971 resultados para Motor Learning


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Relatório de estágio de mestre em Ensino de Educação Física nos Ensinos Básico e Secundário

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Relatório de estágio de mestrado em Ensino de Educação Física nos Ensinos Básico e Secundário

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The relationship between estimated and real motor competences was analyzed for several tasks. Participants were 303 children (160 boys and 143 girls), which had between 6 and 10 years of age (M=8.63, SD=1.16). None of the children presented developmental difficulties or learning disabilities, and all attended age-appropriate classes. Children were divided into three groups according to their age: group 1 (N= 102; age range: 6.48-8.01 years); group 2 (N= 101; age range: 8.02-9.22 years); and group 3 (N=100; age range: 9.24-10.93 years). Children were asked to predict their maximum distance for a locomotor, a manipulative, and a balance task, prior to performing those tasks. Children’s estimations were compared with their real performance to determine their accuracy. Children had, in general, a tendency to overestimate their performance (standing long jump: 56.11%, kicking: 63.37%, throwing: 73.60%, and Walking Backwards (WB) on a balance beam: 45.21%), and older children tended to be more accurate, except for the manipulative tasks. Furthermore, the relationship between estimation and real performance in children with different levels of motor coordination (Köperkoordinationstest für Kinder, KTK) was analyzed. The 75 children with the highest score comprised the Highest Motor Coordination (HMC) group, and the 78 children with the lowest score were placed in the Lowest Motor Coordination (LMC) group. There was a tendency for LMC and HMC children to overestimate their skills at all tasks, except for the HMC group at the WB task. Children with the HMC level tended to be more accurate when predicting their motor performance; however, differences in absolute percent error were only significant for the throwing and WB tasks. In conclusion, children display a tendency to overestimate their performance independently of their motor coordination level and task. This fact may be determinant to the development of their motor competences, since they are more likely to engage and persist in motor tasks, but it might also increase the occurrence of unintended injuries.

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The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

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A partir de diferents enquestes de satisfacció institucional i de l'anàlisi de l'arxiu 'log' del servidor de la biblioteca respecte a l'ús i al comportament dels usuaris, es va detectar que cada cop era més complex accedir als continguts i serveis de manera proporcional al creixement d'aquests darrers i de l'augment del nombre d'usuaris. El creixement dels recursos i de les diferents aplicacions desenvolupats a la Biblioteca Virtual de la UOC (BUOC) va fer necessari la selecció i la implementació d'un motor de cerca que facilités de manera global l'accés als recursos d'informació i als serveis oferts a la comunitat virtual de la UOC d'acord amb la tipologia d'usuari, l'idioma i el seu entorn d'aprenentatge. En aquest article s'exposa el procés d'anàlisi de diferents productes i la implementació de Verity a la BUOC amb els desenvolupaments realitzats en les diferents aplicacions perquè el motor de cerca pugui fer la seva funció.

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L'imagerie mentale est définie comme une expérience similaire à la perception mais se déroulant en l'absence d'une stimulation physique. Des recherches antérieures ont montré que l'imagerie mentale améliore la performance dans certains domaines, comme par exemple le domaine moteur. Cependant, son rôle dans l'apprentissage perceptif n'a pas encore été étudié. L'apprentissage perceptif correspond à l'amélioration permanente des performances suite à la répétition de la même tâche. Cette thèse présente une série des résultats empiriques qui montrent que l'apprentissage perceptif peut aussi être achevé en l'absence des stimuli physiques. En effet, imaginer des stimuli visuels amène à une meilleure performance avec les stimuli réels. Donc, les processus sous-jacents l'apprentissage perceptif ne sont pas uniquement déclenchés par les stimuli sensoriels, mais également par des signaux internes. En plus, l'apprentissage perceptif à travers l'imagerie mentale ne se réalise que seule-ment quand les stimuli ne sont pas (complètement) présents, mais gaiement quand les stimuli montrés ne sont pas utiles quant à la résolution de la tâche. - Mental imagery is described as an experience that resembles pereeptnal ex-perience but which occurs in the absence ef a physical stimulation. Despite its beneficial effects in, among others, motor performance, the role of mental imagery m perceptual learning has not yet been addressed. Here we focus on a specific sensory modality: vision. Perceptual learning is the ability to improve perception in a stable way through the repetition of a given task Here I demonstrate by a series of empirical results that a perceptual improve¬ment can also occur in the absence of a stimulation. Imagining visual stimuli is sufficient for successful perceptual learning. Hence, processes underlying perceptual learning are not only stimulus-driven but can also be driven by internally generated signals. Moreover, I also show that perceptual learning via mental imagery can occur not only when physical stimuli are (partially) absent, but also in conditions where stimuli are uninformative with respect to the task that has to be learned.

