education in Germany. At the core of Flexner’s view was the notion that formal analytic reasoning, the kind of thinking integral to the natural sciences, should hold pride of place in the intellectual training of physicians. This idea was pioneered at Harvard University, the University of Michigan, and the University of Pennsylvania in the 1880s, but was most fully expressed in the educational program at Johns Hopkins University, which Flexner regarded as the ideal for medical education. (...)

Citation auctions as a method to improve selection of scientific papers

This paper describes the basis of citation auctions as a new approach to selecting scientific papers for publication. Our main idea is to use an auction for selecting papers for publication through - differently from the state of the art - bids that consist of the number of citations that a scientist expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper's content to judge the quality of its contribution. Additionally, the method will not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives. Sample analyses of the number of citations collected in papers published in years 1999-2004 for one journal, and in years 2003-2005 for a series of conferences (in a totally different discipline), via Google scholar, are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach

Can SMS Technology Improve Low Take-up of Social Benefits?

Low take up of stigma-free social benefits is often blamed on information asymmetries or administrative barriers. There is limited evidence on which of these potential channels is more salient in which contexts. We designed and implemented a randomized controlled trial to assess the extent to which informational barriers are responsible for the prevalent low take-up of government benefits among Colombian conflict-driven internal refugees. We provide timely information on benefits eligibility via SMS to a random half of the displaced household that migrated to Bogot´a over a 6-month period. We show that improving information increases benefits’ take up. However, the effect is small and only true for certain type of benefits. Hence, consistent with previous experimental literature, the availability of timely information explains only part of the low-take up rates and the role of administrative barriers and bureaucratic processes should be tackled to increase the well-being of internal refugees in Colombia.

Improve with pencil-video. 'Mejorar con lápiz-vídeo'.

Falta el vídeo

Building Professional Capacity Aiming to Improve the Educational Position of Migrant Children : a reflection on the Sirius network activities

Resumen basado en el de la publicaci??n

Intelligent agents to improve adaptivity in a web-based learning environment

En esta tesis se propone el uso de agentes inteligentes en entornos de aprendizaje en línea con el fin de mejorar la asistencia y motivación del estudiante a través de contenidos personalizados que tienen en cuenta el estilo de aprendizaje del estudiante y su nivel de conocimiento. Los agentes propuestos se desempeñan como asistentes personales que ayudan al estudiante a llevar a cabo las actividades de aprendizaje midiendo su progreso y motivación. El entorno de agentes se construye a través de una arquitectura multiagente llamada MASPLANG diseñada para dar soporte adaptativo (presentación y navegación adaptativa) a un sistema hipermedia educativo desarrollado en la Universitat de Girona para impartir educación virtual a través del web. Un aspecto importante de esta propuesta es la habilidad de construir un modelo de estudiante híbrido que comienza con un modelo estereotípico del estudiante basado en estilos de aprendizaje y se modifica gradualmente a medida que el estudiante interactúa con el sistema (gustos subjetivos). Dentro del contexto de esta tesis, el aprendizaje se define como el proceso interno que, bajo factores de cambio resulta en la adquisición de la representación interna de un conocimiento o de una actitud. Este proceso interno no se puede medir directamente sino a través de demostraciones observables externas que constituyen el comportamiento relacionado con el objeto de conocimiento. Finalmente, este cambio es el resultado de la experiencia o entrenamiento y tiene una durabilidad que depende de factores como la motivación y el compromiso. El MASPLANG está compuesto por dos niveles de agentes: los intermediarios llamados IA (agentes de información) que están en el nivel inferior y los de Interfaz llamados PDA (agentes asistentes) que están en el nivel superior. Los agentes asistentes atienden a los estudiantes cuando trabajan con el material didáctico de un curso o una lección de aprendizaje. Esta asistencia consiste en la recolección y análisis de las acciones de los estudiantes para ofrecer contenidos personalizados y en la motivación del estudiante durante el aprendizaje mediante el ofrecimiento de contenidos de retroalimentación, ejercicios adaptados al nivel de conocimiento y mensajes, a través de interfaces de usuario animadas y atractivas. Los agentes de información se encargan del mantenimiento de los modelos pedagógico y del dominio y son los que están en completa interacción con las bases de datos del sistema (compendio de actividades del estudiante y modelo del dominio). El escenario de funcionamiento del MASPLANG está definido por el tipo de usuarios y el tipo de contenidos que ofrece. Como su entorno es un sistema hipermedia educativo, los usuarios se clasifican en profesores quienes definen y preparan los contenidos para el aprendizaje adaptativo, y los estudiantes quienes llevan a cabo las actividades de aprendizaje de forma personalizada. El perfil de aprendizaje inicial del estudiante se captura a través de la evaluación del cuestionario ILS (herramienta de diagnóstico del modelo FSLSM de estilos de aprendizaje adoptado para este estudio) que se asigna al estudiante en su primera interacción con el sistema. Este cuestionario consiste en un conjunto de preguntas de naturaleza sicológica cuyo objetivo es determinar los deseos, hábitos y reacciones del estudiante que orientarán la personalización de los contenidos y del entorno de aprendizaje. El modelo del estudiante se construye entonces teniendo en cuenta este perfil de aprendizaje y el nivel de conocimiento obtenido mediante el análisis de las acciones del estudiante en el entorno.

