905 resultados para One-Step Learning
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This leaflet was developed for parents and carers of babies aged up to one year old who need help learning to talk.
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This leaflet was developed for parents and carers of babies aged between one and two years old who need help learning to talk.
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In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.
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Recently many OER activities have been getting popular, and users who access those content for informal learning are increasing. Most popular OER must be OCW, which has been proposed and promoted by MIT since 2001. In Japan OCW has been penetrating gradually since 2005. However in terms of formal learning utilization ICT technology has not been so popular yet in Japanese higher education field. In this paper two case studies, one is formal e-Learning using OCW, and the other is portal site of open contents from universities are described
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The adjustment of the teaching learning contents in Physical Education, requires of a rigorous analysis that permits to adjust them to the maximum with the educational needs of the student body. It has been approached an investigation study in the one which have intervened pupils, boys and girls, of two different populations, Girona and Madrid in order to prove and analyse the motor and mental components of the student body in the real situation of the game. The hypothesis that we have treated are:if it exists differences between the boys and girls of the educational levels studied in the motor and mental solution in the sports initiation, additionally, the differences that they can exist between the courses and what distance is verified between the study ages to approach a physical activity that implies an initial step to the hour of teaching the collective sports in the classes of Physical education. They have been employed three measure instruments: the first permits to analyse the mental solution without need of practice employing situation photographs of the real game with those which the pupils must choose to who to happen; the second is a pass test that permits to prove the technical dominance to use in a collective sport and the third is a real game situation that permits to put in manifesto the relationship between the mental behaviour and the motor of the pupil. This real game situation is ‘the game of ten pass’ (Blázquez,1986; Torres,1993). The results demonstrate that it do not exist differences between the two sexes in the study ages. In the case of the technical execution level, there is a considerable increase with the age and it is slightly greater in the kids that in the girls. In the case of the real game, we find ourselves with a great variability in the results and we cannot conclude that there are relative differences to the sex in none of the three courses. Respect at participation level during the game is confirmed that the pupils that more participate are not the pupils than more balls lose, what permits to guarantee the idea of the fact that it is convenient to use the real game practice as direct learning element. Finally, there is no a high correlation between the execution level measured in the test of technical execution and the decision execution during the game
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This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV
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Background: One characteristic of post traumatic stress disorder is an inability to adapt to a safe environment i.e. to change behavior when predictions of adverse outcomes are not met. Recent studies have also indicated that PTSD patients have altered pain processing, with hyperactivation of the putamen and insula to aversive stimuli (Geuze et al, 2007). The present study examined neuronal responses to aversive and predicted aversive events. Methods: Twenty-four trauma exposed non-PTSD controls and nineteen subjects with PTSD underwent fMRI imaging during a partial reinforcement fear conditioning paradigm, with a mild electric shock as the unconditioned stimuli (UCS). Three conditions were analyzed: actual presentations of the UCS, events when a UCS was expected, but omitted (CS+), and events when the UCS was neither expected nor delivered (CS-). Results: The UCS evoked significant alterations in the pain matrix consisting of the brainstem, the midbrain, the thalamus, the insula, the anterior and middle cingulate and the contralateral somatosensory cortex. PTSD subjects displayed bilaterally elevated putamen activity to the electric shock, as compared to controls. In trials when USC was expected, but omitted, significant activations were observed in the brainstem, the midbrain, the anterior insula and the anterior cingulate. PTSD subjects displayed similar activations, but also elevated activations in the amygdala and the posterior insula. Conclusions: These results indicate altered fear and safety learning in PTSD, and neuronal activations are further explored in terms of functional connectivity using psychophysiological interaction analyses.
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Aquest estudi pretén investigar els intercanvis verbals mestre/a – aprenent(s) en dos contextos d'instrucció diferents: classes amb un enfocament AICLE (Aprenentatge Integrat de Continguts Curriculars i Llengua Estrangera) on s’aprenen continguts no lingüístics a través de l’anglès, per una banda, i classes 'tradicionals' d'anglès com a llengua estrangera, on l’anglès és alhora objecte d’estudi i vehicle de comunicació, per una altra banda. Més concretament, les preguntes que formula el/la mestre/a, la producció oral dels aprenents i el 'feedback' del/de la mestre/a en els episodis d’atenció a la forma s’han estudiat a la llum de les principals teories provinents del camp de l’Adquisició de Segones Llengües (SLA) per tal de demostrar el seu paper en l’aprenentatge de l’anglès. El corpus de dades prové de l’enregistrament de 7 sessions AICLE i d'11 sessions EFL enregistrades en format àudio i vídeo en dos centres públics d’Educació Primària (EP) de Catalunya. A cadascuna de les escoles, el/la mateix/a mestre/a és l’encarregat/da dels dos tipus d’instrucció amb el mateix grup d’aprenents (10-11 anys d’edat), fet que permet eliminar variables individuals com l'aptitud dels aprenents o l'estil del/de la mestre/a.Els resultats mostren un cert nombre de similituds discursives entre AICLE i EFL donat que ambdós enfocaments tenen lloc en el context-classe amb unes característiques ben definides. Tal com apunta la recerca realitzada en aquest camp, la instrucció AICLE reuneix un seguit de condicions idònies per un major desenvolupament dels nivells de llengua anglesa més enllà de les classes ‘tradicionals’ d’anglès. Malgrat això, aquest estudi sembla indicar que el potencial d'AICLE pel que fa a facilitar una exposició rica a l’anglès i una producció oral significativa no s’explota degudament. En aquest sentit, els resultats d’aquest estudi poden contribuir a la formació dels futurs professors d'AICLE si es busca l’assoliment d’una complementarietat d’ambdós contextos amb l’objectiu últim de millorar els nivells de domini de la llengua anglesa.
