Do real books help the learning of english in P4?

The purpose of this study is to answer the principal question, Do Real Books help the learning of English in P4?, and create a useful document to English teachers in Infant Education that are interested in working through stories. Previous to the development of the work, it has been necessary a research work and a theoretical documentation, performed using a literature review. This process has served to establish the basis of the study and to develop the subsequent didactic intervention. This second part of the study, the didactic intervention, contains all the information about how it was planned, carried to term and evaluated. There are three different ���real books��� used as a reference in which the reader can see how to choose the correct story, how to adapt the text to the children, the daily planning, and how to evaluate the activities.

El proyecto ���Ecosportech��� como ejemplo de universidad emprendedora. Una experiencia a base del ���Problem Based Learning���

El objetivo de este art��culo es presentar el proyecto EcoSPORTech, cuya finalidad es la creaci��n de una empresa social con j��venes para la realizaci��n de actividades deportivas/ocio en el medio natural, integrando las nuevas tecnolog��as. Este proyecto supone una colaboraci��n interdisciplinaria dentro de la Universidad de Vic, entre las facultades de Empresa y Comunicaci��n (FEC), la de Ciencias de la Salud y el Bienestar (FCSB) y la de Educaci��n (FE) e integra un equipo de profesionales procedentes de los ��mbitos de la empresa, el marketing, el periodismo, el deporte y la terapia ocupacional. Estos profesores formar��n al grupo de j��venes con los que se crear�� la empresa y dirigir��n la misma. Esta empresa (cooperativa) se integra en el vivero de empresas sociales que se est�� creando en la Universidad de Vic.

A Smartphone-Based Prototype System for Incident/Work Zone Management Driven by Crowd-Sourced Data, 2015

This project develops a smartphone-based prototype system that supplements the 511 system to improve its dynamic traffic routing service to state highway users under non-recurrent congestion. This system will save considerable time to provide crucial traffic information and en-route assistance to travelers for them to avoid being trapped in traffic congestion due to accidents, work zones, hazards, or special events. It also creates a feedback loop between travelers and responsible agencies that enable the state to effectively collect, fuse, and analyze crowd-sourced data for next-gen transportation planning and management. This project can result in substantial economic savings (e.g. less traffic congestion, reduced fuel wastage and emissions) and safety benefits for the freight industry and society due to better dissemination of real-time traffic information by highway users. Such benefits will increase significantly in future with the expected increase in freight traffic on the network. The proposed system also has the flexibility to be integrated with various transportation management modules to assist state agencies to improve transportation services and daily operations.

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Cation Transport Coupled to ATP Hydrolysis By the (Na, K)-ATPase : an integrated, animated model

An Adobe (R) animation is presented for use in undergraduate Biochemistry courses, illustrating the mechanism of Na+ and K+ translocation coupled to ATP hydrolysis by the (Na, K)-ATPase, a P-2c-type ATPase, or ATP-powered ion pump that actively translocates cations across plasma membranes. The enzyme is also known as an E-1/E-2-ATPase as it undergoes conformational changes between the E-1 and E-2 forms during the pumping cycle, altering the affinity and accessibility of the transmembrane ion-binding sites. The animation is based on Horisberger's scheme that incorporates the most recent significant findings to have improved our understanding of the (Na, K)-ATPase structure function relationship. The movements of the various domains within the (Na, K)-ATPase alpha-subunit illustrate the conformational changes that occur during Na+ and K+ translocation across the membrane and emphasize involvement of the actuator, nucleotide, and phosphorylation domains, that is, the "core engine" of the pump, with respect to ATP binding, cation transport, and ADP and P-i release.

Machine learning for geospatial data : algorithms, software tools and case studies

