51 resultados para Educational Assessment, Evaluation, and Research

em CentAUR: Central Archive University of Reading - UK


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This study examines if and how gender relates to research evaluation via panel assessment and journal ratings lists. Using data from UK business schools we find no evidence that the proportion of women in a submission for panel assessment affected the score received by the submitting institution. However, we do find that women on average receive lower scores according to some journal ratings lists. There are important differences in the rated quality of journals that men and women publish in across the sub-disciplines with men publishing significantly more research in the highest rated accountancy, information management and strategy journals. In addition, women who are able to utilise networks to co-author with individuals outside their institution are able to publish in higher-rated journals, although the same is not true for men; women who are attributed with “individual staff circumstances” (e.g. maternity leave or part-time working) have lower scores according to journal ratings lists.

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A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.

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The introduction of metrics, league tables, performance targets, research assessment exercises and a range of other pressures placed by society, funding bodies and employers on scholars, teachers and students have resulted in diminished value being placed on the essential ethical criterion of truth. The impact of reduced valuation for truth has a huge impact on the standing of science and not least horticultural science in the eyes of the general public at a time when this should be a primary concern. This contribution discusses examples of the impact of diminished valuation of truth, the causes of this phenomenon, the results that come from this situation and remedies that are needed.

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This paper explores methodological issues related to research into second language listening strategies. We argue that a number of central questions regarding research methodology in this line of enquiry are underexamined, and we engage in the discussion of three key methodological questions: (1) To what extent is a verbal report a valid and reliable way of eliciting information about strategies? (2) Should we control for learners' level of linguistic knowledge when examining their listening strategy use? and (3) What are the problems surrounding the analysis of data gained through verbal reports? We discuss each of these three methodological issues within the framework of a research project investigating listening strategies deployed by learners of French in secondary schools in England. Implications from these findings for future research are discussed.

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Although in several EU Member States many public interventions have been running for the prevention and/or management of obesity and other nutrition-related health conditions, few have yet been formally evaluated. The multidisciplinary team of the EATWELL project will gather benchmark data on healthy eating interventions in EU Member States and review existing information on the effectiveness of interventions using a three-stage procedure (i) Assessment of the intervention's impact on consumer attitudes, consumer behaviour and diets; (ii) The impact of the change in diets on obesity and health and (iii) The value attached by society to these changes, measured in life years gained, cost savings and quality-adjusted life years. Where evaluations have been inadequate, EATWELL will gather secondary data and analyse them with a multidisciplinary approach incorporating models from the psychology and economics disciplines. Particular attention will be paid to lessons that can be learned from private sector that are transferable to the healthy eating campaigns in the public sector. Through consumer surveys and workshops with other stakeholders, EATWELL will assess the acceptability of the range of potential interventions. Armed with scientific quantitative evaluations of policy interventions and their acceptability to stakeholders, EATWELL expects to recommend more appropriate interventions for Member States and the EU, providing a one-stop guide to methods and measures in interventions evaluation, and outline data collection priorities for the future.

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An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km. The 15-year integrations were forced from reanalyses and observed sea surface temperature and sea ice (global model from sea surface only). The observational reference is based on 6400 rain gauge records (10–50 stations per grid box). Evaluation statistics encompass mean precipitation, wet-day frequency, precipitation intensity, and quantiles of the frequency distribution. For mean precipitation, the models reproduce the characteristics of the annual cycle and the spatial distribution. The domain mean bias varies between −23% and +3% in winter and between −27% and −5% in summer. Larger errors are found for other statistics. In summer, all models underestimate precipitation intensity (by 16–42%) and there is a too low frequency of heavy events. This bias reflects too dry summer mean conditions in three of the models, while it is partly compensated by too many low-intensity events in the other two models. Similar intermodel differences are found for other European subregions. Interestingly, the model errors are very similar between the two models with the same dynamical core (but different parameterizations) and they differ considerably between the two models with similar parameterizations (but different dynamics). Despite considerable biases, the models reproduce prominent mesoscale features of heavy precipitation, which is a promising result for their use in climate change downscaling over complex topography.