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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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El projecte Integració del motor APIS de qüestionaris on-line en una plataformad'eLearning basada en serveis descriu el procés d'anàlisi i implementació del codi necessari per integrar dins de la plataforma d'eLearning SLeD tot el motor d'APIS de manera que SLeD pugui reproduir preguntes o items i exàmens complets o tests dins d'una UOL o unitat d'aprenentatge. Això permetrà dotar a APIS d'un control de sessió d'usuari i permetrà una utilitat que fins ara no tenia, la possibilitat de entrar al món online mitjançant SLeD. Tot aixòs’implementa gràcies a la connexió WebServices amb el mòdul CCSI de CopperCore i SLeD que s'encarrega de donar facilitats al programador de cara a ampliar el ventall d'eines que ofereix aquesta plataforma i fomentar encara més la idea del codi lliure (open source) i la utilitat globalitzadora d'e-Learning.

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OBJECTIVE: To determine the frequency of recent skin injuries in children with neuromotor disabilities and its association with disability. DESIGN: Cross-sectional study of 168 children with neuromotor disabilities aged 2-16 years. SETTING: Two outpatient child rehabilitation centres. MAIN OUTCOME MEASURES: Children were classified as unrestricted walkers, restricted walkers or wheelchair dependent. Each participant's body surface was systematically examined for recent skin injuries with the exception of the anal-genital area. RESULTS: The mean age of our sample was 7.8 (SD 3.7) years with a 3:2 male/female ratio. Overall, 64% had cerebral palsy, 17% a neuromuscular disease and 19% other motor disabilities. Participants had on average 5.3 (SD 4.5) recent skin injuries (max 19), of which 2.5 were bruises (SD 3.3, max 16), 2.4 were abrasions, scratches or cuts (SD 3.0, max 16) and 0.4 were pressure lesions (SD 0.8, max 4). There was a significant decrease in the frequency of recent skin injuries and of bruises with increasing severity of motor disability. Most of this variation was accounted for by injuries to the lower limbs. There were no significant effects of gender, learning disabilities or other comorbidities. CONCLUSIONS: Children with neuromotor disabilities present a progressive reduction in the number of skin injuries with decreasing mobility. Therefore, recent skin injuries in this population which are unusual by their number, appearance or distribution, should raise at least the same level of suspicion for physical abuse as in children without disabilities.

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People who suffer from traumatic brain injury (TBI) often experience cognitive deficits in spatial reference and working memory. The possible roles of cyclooxygenase-1 (COX-1) in learning and memory impairment in mice with TBI are far from well known. Adult mice subjected to TBI were treated with the COX-1 selective inhibitor SC560. Performance in the open field and on the beam walk was then used to assess motor and behavioral function 1, 3, 7, 14, and 21 days following injury. Acquisition of spatial learning and memory retention was assessed using the Morris water maze on day 15 post-TBI. The expressions of COX-1, prostaglandin E2 (PGE2), interleukin (IL)-6, brain-derived neurotrophic factor (BDNF), platelet-derived growth factor BB (PDGF-BB), synapsin-I, and synaptophysin were detected in TBI mice. Administration of SC560 improved performance of beam walk tasks as well as spatial learning and memory after TBI. SC560 also reduced expressions of inflammatory markers IL-6 and PGE2, and reversed the expressions of COX-1, BDNF, PDGF-BB, synapsin-I, and synaptophysin in TBI mice. The present findings demonstrated that COX-1 might play an important role in cognitive deficits after TBI and that selective COX-1 inhibition should be further investigated as a potential therapeutic approach for TBI.

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This study examined the effectiveness of motor-encoding activities on memory and performance of students in a Grade One reading program. There were two experiments in the study. Experiment 1 replicated a study by Eli Saltz and David Dixon (1982). The effect of motoric enactment (Le., pretend play) of sentences on memory for the sentences was investigated. Forty Grade One students performed a "memory-for-sentences" technique, devised by Saltz and Dixon. Only the experimental group used motoric enactment of the sentences. Although quantitative findings revealed no significant difference between the mean scores of the experimental group versus the control group, aspects of the experimental design could have affected the results. It was suggested that Saltz and Dixon's study could be replicated again, with more attention given to variables such as population size, nature of the test sentences, subjects' previous educational experience and conditions related to the testing environment. The second experiment was an application of Saltz and Dixon's theory that motoric imagery should facilitate memory for sentences. The intent was to apply this theory to Grade One students' ability to remember words from their reading program. An experimental gym program was developed using kinesthetic activities to reinforce the skills of the classroom reading program. The same subject group was used in Experiment 2. It was hypothesized that the subjects who experienced the experimental gym program would show greater signs of progress in reading ability, as evidenced by their scores on Form G of the Woodcock Reading Mastery Test--Revised. The data from the WRM--R were analyzed with a 3-way split-plot analysis of variance in which group (experimental vs. control) and sex were the between subjects variables and test-time (pre-test vs. post-test) was the within-subjects variable. Findings revealed the following: (a) both groups made substantial gains over time on the visual-auditory learning sub-test and the triple action of group x sex x time also was significant; (b) children in the experimental and control groups performed similarly on both the pre- and post-test of the letter identification test; (c) time was the only significant effect on subjects' performance on the word identification task; (d) work attack scores showed marked improvement in performance over time for both the experimenta+ and control groups; (e) passage comprehension scores indicated an improvement in performance for both groups over time. Similar to Experiment 1, it is suggested that several modifications in the experimental design could produce significant results. These factors are addressed with suggestions for further research in the area of active learning; more specifically, the effect of motor-encoding activities on memory and academic performance of children.

