783 resultados para Fieldwork Learning Framework


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The EVS4CSCL project starts in the context of a Computer Supported Collaborative Learning environment (CSCL). Previous UOC projects created a CSCL generic platform (CLPL) to facilitate the development of CSCL applications. A discussion forum (DF) was the first application developed over the framework. This discussion forum was different from other products on the marketplace because of its focus on the learning process. The DF carried out the specification and elaboration phases from the discussion learning process but there was a lack in the consensus phase. The consensus phase in a learning environment is not something to be achieved but tested. Common tests are done by Electronic Voting System (EVS) tools, but consensus test is not an assessment test. We are not evaluating our students by their answers but by their discussion activity. Our educational EVS would be used as a discussion catalyst proposing a discussion about the results after an initial query or it would be used after a discussion period in order to manifest how the discussion changed the students mind (consensus). It should be also used by the teacher as a quick way to know where the student needs some reinforcement. That is important in a distance-learning environment where there is no direct contact between the teacher and the student and it is difficult to detect the learning lacks. In an educational environment, assessment it is a must and the EVS will provide direct assessment by peer usefulness evaluation, teacher marks on every query created and indirect assessment from statistics regarding the user activity.

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This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

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Aquest fitxer conté la ontologia que descriu un metamodel de l'especificació Open Service Interface Design v.2.0 proposada per OKI. Ha estat creada en OWL i estesa amb un conjunt de regles SWRL. S'adjunta també el conjunt de regles.

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This file includes the ontology of patterns of educational settings adapted to a given organization as part of a formal framework for specifying, reusing and implementing educational settings. It includes a description of such an ontology.

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This work shows the use of adaptation techniques involved in an e-learning system that considers students' learning styles and students' knowledge states. The mentioned e-learning system is built on a multiagent framework designed to examine opportunities to improve the teaching and to motivate the students to learn what they want in a user-friendly and assisted environment

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Peer-reviewed

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Dialogic learning and interactive groups have proved to be a useful methodological approach appliedin educational situations for lifelong adult learners. The principles of this approach stress theimportance of dialogue and equal participation also when designing the training activities. This paperadopts these principles as the basis for a configurable template that can be integrated in runtimesystems. The template is formulated as a meta-UoL which can be interpreted by IMS Learning Designplayers. This template serves as a guide to flexibly select and edit the activities at runtime (on the fly).The meta-UoL has been used successfully by a practitioner so as to create a real-life example, withpositive and encouraging results

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This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.

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The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

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Scientific reporting and communication is a challenging topic for which traditional study programs do not offer structured learning activities on a regular basis. This paper reports on the development and implementation of a web application and associated learning activities that intend to raise the awareness of reporting and communication issues among students in forensic science and law. The project covers interdisciplinary case studies based on a library of written reports about forensic examinations. Special features of the web framework, in particular a report annotation tool, support the design of various individual and group learning activities that focus on the development of knowledge and competence in dealing with reporting and communication challenges in the students' future areas of professional activity.

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As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

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In the past three decades, feminists and critical theorists have discussed and argued the importance of deconstructing and problematizing social science research methodology in order to question normalized hierarchies concerning the production of knowledge and the status of truth claims. Nevertheless, often, these ideas have basically remained theoretical propositions not embodied in research practices. In fact there is very little published discussion about the difficulties and limits of their practical application. In this paper we introduce some interconnected reflections starting from two different but related experiences of embodying 'feminist activist research'. Our aim is to emphasise the importance of attending to process, making mistakes and learning during fieldwork, as well as experimenting with personalized forms of analysis, such as the construction of narratives and the story-telling process.

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In the past three decades, feminists and critical theorists have discussed and argued the importance of deconstructing and problematizing social science research methodology in order to question normalized hierarchies concerning the production of knowledge and the status of truth claims. Nevertheless, often, these ideas have basically remained theoretical propositions not embodied in research practices. In fact there is very little published discussion about the difficulties and limits of their practical application. In this paper we introduce some interconnected reflections starting from two different but related experiences of embodying 'feminist activist research'. Our aim is to emphasise the importance of attending to process, making mistakes and learning during fieldwork, as well as experimenting with personalized forms of analysis, such as the construction of narratives and the story-telling process.

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There is nothing as amazing and fascinating as children learning process. Between 0 and 6 years old, a child brain develops in a waythat will never be repeated. At this age, children are eager to discover and they have great potential of active and affective life.Because of this, their learning capacity in this period is incalculable. (Jordan-Decarbo y Nelson, 2002; Wild, 1999).Pre-school Education is a unique and special stage, with self identity, which aims are:attending children as a whole,motivate them to learn,give them an affective and stable environment in which they can grow up and get to be balanced and confident people and inwhich they can relate to others, learn, enjoy and be happy.Arts, Music, Visual Arts and Drama (Gardner, 1994) can provide a framework of special, even unique, personal expression.With the aim of introducing qualitative improvements in the education of children and to ensure their emotional wellbeing, and havingnoticed that teachers had important needs and concerns as regards to diversity in their student groups, we developed a programbased on the detection of needs and concerns explained by professionals in education.This program of Grupo edebé, object of our research, is a multicultural, interdisciplinary and globalizing project the aims of which are:developing children's talent and personality,keeping their imagination and creativity and using these as a learning resource,promoting reasoning, favouring expression and communication,providing children with the tools to manage their emotions,and especially, introducing Arts as a procedure to increase learning.We wanted to start the research by studying the impact (Brice, 2003) that this last point had on the learning of five-year-old childrenschooled in multicultural environments.Therefore, the main goal of the research was the assessment of the implementation of a child education programme attending todiversity in a population of five-year-old children, specifically in the practice of procedures based on the use of Arts (music, arts andcrafts and theatre) as a vehicle or procedure for learning contents in Pre-school stage.Because children emotional welfare was a subject of our concern, and bearing in mind that the affective aspects are of vitalimportance for learning and child development (Parke and Gauvain, 2009), Grupo Edebé has also evaluated the starting, evolving andfinal impact in five-year-old children given that they finish Pre-school education at that age.