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Specific traditional plate count method and real-time PCR systems based on SYBR Green I and TaqMan technologies using a specific primer pair and probe for amplification of iap-gene were used for quantitative assay of Listeria monocytogenes in seven decimal serial dilution series of nutrient broth and milk samples containing 1.58 to 1.58×107 cfu /ml and the real-time PCR methods were compared with the plate count method with respect to accuracy and sensitivity. In this study, the plate count method was performed using surface-plating of 0.1 ml of each sample on Palcam Agar. The lowest detectable level for this method was 1.58×10 cfu/ml for both nutrient broth and milk samples. Using purified DNA as a template for generation of standard curves, as few as four copies of the iap-gene could be detected per reaction with both real-time PCR assays, indicating that they were highly sensitive. When these real-time PCR assays were applied to quantification of L. monocytogenes in decimal serial dilution series of nutrient broth and milk samples, 3.16×10 to 3.16×105 copies per reaction (equals to 1.58×103 to 1.58×107 cfu/ml L. monocytogenes) were detectable. As logarithmic cycles, for Plate Count and both molecular assays, the quantitative results of the detectable steps were similar to the inoculation levels.

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A manageable, relatively inexpensive model was constructed to predict the loss of nitrogen and phosphorus from a complex catchment to its drainage system. The model used an export coefficient approach, calculating the total nitrogen (N) and total phosphorus (P) load delivered annually to a water body as the sum of the individual loads exported from each nutrient source in its catchment. The export coefficient modelling approach permits scaling up from plot-scale experiments to the catchment scale, allowing application of findings from field experimental studies at a suitable scale for catchment management. The catchment of the River Windrush, a tributary of the River Thames, UK, was selected as the initial study site. The Windrush model predicted nitrogen and phosphorus loading within 2% of observed total nitrogen load and 0.5% of observed total phosphorus load in 1989. The export coefficient modelling approach was then validated by application in a second research basin, the catchment of Slapton Ley, south Devon, which has markedly different catchment hydrology and land use. The Slapton model was calibrated within 2% of observed total nitrogen load and 2.5% of observed total phosphorus load in 1986. Both models proved sensitive to the impact of temporal changes in land use and management on water quality in both catchments, and were therefore used to evaluate the potential impact of proposed pollution control strategies on the nutrient loading delivered to the River Windrush and Slapton Ley

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To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor–outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier–Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate high-resolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios. Copyright © 2010 Royal Meteorological Society

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The sustainable intelligent building is a building that has the best combination of environmental, social, economic and technical values. And its sustainability assessment is related with system engineering methods and multi-criteria decision-making. Therefore firstly, the wireless monitoring system of sustainable parameters for intelligent buildings is achieved; secondly, the indicators and key issues based on the “whole life circle” for sustainability of intelligent buildings are researched; thirdly, the sustainable assessment model identified on the structure entropy and fuzzy analytic hierarchy process is proposed.

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This case study reports on the development of a bespoke mobile recording app for collating records of biodiversity sightings on a University campus. This innovative project was achieved through a multi-disciplinary partnership of staff and students. It is hoped that the app itself will benefit lecturers by streamlining data collection during teaching and learning activities, whilst engaging students and highlighting the wealth of diversity available on campus

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Previous assessments of the impacts of climate change on heat-related mortality use the "delta method" to create temperature projection time series that are applied to temperature-mortality models to estimate future mortality impacts. The delta method means that climate model bias in the modelled present does not influence the temperature projection time series and impacts. However, the delta method assumes that climate change will result only in a change in the mean temperature but there is evidence that there will also be changes in the variability of temperature with climate change. The aim of this paper is to demonstrate the importance of considering changes in temperature variability with climate change in impacts assessments of future heat-related mortality. We investigate future heatrelated mortality impacts in six cities (Boston, Budapest, Dallas, Lisbon, London and Sydney) by applying temperature projections from the UK Meteorological Office HadCM3 climate model to the temperature-mortality models constructed and validated in Part 1. We investigate the impacts for four cases based on various combinations of mean and variability changes in temperature with climate change. The results demonstrate that higher mortality is attributed to increases in the mean and variability of temperature with climate change rather than with the change in mean temperature alone. This has implications for interpreting existing impacts estimates that have used the delta method. We present a novel method for the creation of temperature projection time series that includes changes in the mean and variability of temperature with climate change and is not influenced by climate model bias in the modelled present. The method should be useful for future impacts assessments. Few studies consider the implications that the limitations of the climate model may have on the heatrelated mortality impacts. Here, we demonstrate the importance of considering this by conducting an evaluation of the daily and extreme temperatures from HadCM3, which demonstrates that the estimates of future heat-related mortality for Dallas and Lisbon may be overestimated due to positive climate model bias. Likewise, estimates for Boston and London may be underestimated due to negative climate model bias. Finally, we briefly consider uncertainties in the impacts associated with greenhouse gas emissions and acclimatisation. The uncertainties in the mortality impacts due to different emissions scenarios of greenhouse gases in the future varied considerably by location. Allowing for acclimatisation to an extra 2°C in mean temperatures reduced future heat-related mortality by approximately half that of no acclimatisation in each city.