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Explicit Information (explicit + information)
Selected AbstractsThe Role of Explicit Information in Instructed SLA: An On-Line Study with Processing Instruction and German Accusative Case InflectionsDIE UNTERRICHTSPRAXIS/TEACHING GERMAN, Issue 1 2009Hillah Culman The present study reports the findings of an experiment on the effects of explicit information on the learning of German case markings. Fifty-nine learners of first- and second-year German received computer-based processing instruction on German accusative case marking and word order. These learners were divided into two groups: one received explicit information on the nature and form of case marking in German prior to the treatment, and one group did not. We measured the effects of explicit information by tracking correct responses on the computer as participants made their way through the activities. Analyses revealed that explicit information had an effect: those who received explicit information began to correctly respond to stimulus sentences (i.e., began to correctly indicate who did what to whom) sooner than those who did not. These results contradict previous research and suggest a hidden role for explicit information within processing instruction. [source] Quantifying spatial classification uncertainties of the historical Wisconsin landscape (USA)ECOGRAPHY, Issue 2 2005Janine Bolliger Landscape feature can be classified by creating categories based on aggregation of spatially explicit information. However, many landscape features appear continuous rather than discrete. The aggregation process likely involves loss of information and introduces a variety of uncertainties whose degree and extent may differ spatially. Since landscape classifications have found wide application in e.g. natural resource policies or ecological research, assessments of spatial classification uncertainties are required. We present a quantitative framework to identify the degree of landscape continuity (fuzziness) and structure (categorization) based on fuzzy classification and offer measures to quantify uncertainties originating from aggregating features into categories. Fuzzy classification is a non-hierarchical, quantitative method of assessing class definitions using degrees of association between features and class. This results in classes which are well defined and compositionally distinct, as well as classes which are less clearly defined but which, to various degrees, share characteristics with some or all classes. The spatial variation in the degree of class definition on the landscape is used to assess classification uncertainties. The two aspects of uncertainty investigated are the degree of association of a feature with the overall class definitions (membership diffusion), and the class-specific degree of association of each pixel on the landscape with each class (membership saturation). Three classification scenarios, one fuzzy and one discrete, of the historical landscape of Wisconsin (USA) were compared for spatial classification uncertainties. Membership diffusion is highest in topographically heterogeneous environments, or areas characterized by many species occupying similar ecological niches. Classification uncertainties for individual classes show that differentiated species distributions can be identified, not only distribution centers. [source] A spatially explicit study of prey,predator interactions in larval fish: assessing the influence of food and predator abundance on larval growth and survivalFISHERIES OCEANOGRAPHY, Issue 1 2003P. Pepin Abstract We apply a coupled biophysical model to reconstruct the environmental history of larval radiated shanny in Conception Bay, Newfoundland. Data on the larvae, their prey and predators were collected during a 2-week period. Our goal was to determine whether environmentally explicit information could be used to infer the characteristics of individual larvae that are most likely to survive. Backward drift reconstruction was used to assess the influence of variations in the feeding environment on changes in the growth rates of individual larvae. Forward drift projections were used to assess the impact of predators on mortality rates as well as the cumulative density distribution of growth rates in the population of larvae in different areas of the bay. There was relatively little influence of current feeding conditions on increment widths. Patterns of selective mortality indicate that fast-growing individuals suffered higher mortality rates, suggesting they were growing into a predator's prey field. However, the mortality rates appeared to increase with decreasing predator abundance, based on the drift reconstructions. The relationship of growth and mortality with environmental conditions suggests that short-term, small-scale variations in environmental history may be difficult to describe accurately in this relatively small system (,1000 km2). [source] Predicting abundance from occupancy: a test for an aggregated insect assemblageJOURNAL OF ANIMAL ECOLOGY, Issue 3 2003M. Warren Summary 1The ubiquitous, positive abundance-occupancy relationship is of potential value to conservation and pest management because of the possibility of using it to predict species abundance from occupancy measures. 