A proposed plan for using Dr. Marie Carbo's tape-recorded books to improve word recognition skills in children with cochlear implants

This paper studies the effectiveness of the recorded books and teaching method developed by Dr. Marie Carbo in the aural habilitation of pre-lingual deaf children with cochlear implants.

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador

This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador.

Modeling and Mapping Golden-winged Warbler Abundance to Improve Regional Conservation Strategies

Conservation planning requires identifying pertinent habitat factors and locating geographic locations where land management may improve habitat conditions for high priority species. I derived habitat models and mapped predicted abundance for the Golden-winged Warbler (Vermivora chrysoptera), a species of high conservation concern, using bird counts, environmental variables, and hierarchical models applied at multiple spatial scales. My aim was to understand habitat associations at multiple spatial scales and create a predictive abundance map for purposes of conservation planning for the Golden-winged Warbler. My models indicated a substantial influence of landscape conditions, including strong positive associations with total forest composition within the landscape. However, many of the associations I observed were counter to reported associations at finer spatial extents; for instance, I found Golden-winged Warblers negatively associated with several measures of edge habitat. No single spatial scale dominated, indicating that this species is responding to factors at multiple spatial scales. I found Golden-winged Warbler abundance was negatively related with Blue-winged Warbler (Vermivora cyanoptera) abundance. I also observed a north-south spatial trend suggestive of a regional climate effect that was not previously noted for this species. The map of predicted abundance indicated a large area of concentrated abundance in west-central Wisconsin, with smaller areas of high abundance along the northern periphery of the Prairie Hardwood Transition. This map of predicted abundance compared favorably with independent evaluation data sets and can thus be used to inform regional planning efforts devoted to conserving this species.

Can wavelets improve the representation of forecast error covariances in variational data assimilation?

Two wavelet-based control variable transform schemes are described and are used to model some important features of forecast error statistics for use in variational data assimilation. The first is a conventional wavelet scheme and the other is an approximation of it. Their ability to capture the position and scale-dependent aspects of covariance structures is tested in a two-dimensional latitude-height context. This is done by comparing the covariance structures implied by the wavelet schemes with those found from the explicit forecast error covariance matrix, and with a non-wavelet- based covariance scheme used currently in an operational assimilation scheme. Qualitatively, the wavelet-based schemes show potential at modeling forecast error statistics well without giving preference to either position or scale-dependent aspects. The degree of spectral representation can be controlled by changing the number of spectral bands in the schemes, and the least number of bands that achieves adequate results is found for the model domain used. Evidence is found of a trade-off between the localization of features in positional and spectral spaces when the number of bands is changed. By examining implied covariance diagnostics, the wavelet-based schemes are found, on the whole, to give results that are closer to diagnostics found from the explicit matrix than from the nonwavelet scheme. Even though the nature of the covariances has the right qualities in spectral space, variances are found to be too low at some wavenumbers and vertical correlation length scales are found to be too long at most scales. The wavelet schemes are found to be good at resolving variations in position and scale-dependent horizontal length scales, although the length scales reproduced are usually too short. The second of the wavelet-based schemes is often found to be better than the first in some important respects, but, unlike the first, it has no exact inverse transform.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.

Can knowledge of the state of the stratosphere be used to improve statistical forecasts of the troposphere?

Recent analysis of the Arctic Oscillation (AO) in the stratosphere and troposphere has suggested that predictability of the state of the tropospheric AO may be obtained from the state of the stratospheric AO. However, much of this research has been of a purely qualitative nature. We present a more thorough statistical analysis of a long AO amplitude dataset which seeks to establish the magnitude of such a link. A relationship between the AO in the lower stratosphere and on the 1000 hPa surface on a 10-45 day time-scale is revealed. The relationship accounts for 5% of the variance of the 1000 hPa time series at its peak value and is significant at the 5% level. Over a similar time-scale the 1000 hPa time series accounts for 1% of itself and is not significant at the 5% level. Further investigation of the relationship reveals that it is only present during the winter season and in particular during February and March. It is also demonstrated that using stratospheric AO amplitude data as a predictor in a simple statistical model results in a gain of skill of 5% over a troposphere-only statistical model. This gain in skill is not repeated if an unrelated time series is included as a predictor in the model. Copyright © 2003 Royal Meteorological Society

The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.