R��sum�� Cette th��se est consacr��e �� l'analyse, la mod��lisation et la visualisation de donn��es environnementales �� r��f��rence spatiale �� l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut ��tre consid��r�� au sens large comme une sous-cat��gorie de l'intelligence artificielle qui concerne particuli��rement le d��veloppement de techniques et d'algorithmes permettant �� une machine d'apprendre �� partir de donn��es. Dans cette th��se, les algorithmes d'apprentissage automatique sont adapt��s pour ��tre appliqu��s �� des donn��es environnementales et �� la pr��diction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorit�� des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-lin��aires, robustes et efficaces pour la mod��lisation. Ils peuvent r��soudre des probl��mes de classification, de r��gression et de mod��lisation de densit�� de probabilit��s dans des espaces �� haute dimension, compos��s de variables informatives spatialis��es (�� g��o-features ��) en plus des coordonn��es g��ographiques. De plus, ils sont id��aux pour ��tre impl��ment��s en tant qu'outils d'aide �� la d��cision pour des questions environnementales allant de la reconnaissance de pattern �� la mod��lisation et la pr��diction en passant par la cartographie automatique. Leur efficacit�� est comparable au mod��les g��ostatistiques dans l'espace des coordonn��es g��ographiques, mais ils sont indispensables pour des donn��es �� hautes dimensions incluant des g��o-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont pr��sent��s th��oriquement et impl��ment��s sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes d��crits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le r��seau de neurones de r��gression g��n��ralis��e (General Regression Neural Networks, GRNN), le r��seau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organis��es (SelfOrganized Maps, SOM), les mod��les �� mixture Gaussiennes (Gaussian Mixture Models, GMM), les r��seaux �� fonctions de base radiales (Radial Basis Functions Networks, RBF) et les r��seaux �� mixture de densit�� (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des t��ches vari��es telle que la classification, la r��gression ou l'estimation de densit�� de probabilit��. L'analyse exploratoire des donn��es (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de donn��es. Dans cette th��se les concepts d'analyse exploratoire de donn��es spatiales (Exploratory Spatial Data Analysis, ESDA) sont trait��s selon l'approche traditionnelle de la g��ostatistique avec la variographie exp��rimentale et selon les principes de l'apprentissage automatique. La variographie exp��rimentale, qui ��tudie les relations entre pairs de points, est un outil de base pour l'analyse g��ostatistique de corr��lations spatiales anisotropiques qui permet de d��tecter la pr��sence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est pr��sent��e �� travers l'application de la m��thode des k plus proches voisins qui est tr��s simple et poss��de d'excellentes qualit��s d'interpr��tation et de visualisation. Une part importante de la th��se traite de sujets d'actualit�� comme la cartographie automatique de donn��es spatiales. Le r��seau de neurones de r��gression g��n��ralis��e est propos�� pour r��soudre cette t��che efficacement. Les performances du GRNN sont d��montr��es par des donn��es de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres m��thodes, particuli��rement lors de situations d'urgence. La th��se est compos��e de quatre chapitres : th��orie, applications, outils logiciels et des exemples guid��s. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a ��t�� d��velopp��e durant les 15 derni��res ann��es et a ��t�� utilis��e pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqu��s. Les cas d'��tudes consid��r��s couvrent un vaste spectre de probl��mes g��oenvironnementaux r��els �� basse et haute dimensionnalit��, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des m��taux lourds, la classification de types de sols et d'unit��s hydrog��ologiques, la cartographie des incertitudes pour l'aide �� la d��cision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils compl��mentaires pour l'analyse exploratoire des donn��es et la visualisation ont ��galement ��t�� d��velopp��s en prenant soin de cr��er une interface conviviale et facile �� l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Promotion of learning skills in the study of economics. pilot project in the subject area of

This communication is part of a larger teaching innovation project financed by the University ofBarcelona, whose objective is to develop and evaluate transversal competences of the UB, learningability and responsibility. The competence is divided into several sub-competencies being the ability toanalyze and synthesis the most intensely worked in the first year. The work presented here part fromthe results obtained in phase 1 and 2 previously implemented in other subjects (Mathematics andHistory) in the first year of the degree of Business Administration Degree. In these subjects��� previousexperiences there were deficiencies in the acquisition of learning skills by the students. The work inthe subject of Mathematics facilitated that students become aware of the deficit. The work on thesubject of History insisted on developing readings schemes and with the practical exercises wassought to go deeply in the development of this competence.The third phase presented here is developed in the framework of the second year degree, in the WorldEconomy subject. The objective of this phase is the development and evaluation of the same crosscompetence of the previous phases, from a practice that includes both, quantitative analysis andcritical reflection. Specifically the practice focuses on the study of the dynamic relationship betweeneconomic growth and the dynamics in the distribution of wealth. The activity design as well as theselection of materials to make it, has been directed to address gaps in the ability to analyze andsynthesize detected in the subjects of the first year in the previous phases of the project.The realization of the practical case is considered adequate methodology to improve the acquisition ofcompetence of the students, then it is also proposed how to evaluate the acquisition of suchcompetence. The practice is evaluated based on a rubric developed in the framework of the projectobjectives. Thus at the end of phase 3 we can analyze the process that have followed the students,detect where they have had major difficulties and identify those aspects of teaching that can help toimprove the acquisition of skills by the students. The interest of this phase resides in the possibility tovalue whether tracing of learning through competences, organized in a collaborative way, is a goodtool to develop the acquisition of these skills and facilitate their evaluation.