2He & Gaston (2000a) developed a model, and a parameterization method, for the prediction of abundance from occupancy based on the negative binomial distribution. There are to date few empirical tests of either the estimation method or model. Here we conduct such a test in a field-based mesocosm experiment using a Drosophilidae assemblage associated with decaying fruit. 3With individual (and groups of) fruit as minimum mapping units, abundance estimates derived using the parameterization method of the He-Gaston model differed significantly from measured values, and were least accurate for the most abundant species. 4Substitution of k -values corrected for species density in the model did not improve abundance predictions significantly. However, substitution of k -values calculated directly from the negative binomial distribution yielded highly accurate abundance predictions. 5Although the distribution of fly species did not deviate significantly from the negative binomial distribution, and the finest possible minimum mapping units were used (individual fruit), the parameterization method in the He-Gaston model consistently underestimated the abundance of species in the assemblage because individuals were very highly aggregated within fruit. 6Because of its potential importance, this model and parameterization method require further exploration at fine scales, commonly represented by individual habitat units, for highly aggregated species. The incorporation of spatially explicit information may provide a means of improving abundance predictions in this regard. [source] Positive Evidence Versus Explicit Rule Presentation and Explicit Negative Feedback: A Computer-Assisted StudyLANGUAGE LEARNING, Issue 1 2004Cristina Sanz The facilitative role of explicit information in second Language acquisition has been supported by a significant body of research (Alanen, 1995; Carroll & Swain, 1993; de Graaff, 1997; DeKeyser, 1995; Ellis, 1993; Robinson, 1996, 1997), but counterevidence is also available (Rosa & O'Neill, 1999; VanPatten & Oikkenon, 1996). This experimental study investigates the effects of computer-delivered, explicit information on the acquisition of Spanish word order by comparing four groups comprised of [+/,Explanation] and [+/,Explicit Feedback]. Results showed that all groups improved significantly and similarly on interpretation and production tests. It is suggested that explicit information may not necessarily facilitate second Language acquisition and that exposing learners to task-essential practice is sufficient to promote acquisition. [source] Distribution modelling to guide stream fish conservation: an example using the mountain sucker in the Black Hills National Forest, USAAQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 7 2008Daniel C. Dauwalter Abstract 1.Conservation biologists need tools that can utilize existing data to identify areas with the appropriate habitat for species of conservation concern. Regression models that predict suitable habitat from geospatial data are such a tool. Multiple logistic regression models developed from existing geospatial data were used to identify large-scale stream characteristics associated with the occurrence of mountain suckers (Catostomus platyrhynchus), a species of conservation concern, in the Black Hills National Forest, South Dakota and Wyoming, USA. 2.Stream permanence, stream slope, stream order, and elevation interacted in complex ways to influence the occurrence of mountain suckers. Mountain suckers were more likely to be present in perennial streams, and in larger, higher gradient streams at higher elevations but in smaller, lower gradient streams at lower elevations. 3.Applying the logistic regression model to all streams provided a way to identify streams in the Black Hills National Forest most likely to have mountain suckers present. These types of models and predictions can be used to prioritize areas that should be surveyed to locate additional populations, identify stream segments within catchments for population monitoring, aid managers in assessing whether proposed forest management will potentially have impacts on fish populations, and identify streams most suitable for stream rehabilitation and conservation or translocation efforts. 4.When the effect of large brown trout (Salmo trutta) was added to the best model of abiotic factors, it had a negative effect on the occurrence of mountain suckers. Negative effects of brown trout on the mountain sucker suggest that management of recreational trout fisheries needs to be balanced with mountain sucker conservation in the Black Hills. However, more spatially explicit information on brown trout abundance would allow managers to understand where the two species interact and where recreational fisheries need to be balanced with fish conservation. Copyright © 2008 John Wiley & Sons, Ltd. [source] | |||||||||||||