972 resultados para exploratory e-learning
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En ciencias de la educación, las últimas décadas han estado marcadas por un interés en las ideas de Lev S. Vygotski. De hecho, a partir de esas ideas se han propuesto varias aplicaciones educativas. Una de ellas es el “Key to learning”. El artículo propone una visión general de este programa educativo desarrollado a partir de algunos trabajos e ideas de autores rusos contemporáneos. Primero, desarrollamos algunas ideas en torno a la noción de zona de desarrollo próximo (ZpD). Después, sugerimos la teoría de las habilidades de aprendizaje. En este sentido, el objetivo principal de “Key to learning” es mejorar las habilidades de aprendizaje cognitivas, comunicativas y directivas de niños de entre 3 a 7 años de edad. Para este propósito son creadas 12 unidades curriculares que componen el programa. Para concluir se enfatiza la creación de zonas de desarrollo próximo estructuradas como parte de un sistema de enseñanza y aprendizaje que vincula la actividad, la asistencia y la agencia
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PURPOSE OF REVIEW: Many chemotherapeutic drugs, including fluoropyrimidines, platinums, CPT-11, taxanes and adriamycin have single-agent activity in advanced gastric cancer. Although combination chemotherapy has been shown to be more effective than single agents, response rates between 30 and 50% have not fulfilled their promise as progression-free survival from the best combinations ranges between 3 and 7 months and overall survival between 8 and 11 months. The development of targeted therapies in gastric cancer clearly stays behind the integration of these novel agents into new treatment concepts for patients with colorectal cancer. This review summarizes the experience and major recent advances in the development of targeted therapies in advanced gastric cancer. RECENT FINDINGS: Recent publications on targeted therapies in gastric cancer are limited to nonrandomized phase I or II trials. The majority of agents tested were angiogenesis inhibitors or agents targeting the epidermal growth factor receptors epidermal growth factor receptor 1 and HER2. SUMMARY: Adequately powered, randomized phase III trials are necessary to define the clinical role of targeted therapies in advanced gastric cancer. Biomarker studies to correlate with treatment outcomes will be critical to identify patients who benefit most from chemotherapy and targeted therapy.
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Contribution of visual and nonvisual mechanisms to spatial behavior of rats in the Morris water maze was studied with a computerized infrared tracking system, which switched off the room lights when the subject entered the inner circular area of the pool with an escape platform. Naive rats trained under light-dark conditions (L-D) found the escape platform more slowly than rats trained in permanent light (L). After group members were swapped, the L-pretrained rats found under L-D conditions the same target faster and eventually approached latencies attained during L navigation. Performance of L-D-trained rats deteriorated in permanent darkness (D) but improved with continued D training. Thus L-D navigation improves gradually by procedural learning (extrapolation of the start-target azimuth into the zero-visibility zone) but remains impaired by lack of immediate visual feedback rather than by absence of the snapshot memory of the target view.
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Objective: The underlying mechanisms modifying clinician's communication skills by means of communication skills training (CST) remain unknown. Defense mechanisms, defined as psychological processes protecting the individual against emotional stress, may be a mediating factor of skills improvement.Methods: Using an adapted version of the Defense Mechanism Rating Scale-Clinician, this study evaluated clinicians' defense mechanisms and their possible modification after CST. Interviews with simulated patients of oncology clinicians (N=57) participating in CST (pre-/post-CST with a 6-month interval) were compared WITH interviews with the same simulated patients of oncology clinicians (N=56) who did not undergo training (T1 and T2 with a 6-month interval).Results: Results showed (i) a high number (mean=16, SD=6) and variety of defenses triggered by the 15-min interviews, (ii) no evolution difference between groups, and (iii) an increase in mature defenses after CST for clinicians with an initial higher level of defensive functioning.Conclusions: This is the first study describing clinicians' defensive functioning; results indicate a possible mediating role of defenses in clinician-patient communication.