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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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How can we best understand the emergence of the European Security and Defence Policy (ESDP)? This paper applies the theories of historical institutionalism and experiential learning to offer a dynamic conceptualisation of moves towards an ESDP which highlights some of the causal factors that a more temporally-restricted analysis would miss. It firstly shows how the institutional and functional expansion of European Political Cooperation (EPC) over the course of the 1970s and 80s gave rise to a context in which the development of a security and defence dimension came to be viewed as more logical and even necessary. It then goes on to analyse some of the external factors (in the form of actors, events and institutions) that further pushed in this direction and proved to influence the policy’s subsequent evolution. The paper is therefore intended to act as a first-step to understanding the ESDP’s development from this perspective.
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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.
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Poor compliance with antihypertensive drug regimens is one recognized cause of inadequate blood pressure control. Compliance is difficult to measure, so poor adherence to treatment remains largely undiagnosed in clinical practice. When the therapeutic response to a drug is not the one expected, it is a major challenge for many physicians to decide whether the patient is a non-responder or a non-complier. Poor compliance is therefore often incorrectly interpreted as a lack of response to treatment. Not detecting non-compliance can lead to the wrong measures being taken. Electronic monitoring of compliance provides important longitudinal information about drug-intake behaviour that cannot be obtained in the clinic. Such monitoring can improve both compliance and blood pressure control, and help physicians to make more rational therapeutic decisions. A reliable assessment of compliance could have a great impact on medical costs by preventing unnecessary investigations or dose adaptations in patients who are not taking their drugs adequately, or potentially reducing the number of hospitalizations. Side-effects and lack of effectiveness are two frequent causes of poor compliance. The right choice of antihypertensive drug can therefore contribute to compliance. In this respect, it is important to find a drug regimen that is effective, long-acting and well tolerated. Long-acting antihypertensive drugs that provide good blood pressure control beyond the 24-h dosing period should perhaps be considered as drugs of choice in non-compliant patients with hypertension because they help to prevent the consequences of occasional drug omissions.
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We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.
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SUMMARY : The function of sleep for the organism is one of the most persistent and perplexing questions in biology. Current findings lead to the conclusion that sleep is primarily for the brain. In particular, a role for sleep in cognitive aspects of brain function is supported by behavioral evidence both in humans and animals. However, in spite of remarkable advancement in the understanding of the mechanisms underlying sleep generation and regulation, it has been proven difficult to determine the neurobiological mechanisms underlying the beneficial effect of sleep, and the detrimental impact of sleep loss, on learning and memory processes. In my thesis, I present results that lead to several critical steps forward in the link between sleep and cognitive function. My major result is the molecular identification and physiological analysis of a protein, the NR2A subunit of NMDA receptor (NMDAR), that confers sensitivity to sleep loss to the hippocampus, a brain structure classically involved in mnemonic processes. Specifically, I used a novel behavioral approach to achieve sleep deprivation in adult C57BL6/J mice, yet minimizing the impact of secondary factors associated with the procedure,.such as stress. By using in vitro electrophysiological analysis, I show, for the first time, that sleep loss dramatically affects bidirectional plasticity at CA3 to CA1 synapses in the hippocampus, a well established cellular model of learning and memory. 