Soil macrofauna under integrated crop-livestock systems in a Brazilian Cerrado Ferralsol

The objective of this work was to assess the effects of integrated crop-livestock systems, associated with two tillage and two fertilization regimes, on the abundance and diversity of the soil macrofauna. Four different management systems were studied: continuous pasture (mixed grass); continuous crop; two crop-livestock rotations (crop/pasture and pasture/crop); and native Cerrado as a control. Macrofauna was sampled using a modified Tropical Soil Biology and Fertility method, and all individuals were counted and identified at the morphospecies level for each plot. A total of 194 morphospecies were found, distributed among 30 groups, and the most representative in decreasing order of density were: Isoptera, Coleoptera larvae, Formicidae, Oligochaeta, Coleoptera adult, Diplopoda, Hemiptera, Diptera larvae, Arachnida, Chilopoda, Lepidoptera, Gasteropoda, Blattodea and Orthoptera. Soil management systems and tillage regimes affected the structure of soil macrofauna, and integrated crop-livestock systems, associated with no-tillage, especially with grass/legume species associations, had more favorable conditions for the development of "soil engineers" compared with continuous pasture or arable crops. Soil macrofauna density and diversity, assessed at morphospecies level, are effective data to measure the impact of land use in Cerrado soils.

Gesti��n de la actividad no presencial y autoevaluaci��n de competencias = Management of student learning outside the classroom and the self-evaluation of competences

La asignatura troncal ���Evaluaci��n Psicol��gica��� de los estudios de Psicolog��a y delestudio de grado ���Desarrollo humano en la sociedad de la informaci��n��� de laUniversidad de Girona consta de 12 cr��ditos seg��n la Ley Org��nica de Universidades.Hasta el a��o acad��mico 2004-05 el trabajo no presencial del alumno consist��a en larealizaci��n de una evaluaci��n psicol��gica que se entregaba por escrito a final de curso yde la cual el estudiante obten��a una calificaci��n y revisi��n si se solicitaba. En el caminohacia el Espacio Europeo de Educaci��n Superior, esta asignatura consta de 9 cr��ditosque equivalen a un total de 255 horas de trabajo presencial y no presencial delestudiante. En los a��os acad��micos 2005-06 y 2006-07 se ha creado una gu��a de trabajopara la gesti��n de la actividad no presencial con el objetivo de alcanzar aprendizajes anivel de aplicaci��n y soluci��n de problemas/pensamiento cr��tico (Bloom, 1975)siguiendo las recomendaciones de la Agencia para la Calidad del Sistema Universitariode Catalu��a (2005). La gu��a incorpora: los objetivos de aprendizaje, los criterios deevaluaci��n, la descripci��n de las actividades, el cronograma semanal de trabajos paratodo el curso, la especificaci��n de las tutor��as programadas para la revisi��n de losdiversos pasos del proceso de evaluaci��n psicol��gica y el uso del foro para elconocimiento, an��lisis y cr��tica constructiva de las evaluaciones realizadas por loscompa��eros

Learning in the working place: the educational potential of a multihead microscope in pathology postgraduate training.

Training future pathologists is an important mission of many hospital anatomic pathology departments. Apprenticeship-a process in which learning and teaching tightly intertwine with daily work, is one of the main educational methods in use in postgraduate medical training. However, patient care, including pathological diagnosis, often comes first, diagnostic priorities prevailing over educational ones. Recognition of the unique educational opportunities is a prerequisite for enhancing the postgraduate learning experience. The aim of this paper is to draw attention of senior pathologists with a role as supervisor in postgraduate training on the potential educational value of a multihead microscope, a common setting in pathology departments. After reporting on an informal observation of senior and junior pathologists' meetings around the multihead microscope in our department, we review the literature on current theories of learning to provide support to the high potential educational value of these meetings for postgraduate training in pathology. We also draw from the literature on learner-centered teaching some recommendations to better support learning in this particular context. Finally, we propose clues for further studies and effective instruction during meetings around a multihead microscope.