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The influence of proximal olfactory cues on place learning and memory was tested in two different spatial tasks. Rats were trained to find a hole leading to their home cage or a single food source in an array of petri dishes. The two apparatuses differed both by the type of reinforcement (return to the home cage or food reward) and the local characteristics of the goal (masked holes or salient dishes). In both cases, the goal was in a fixed location relative to distant visual landmarks and could be marked by a local olfactory cue. Thus, the position of the goal was defined by two sets of redundant cues, each of which was sufficient to allow the discrimination of the goal location. These experiments were conducted with two strains of hooded rats (Long-Evans and PVG), which show different speeds of acquisition in place learning tasks. They revealed that the presence of an olfactory cue marking the goal facilitated learning of its location and that the facilitation persisted after the removal of the cue. Thus, the proximal olfactory cue appeared to potentiate learning and memory of the goal location relative to distant environmental cues. This facilitating effect was only detected when the expression of spatial memory was not already optimal, i.e., during the early phase of acquisition. It was not limited to a particular strain.
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Recent findings in neuroscience suggest that adult brain structure changes in response to environmental alterations and skill learning. Whereas much is known about structural changes after intensive practice for several months, little is known about the effects of single practice sessions on macroscopic brain structure and about progressive (dynamic) morphological alterations relative to improved task proficiency during learning for several weeks. Using T1-weighted and diffusion tensor imaging in humans, we demonstrate significant gray matter volume increases in frontal and parietal brain areas following only two sessions of practice in a complex whole-body balancing task. Gray matter volume increase in the prefrontal cortex correlated positively with subject's performance improvements during a 6 week learning period. Furthermore, we found that microstructural changes of fractional anisotropy in corresponding white matter regions followed the same temporal dynamic in relation to task performance. The results make clear how marginal alterations in our ever changing environment affect adult brain structure and elucidate the interrelated reorganization in cortical areas and associated fiber connections in correlation with improvements in task performance.
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This study deals with the psychological processes underlying the selection of appropriate strategy during exploratory behavior. A new device was used to assess sexual dimorphisms in spatial abilities that do not depend on spatial rotation, map reading or directional vector extraction capacities. Moreover, it makes it possible to investigate exploratory behavior as a specific response to novelty that trades off risk and reward. Risk management under uncertainty was assessed through both spontaneous searching strategies and signal detection capacities. The results of exploratory behavior, detection capacities, and decision-making strategies seem to indicate that women's exploratory behavior is based on risk-reducing behavior while men behavior does not appear to be influenced by this variable. This difference was interpreted as a difference in information processing modifying beliefs concerning the likelihood of uncertain events, and therefore influencing risk evaluation.
Learning-induced plasticity in auditory spatial representations revealed by electrical neuroimaging.
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Auditory spatial representations are likely encoded at a population level within human auditory cortices. We investigated learning-induced plasticity of spatial discrimination in healthy subjects using auditory-evoked potentials (AEPs) and electrical neuroimaging analyses. Stimuli were 100 ms white-noise bursts lateralized with varying interaural time differences. In three experiments, plasticity was induced with 40 min of discrimination training. During training, accuracy significantly improved from near-chance levels to approximately 75%. Before and after training, AEPs were recorded to stimuli presented passively with a more medial sound lateralization outnumbering a more lateral one (7:1). In experiment 1, the same lateralizations were used for training and AEP sessions. Significant AEP modulations to the different lateralizations were evident only after training, indicative of a learning-induced mismatch negativity (MMN). More precisely, this MMN at 195-250 ms after stimulus onset followed from differences in the AEP topography to each stimulus position, indicative of changes in the underlying brain network. In experiment 2, mirror-symmetric locations were used for training and AEP sessions; no training-related AEP modulations or MMN were observed. In experiment 3, the discrimination of trained plus equidistant untrained separations was tested psychophysically before and 0, 6, 24, and 48 h after training. Learning-induced plasticity lasted <6 h, did not generalize to untrained lateralizations, and was not the simple result of strengthening the representation of the trained lateralizations. Thus, learning-induced plasticity of auditory spatial discrimination relies on spatial comparisons, rather than a spatial anchor or a general comparator. Furthermore, cortical auditory representations of space are dynamic and subject to rapid reorganization.
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In this paper we propose a novel unsupervised approach to learning domain-specific ontologies from large open-domain text collections. The method is based on the joint exploitation of Semantic Domains and Super Sense Tagging for Information Retrieval tasks. Our approach is able to retrieve domain specific terms and concepts while associating them with a set of high level ontological types, named supersenses, providing flat ontologies characterized by very high accuracy and pertinence to the domain.
