Competencias y prácticas científicas en el laboratorio de química : participación del alumnado de secundaria en la indagación

Esta investigación pretende contribuir al estudio de la participación del alumnado en las prácticas de la comunidad científica, en particular en las relacionadas con el diseño y puesta en práctica de investigaciones e interpretación de datos y establecimiento de conclusiones, así como al estudio de las operaciones epistémicas que el alumnado lleva a cabo en cada práctica. El estudio se enmarca en una perspectiva que considera el aprendizaje de las ciencias como un proceso de socialización dentro de la cultura científica (Driver, Newton & Osborne, 2010) e implica la participación de los estudiantes en las prácticas características de la comunidad científica. La participación del alumnado en las prácticas científicas (NGSS, 2013) implica construir el conocimiento científico y comprender por qué este se construye, examina y evalúa de una forma determinada (Reiser, Berland & Kenyon, 2012). El enfoque del aprendizaje basado en las prácticas guarda relación con el desarrollo de las competencias científicas, ya que ambas implican el desarrollo de operaciones similares.Aquesta recerca pretén contribuir a l'estudi de la participació de l'alumnat en les pràctiques de la comunitat científica, en particular en les relacionades amb el disseny i posada en pràctica de recerques i interpretació de dades i establiment de conclusions, així com a l'estudi de les operacions epistèmiques que l'alumnat duu a terme en cada pràctica. L'estudi s'emmarca en una perspectiva que considera l'aprenentatge de les ciències com un procés de socialització dins de la cultura científica (Driver, Newton & Osborne, 2010) i implica la participació dels estudiants en les pràctiques característiques de la comunitat científica. La participació de l'alumnat en les pràctiques científiques (NGSS, 2013) implica construir el coneixement científic i comprendre per què aquest es construeix, examina i avalua d'una forma determinada (Reiser, Berland & Kenyon, 2012). L'enfocament de l'aprenentatge basat en les pràctiques guarda relació amb el desenvolupament de les competències científiques, ja que ambdues impliquen el desenvolupament d'operacions similars.This research aims to contribute to the study of the participation of students in the practices of the scientific community, notably those related to the design and implementation of research and interpretation of data and establishment of conclusions, as well as to the study of operations epistemic students carry out in each practice. The study is part of an approach that considers the science learning as a process of socialization within the scientific culture (Driver, Newton & Osborne, 2010) and involves the participation of students in the characteristics of the scientific community practices. The participation of students in scientific practice (NGSS, 2013) means building scientific knowledge and understand why this is built, examines and evaluates a certain form (Reiser, Berland & Kenyon, 2012). Practice-based learning approach relates to the development of scientific competences, since both involve the development of similar operations

DTDA: An R Package to Analyze Randomly Truncated Data

In this paper, the R package DTDA for analyzing truncated data is described. This package contains tools for performing three different but related algorithms to compute the nonparametric maximum likelihood estimator of the survival function in the presence of random truncation. More precisely, the package implements the algorithms proposed by Efron and Petrosian (1999) and Shen (2008), for analyzing randomly one-sided and two-sided (i.e., doubly) truncated data. These algorithms and some recent extensions are briefly reviewed. Two real data sets are used to show how DTDA package works in practice.

Inference for variograms

The empirical variogram is a standard tool in the investigation and modelling of spatial covariance. However, its properties can be difficult to identify and exploit in the context of exploring the characteristics of individual datasets. This is particularly true when seeking to move beyond description towards inferential statements about the structure of the spatial covariance which may be present. A robust form of empirical variogram based on a fourth-root transformation is used. This takes advantage of the normal approximation which gives an excellent description of the variation exhibited on this scale. Calculations of mean, variance and covariance of the binned empirical variogram then allow useful computations such as confidence intervals to be added to the underlying estimator. The comparison of variograms for different datasets provides an illustration of this. The suitability of simplifying assumptions such as isotropy and stationarity can then also be investigated through the construction of appropriate test statistics and the distributional calculations required in the associated p-values can be performed through quadratic form methods. Examples of the use of these methods in assessing the form of spatial covariance present in datasets are shown, both through hypothesis tests and in graphical form. A simulation study explores the properties of the tests while pollution data on mosses in Galicia (North-West Spain) are used to provide a real data illustration

Does functional soil microbial diversity contribute to explain within-site plant beta-diversity in an alpine grassland and a <i>dehesa</i> meadow in Spain?

Questions: Once that the effects of hydrological and chemical soil properties have been accounted for, does soil microbial diversity contribute to explain change in plant community structure (i.e. within-site beta-diversity)? If so, at which spatial scale does microbial diversity operate? Location: La Mina in Moscosa Farm, Salamanca, western Spain (dehesa community) and Laguna Larga in the Urbión Peaks, Soria, central-northern Spain (alpine grassland). Methods: The abundance of vascular plant species, soil gram-negative microbial functional types and soil chemical properties (pH, available phosphorus, and extractable cations) were sampled at both sites, for which hydrological models were available. Redundancy analysis (RDA) was used to partition variation in plant community structure into hydrological, chemical and microbial components. Spatial filters, arranged in scalograms, were used to test for the spatial scales at which plant community structure change. Results: In the case of the dehesa the diversity of soil gram-negative microbes, weakly driven by soil pH, contributed to a small extent (adj-R2 = 2%) and at a relative medium spatial scale to explain change in plant community structure. The abundance of a few dehesa species, both annual (Trifolium dubium, Vulpia bromoides) and perennial (Poa bulbosa, Festuca ampla), was associated with either increasing or decreasing soil microbial diversity. In the alpine meadow the contribution was negligible. Conclusions: Microbial diversity can drive community structure, though in the hierarchy of environmental factors structuring communities it appears to rank lower than other soil factors. Still, microbial diversity appears to promote or restrain individual plant species. This paper aims to encourage future studies to use more comprehensive and insightful techniques to assess microbial diversity and to combine this with statistical approaches such as the one used here