4-6 hours of sleep loss elevate the modification threshold for bidirectional synaptic plasticity (MT), thereby promoting long-term depression of CA3 to CA 1 synaptic strength after stimulation in the theta frequency range (5 Hz), and rendering long-term potentiation induction.more difficult. Remarkably, 3 hours of recovery sleep, after the deprivation, reset the MT at control values, thus re-establishing the normal proneness of synapses to undergo long-term plastic changes. At the molecular level, these functional changes are paralleled by a change in the NMDAR subunit composition. In particular, the expression of the NR2A subunit protein of NMDAR at CA3 to CA1 synapses is selectively and rapidly increased by sleep deprivation, whereas recovery sleep reset NR2A synaptic content to control levels. By using an array of genetic, pharmacological and computational approaches, I demonstrate here an obligatory role for NR2A-containing NMDARs in conveying the effect of sleep loss on CA3 to CAl MT. Moreover, I show that a genetic deletion of the NR2A subunit fully preserves hippocampal plasticity from the impact of sleep loss, whereas it does not alter sleepwake behavior and homeostatic response to sleep deprivation. As to the mechanism underlying the effects of the NR2A subunit on hippocampal synaptic plasticity, I show that the increased NR2A expression after sleep loss distinctly affects the contribution of synaptic and more slowly recruited NMDAR pools activated during plasticity-induction protocols. This study represents a major step forward in understanding the mechanistic basis underlying sleep's role for the brain. By showing that sleep and sleep loss affect neuronal plasticity by regulating the expression and function of a synaptic neurotransmitter receptor, I propose that an important aspect of sleep function could consist in maintaining and regulating protein redistribution and ion channel trafficking at central synapses. These findings provide a novel starting point for investigations into the connections between sleep and learning, and they may open novel ways for pharmacological control over hippocampal .function during periods of sleep restriction. RÉSUMÉ DU PROJET La fonction du sommeil pour l'organisme est une des questions les plus persistantes et difficiles dans la biologie. Les découvertes actuelles mènent à la conclusion que le sommeil est essentiel pour le cerveau. En particulier, le rôle du sommeil dans les aspects cognitifs est soutenu par des études comportementales tant chez les humains que chez les animaux. Cependant, malgré l'avancement remarquable dans la compréhension des mécanismes sous-tendant la génération et la régulation du sommeil, les mécanismes neurobiologiques qui pourraient expliquer l'effet favorable du sommeil sur l'apprentissage et la mémoire ne sont pas encore clairs. Dans ma thèse, je présente des résultats qui aident à clarifier le lien entre le sommeil et la fonction cognitive. Mon résultat le plus significatif est l'identification moléculaire et l'analyse physiologique d'une protéine, la sous-unité NR2A du récepteur NMDA, qui rend l'hippocampe sensible à la perte de sommeil. Dans cette étude, nous avons utilisé une nouvelle approche expérimentale qui nous a permis d'induire une privation de sommeil chez les souris C57BL6/J adultes, en minimisant l'impact de facteurs confondants comme, par exemple, le stress. En utilisant les techniques de l'électrophysiologie in vitro, j'ai démontré, pour la première fois, que la perte de sommeil est responsable d'affecter radicalement la plasticité bidirectionnelle au niveau des synapses CA3-CA1 de l'hippocampe. Cela correspond à un mécanisme cellulaire de l'apprentissage et de la mémoire bien établi. En particulier, 4-6 heures de privation de sommeil élèvent le seuil de modification pour la plasticité synaptique bidirectionnelle (SM). Comme conséquence, la dépression à long terme de la transmission synaptique est induite par la stimulation des fibres afférentes dans la bande de fréquences thêta (5 Hz), alors que la potentialisation à long terme devient plus difficile. D'autre part, 3 heures de sommeil de récupération sont suffisant pour rétablir le SM aux valeurs contrôles. Au niveau moléculaire, les changements de la plasticité synaptiques sont associés à une altération de la composition du récepteur NMDA. En particulier, l'expression synaptique de la protéine NR2A du récepteur NMDA est rapidement augmentée de manière sélective par la privation de sommeil, alors que le sommeil de récupération rétablit l'expression de la protéine au niveau contrôle. En utilisant des approches génétiques, pharmacologiques et computationnelles, j'ai démontré que les récepteurs NMDA qui expriment la sous-unité NR2A sont responsables de l'effet de la privation de sommeil sur le SM. De plus, nous avons prouvé qu'une délétion génétique de la sous-unité NR2A préserve complètement la plasticité synaptique hippocampale de l'impact de la perte de sommeil, alors que cette manipulation ne change pas les mécanismes de régulation homéostatique du sommeil. En ce qui concerne les mécanismes, j'ai .découvert que l'augmentation de l'expression de la sous-unité NR2A au niveau synaptique modifie les propriétés de la réponse du récepteur NMDA aux protocoles de stimulations utilisés pour induire la plasticité. Cette étude représente un pas en avant important dans la compréhension de la base mécaniste sous-tendant le rôle du sommeil pour le cerveau. En montrant que le sommeil et la perte de sommeil affectent la plasticité neuronale en régulant l'expression et la fonction d'un récepteur de la neurotransmission, je propose qu'un aspect important de la fonction du sommeil puisse être finalisé au règlement de la redistribution des protéines et du tracking des récepteurs aux synapses centraux. Ces découvertes fournissent un point de départ pour mieux comprendre les liens entre le sommeil et l'apprentissage, et d'ailleurs, ils peuvent ouvrir des voies pour des traitements pharmacologiques dans le .but de préserver la fonction hippocampale pendant les périodes de restriction de sommeil.