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The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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This paper reports on the purpose, design, methodology and target audience of E-learning courses in forensic interpretation offered by the authors since 2010, including practical experiences made throughout the implementation period of this project. This initiative was motivated by the fact that reporting results of forensic examinations in a logically correct and scientifically rigorous way is a daily challenge for any forensic practitioner. Indeed, interpretation of raw data and communication of findings in both written and oral statements are topics where knowledge and applied skills are needed. Although most forensic scientists hold educational records in traditional sciences, only few actually followed full courses that focussed on interpretation issues. Such courses should include foundational principles and methodology - including elements of forensic statistics - for the evaluation of forensic data in a way that is tailored to meet the needs of the criminal justice system. In order to help bridge this gap, the authors' initiative seeks to offer educational opportunities that allow practitioners to acquire knowledge and competence in the current approaches to the evaluation and interpretation of forensic findings. These cover, among other aspects, probabilistic reasoning (including Bayesian networks and other methods of forensic statistics, tools and software), case pre-assessment, skills in the oral and written communication of uncertainty, and the development of independence and self-confidence to solve practical inference problems. E-learning was chosen as a general format because it helps to form a trans-institutional online-community of practitioners from varying forensic disciplines and workfield experience such as reporting officers, (chief) scientists, forensic coordinators, but also lawyers who all can interact directly from their personal workplaces without consideration of distances, travel expenses or time schedules. In the authors' experience, the proposed learning initiative supports participants in developing their expertise and skills in forensic interpretation, but also offers an opportunity for the associated institutions and the forensic community to reinforce the development of a harmonized view with regard to interpretation across forensic disciplines, laboratories and judicial systems.
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AIM: The study aims to evaluate the effects of assertive community treatment (ACT) on the mental health and overall functioning of adolescents suffering from severe psychiatric disorders and who refuse any traditional child psychiatric care. There are a few studies evaluating the effects of ACT on a population of adolescents with psychiatric disorders. This short report highlights the impact of an ACT programme tailored to the needs of these patients, not only as an alternative to hospitalization, but also as a new form of intervention for patients that are difficult to engage. METHODS: The effect of ACT on 35 adolescents using the Health of the Nation Outcome Scales for Children and Adolescents (HoNOSCA) as a measuring tool in pre- and post-intervention was evaluated. RESULTS: The results show that the intervention was associated with a significant improvement on the HoNOSCA overall score, with the following items showing significant amelioration: hyperactivity/focus problems, non-organic somatic symptoms, emotional symptoms, scholastic/language skills, peer relationships, family relationships and school attendance. CONCLUSION: ACT appears as a feasible intervention for hard-to-engage adolescents suffering from psychiatric disorders. The intervention seems to improve their mental health and functioning. This pilot study may serve as a basis to prepare a controlled study that will also take the costs of the intervention into account.
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BACKGROUND: Little is known about coping specificities, as operationalization of the concept of affect regulation, in borderline personality disorder (BPD). It is most important to take into account methodological criticisms addressed to the self-report questionnaire approach and to compare BPD coping specificities to the ones of neighbouring diagnostic categories, such as bipolar disorder (BD). SAMPLING AND METHODS: The present exploratory study compared the coping profiles of N = 25 patients presenting BPD to those of N = 25 patients presenting BD and to those of N = 25 healthy controls. All participants underwent a clinical interview that was transcribed and rated using the Coping Patterns observer-rater system. RESULTS: Results partially confirmed study hypotheses and showed differences between BPD patients and healthy controls in all coping domains (competence, resources and autonomy), whereas the only coping domain presenting a BPD-specific lack of skills, compared with the BD patients, was autonomy, a set of coping strategies facing stress appraised as challenge. These coping processes were linked to general and BPD symptomatology. CONCLUSIONS: These results extend conclusions of earlier studies on affect regulation processes in BPD and bear important clinical implications, in the context of dialectical behavior therapy and other therapeutic approaches. Limitations of this exploratory study, such as the small sample size, are acknowledged. Copyright © 2012 John Wiley & Sons, Ltd. KEY PRACTITIONER MESSAGE: Coping can be reliably assessed in the narrative process in an non-structured interview frame. Patients with borderline personality disorder present with a specific lack of skills in affect regulation related to autonomy issues, compared to patients with bipolar disorder and healthy controls. Lack of skills in accommodation to distressing emotions in borderline personality disorder is related to symptom gravity and may be treated using radical acceptance strategies.