Cover plants with potential use for crop-livestock integrated systems in the Cerrado region

The objective of this work was to evaluate the effects of lignin, hemicellulose, and cellulose concentrations in the decomposition process of cover plant residues with potential use in no-tillage with corn, for crop-livestock integrated system, in the Cerrado region. The experiment was carried out at Embrapa Cerrados, in Planaltina, DF, Brazil in a split plot experimental design. The plots were represented by the plant species and the subplots by harvesting times, with three replicates. The cover plants Urochloa ruziziensis, Canavalia brasiliensis, Cajanus cajan, Pennisetum glaucum, Mucuna aterrima, Raphanus sativus, Sorghum bicolor were evaluated together with spontaneous plants in the fallow. Cover plants with lower lignin concentrations and, consequently, higher residue decomposition such as C. brasiliensis and U. ruziziensis promoted higher corn yield. High concentrations of lignin inhibit plant residue decomposition and this is favorable for the soil cover. Lower concentrations of lignin result in accelerated plant decomposition, more efficient nutrient cycling, and higher corn yield.

Soil biological attributes in pastures of different ages in a crop-livestock integrated system

The objective of this work was to evaluate the effect of the pasture (Urochloa brizantha) component age on soil biological properties, in a crop-livestock integrated system. The experiment was carried out in a Brazilian savannah (Cerrado) area with 92 ha, divided into six pens of approximately 15 ha. Each pen represented a different stage of the pasture component: formation, P0; one year, P1; two years, P2; three years, P3; and final with 3.5 years, Pf. Samples were taken in the 0-10 cm soil depth. The soil biological parameters - microbial biomass carbon (MBC), microbial biomass respiration (C-CO2), metabolic quotient (qCO2), microbial quotient (q mic), and total organic carbon (TOC) - were evaluated and compared among different stages of the pasture, and between an adjacent area under native Cerrado and another area under degraded pasture (PCD). The MBC, q mic and TOC increased and qCO2 reduced under the different pasture stages. Compared to PCD, the pasture stages had higher MBC, q mic and TOC, and lower qCO2. The crop-livestock integrated system improved soil microbiological parameters and immobilized carbon in the soil in comparison to the degraded pasture.

La Gesti��n de la Informaci��n Personal en usuarios intensivos de las TIC

Se presenta un modelo de an��lisis del comportamiento informacional global de un colectivo de individuos (estudiantes de la Universitat Oberta de Catalunya) que tienen una percepci��n positiva sobre el uso de las tecnolog��as de la informaci��n y la comunicaci��n y que realizan un uso intensivo de las mismas.A partir de una aproximaci��n cualitativa, mediante 24 entrevistas y un posterior an��lisis del contenido, se identifican cuatro perfiles distintos de gesti��n de la informaci��n personal (reactivo, pasivo, exhaustivo y proactivo) en base a diez variables subyacentes (acceso, gesti��n y usos de la informaci��n, competenciasinformacionales, perfil cognitivo, actitud, percepci��n de las TIC, ��mbito acad��mico, profesional y de la vida diaria) y se ponen derelieve las diferencias de comportamiento informacional dependiendo del ��mbito en el que se encuentren. La identificaci��n de los perfiles es un estadio b��sico del dise��o centrado en los usuarios que facilita la realizaci��n de intervenciones espec��ficas para cada tipo de usuario, respetando requerimientos de herramientasy procesos para que puedan desarrollar su comportamiento informacional de forma eficiente y eficaz.

Analysing Professional Discourse in Interactive Learning: Integrating Historical and Situational Perspectives

Peer-reviewed

Trabajo colaborativo en entornos e-learning y desarrollo de competencias transversales de trabajo en equipo: An��lisis del caso del M��ster en gesti��n de Proyectos en Cooperaci��n Internacional, CSEU La Salle

Peer-reviewed