Search results for '*Skill Learning' (try it on Scholar)

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  1. Stéphanie Lefebvre, Patrice Laloux, André Peeters, Philippe Desfontaines, Jacques Jamart & Yves Vandermeeren (2012). Dual-tDCS Enhances Online Motor Skill Learning and Long-Term Retention in Chronic Stroke Patients. Frontiers in Human Neuroscience 6.score: 240.0
    Background Since motor learning is a key component for stroke recovery, enhancing motor skill learning is a crucial challenge for neurorehabilitation. Transcranial direct current stimulation (tDCS) is a promising approach for improving motor learning. The aim of this trial was to test the hypothesis that dual-tDCS applied bilaterally over the primary motor cortices (M1) improves online motor skill learning with the paretic hand and its long-term retention. Methods Eighteen chronic stroke patients participated in a randomised, cross-over, (...)
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  2. Y. Vandermeeren S. Lefebvre, P. Laloux, A. Peeters, P. Desfontaines, J. Jamart (2012). Dual-tDCS Enhances Online Motor Skill Learning and Long-Term Retention in Chronic Stroke Patients. Frontiers in Human Neuroscience 6.score: 240.0
    Background Since motor learning is a key component for stroke recovery, enhancing motor skill learning is a crucial challenge for neurorehabilitation. Transcranial direct current stimulation (tDCS) is a promising approach for improving motor learning. The aim of this trial was to test the hypothesis that dual-tDCS applied bilaterally over the primary motor cortices (M1) improves online motor skill learning with the paretic hand and its long-term retention. Methods Eighteen chronic stroke patients participated in a randomised, cross-over, (...)
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  3. Edwin M. Robertson, Alvaro Pascual-Leone & Daniel Z. Press (2004). Awareness Modifies the Skill-Learning Benefits of Sleep. Current Biology 14 (3):208-212.score: 210.0
  4. Daniel B. Willingham, Joanna Salidis & John D. E. Gabrieli (2002). Direct Comparison of Neural Systems Mediating Conscious and Unconscious Skill Learning. Journal of Neurophysiology 88 (3):1451-1460.score: 210.0
  5. Alfred H. Fuchs (1962). The Progression-Regression Hypotheses in Perceptual-Motor Skill Learning. Journal of Experimental Psychology 63 (2):177.score: 210.0
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  6. Ágnes Lukács & Ferenc Kemény (2014). Development of Different Forms of Skill Learning Throughout the Lifespan. Cognitive Science 38 (8).score: 192.0
    The acquisition of complex motor, cognitive, and social skills, like playing a musical instrument or mastering sports or a language, is generally associated with implicit skill learning (SL). Although it is a general view that SL is most effective in childhood, and such skills are best acquired if learning starts early, this idea has rarely been tested by systematic empirical studies on the developmental pathways of SL from childhood to old age. In this paper, we challenge the view (...)
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  7. Ron Sun, Todd Peterson & Edward Merrill, A Bottom-Up Model of Skill Learning.score: 180.0
    We present a skill learning model CLARION. Different from existing models of high-level skill learning that use a topdown approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. CLAR- ION is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line learning. We compare the model with human data in a minefield navigation task. A (...)
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  8. Ron Sun (2005). The Interaction of the Explicit and the Implicit in Skill Learning: A Dual-Process Approach. Psychological Review 112:159-192.score: 180.0
    This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A (...)
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  9. Ron Sun, Todd Peterson & Edward Merrill, Bottom-Up Skill Learning in Reactive Sequential Decision Tasks.score: 180.0
    This paper introduces a hybrid model that unifies connectionist, symbolic, and reinforcement learning into an integrated architecture for bottom-up skill learning in reactive sequential decision tasks. The model is designed for an agent to learn continuously from on-going experience in the world, without the use of preconceived concepts and knowledge. Both procedural skills and high-level knowledge are acquired through an agent’s experience interacting with the world. Computational experiments with the model in two domains are reported.
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  10. Ron Sun, Skill Learning Using A Bottom-Up Hybrid Model.score: 180.0
    top-down approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward lowlevel skill learning, where procedural knowledge develops rst and declarative knowledge develops from it. Clarionwhich follows this approach is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line learning. We compare the model with human data in a mine eld navigation task. A match between the model and human data is observed in several comparisons.