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Sleep spindles have been found to increase following an intense period of learning on a combination of motor tasks. It is not clear whether these changes are task specific, or a result of learning in general. The current study investigated changes in sleep spindles and spectral power following learning on cognitive procedural (C-PM), simple procedural (S-PM) or declarative (DM) learning tasks. It was hypothesized that S-PM learning would result in increases in Sigma power during Non-REM sleep, whereas C-PM and DM learning would not affect Sigma power. It was also hypothesized that DM learning would increase Theta power during REM sleep, whereas S-PM and C-PM learning would not affect Theta power. Thirty-six participants spent three consecutive nights in the sleep laboratory. Baseline polysomnographic recordings were collected on night 2. Participants were randomly assigned to one of four conditions: C-PM, S-PM, DM or control (C). Memory task training occurred on night 3 followed by polysomnographic recording. Re-testing on respective memory tasks occurred one-week following training. EEG was sampled at 256Hz from 16 sites during sleep. Artifact-free EEG from each sleep stage was submitted to power spectral analysis. The C-PM group made significantly fewer errors, the DM group recalled more, and the S-PM improved on performance from test to re-test. There was a significant night by group interaction for the duration of Stage 2 sleep. Independent t-tests revealed that the S-PM group had significantly more Stage 2 sleep on the test night than the C group. The C-PM and the DM group did not differ from controls in the duration of Stage 2 sleep on test night. There was no significant change in the duration of slow wave sleep (SWS) or REM sleep. Sleep spindle density (spindles/minute) increased significantly from baseline to test night following S-PM learning, but not for C-PM, DM or C groups. This is the first study to have shown that the same pattern of results was found for spindles in SWS. Low Sigma power (12-14Hz) increased significantly during SWS following S-PM learning but not for C-PM, DM or C groups. This effect was maximal at Cz, and the largest increase in Sigma power was at Oz. It was also found that Theta power increased significantly during REM sleep following DM learning, but not for S-PM, C-PM or C groups. This effect was maximal at Cz and the largest change in Theta power was observed at Cz. These findings are consistent with the previous research that simple procedural learning is consolidated during Stage 2 sleep, and provide additional data to suggest that sleep spindles across all non-REM stages and not just Stage 2 sleep may be a mechanism for brain plasticity. This study also provides the first evidence to suggest that Theta activity during REM sleep is involved in memory consolidation.

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Recent studies have shown that providing learners Knowledge of Results (KR) after “good trials” rather than “poor trials” is superior for learning. The present study examined whether requiring participants to estimate their three best or three worst trials in a series of six trial blocks before receiving KR would prove superior to learning compared to not estimating their performance. Participants were required to push and release a slide along a confined pathway using their non-dominant hand to a target distance (133cm). The retention and transfer data suggest those participants who received KR after good trials demonstrated superior learning and performance estimations compared to those receiving KR after poor trials. The results of the present experiment offer an important theoretical extension in our understanding of the role of KR content and performance estimation on motor skill learning.

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Converging evidence has demonstrated learning advantages when an individual is instructed to focus their attention externally. However, many of the motor tasks utilized in past research had clear external objectives (i.e., putting accuracy), creating a compatible relationship between an external focus of attention (i.e., outcome) and an external task objective (i.e., putting accuracy). The present study examined whether or not the consistency of instructions and task objective would differentially impact the acquisition of a golf putting task. Participants performed a putting task in a control condition or in one of four experimental conditions resulting from the factorial interaction of task instructions (internal or external) and task objective (internal or external). The retention and transfer data revealed that participants who received an external task objective demonstrated superior outcome scores. Participants who received technique information paired with outcome information demonstrated superior technique scores.

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As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.