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  11. Lawrence Karlin & Rudolf G. Mortimer (1963). Effect of Verbal, Visual, and Auditory Augmenting Cues on Learning a Complex Motor Skill. Journal of Experimental Psychology 65 (1):75.score: 180.0
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  12. Lawrence Karlin & Rudolf G. Mortimer (1962). Effects of Visual and Verbal Cues on Learning a Motor Skill. Journal of Experimental Psychology 64 (6):608.score: 180.0
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  13. Katherine E. Baker, Ruth C. Wylie & Robert M. Gagné (1951). The Effects of an Interfering Task on the Learning of a Complex Motor Skill. Journal of Experimental Psychology 41 (1):1.score: 168.0
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  14. Edward A. Bilodeau & Ina McD Bilodeau (1958). Variable Frequency of Knowledge of Results and the Learning of a Simple Skill. Journal of Experimental Psychology 55 (4):379.score: 168.0
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  15. Kenneth A. Blick & Edward A. Bilodeau (1963). Interpolated Activity and the Learning of a Simple Skill. Journal of Experimental Psychology 65 (5):515.score: 168.0
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  16. Ellen Fridland (2014). Skill Learning and Conceptual Thought: Making Our Way Through the Wilderness. In Bana Bashour Hans Muller (ed.), Contemporary Philosophical Naturalism and Its Implications. Routledge.score: 162.0
  17. Ellen Fridland (2013). Imitation, Skill Learning, and Conceptual Thought: An Embodied, Developmental Approach. In Liz Swan (ed.), Origins of Mind. 203--224.score: 162.0
  18. Luca A. Finelli & Terrence J. Sejnowski (2005). What is Consolidated During Sleep-Dependent Motor Skill Learning? Behavioral and Brain Sciences 28 (1):70-71.score: 162.0
    Learning procedural skills involves improvement in speed and accuracy. Walker proposes two stages of memory consolidation: enhancement, which requires sleep, and stabilization, which does not require sleep. Speed improvement for a motor learning task but not accuracy occurs after sleep-dependent enhancement. We discuss this finding in the context of computational models and underlying sleep mechanisms.
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  19. Rose Martini Diane M. Ste-Marie, Kelly Vertes, Amanda M. Rymal (2011). Feedforward Self-Modeling Enhances Skill Acquisition in Children Learning Trampoline Skills. Frontiers in Psychology 2.score: 156.0
    The purpose of this research was to examine whether children would benefit from a feedforward self-modeling (FSM) video and to explore possible explanatory mechanisms for the potential benefits, using a self-regulation framework. To this end, children were involved in learning two five-skill trampoline routines. For one of the routines, a FSM video was provided during acquisition, whereas only verbal instructions were provided for the alternate routine. The FSM involved editing video footage such that it showed the learner performing the (...)
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  20. Edward Merrillb & Todd Petersonb (2001). From Implicit Skills to Explicit Knowledge: A Bottom‐Up Model of Skill Learning. Cognitive Science 25 (2):203-244.score: 150.0
  21. Ron Sun, Top-Down Versus Bottom-Up Learning in Cognitive Skill Acquisition.score: 150.0
    This paper explores the interaction between implicit and explicit processes during skill learning, in terms of top-down learning (that is, learning that goes from explicit to implicit knowledge) versus bottom-up learning (that is, learning that goes from implicit to explicit knowledge). Instead of studying each type of knowledge (implicit or explicit) in isolation, we stress the interaction between the two types, especially in terms of one type giving rise to the other, and its effects on (...)
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  22. M. E. Raichle (2000). The Neural Correlates of Consciousness: An Analysis of Cognitive Skill Learning. In Michael S. Gazzaniga (ed.), The New Cognitive Neurosciences: 2nd Edition. Mit Press.score: 150.0
  23. Ellen Fridland (2013). 6 Skill Learning and Conceptual Thought. In Bana Bashour Hans Muller (ed.), Contemporary Philosophical Naturalism and its Implications. Routledge. 13--77.score: 150.0
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  24. Rieger Jochem (2011). Motor Skill Learning is Accompanied by Changes of Neuronal Network Dynamics in the Theta and High-Gamma Range. Frontiers in Human Neuroscience 5.score: 150.0
  25. Robrecht Prd van der Wel, Natalie Sebanz & Guenther Knoblich (2012). The Sense of Agency During Skill Learning in Individuals and Dyads. Consciousness and Cognition 21 (3):1267-1279.score: 150.0
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  26. Richard A. Carlson (2003). Skill Learning. In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.score: 150.0
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  27. A. F. Healy (2009). Skill Learning, Enhancement Of. In Hal Pashler (ed.), Encyclopedia of the Mind. Sage Publications.score: 150.0
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  28. Penhune Virginia (2009). Developmental Contributions to Human Motor Skill Learning. Frontiers in Human Neuroscience 3.score: 150.0
  29. Cj Winstein & Ra Schmidt (1987). Relative Frequency of Knowledge of Results and Complex Motor Skill Learning. Bulletin of the Psychonomic Society 25 (5):328-328.score: 150.0
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  30. B. Scott & A. Bansal (2013). A Cybernetic Computational Model for Learning and Skill Acquisition. Constructivist Foundations 9 (1):125-136.score: 144.0
    Context: Although there are rich descriptive accounts of skill acquisition in the literature, there are no satisfactory explanatory models of the cognitive processes involved. Problem: The aim of the paper is to explain some key phenomena frequently observed in the acquisition of motor skills: the loss of conscious access to knowledge of the structure of a skill and the awareness that an error has been made prior to the receipt of knowledge of results. Method: In the 1970s, the first author (...)
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  31. Oskar Lindwall & Anna Ekström (2012). Instruction-in-Interaction: The Teaching and Learning of a Manual Skill. [REVIEW] Human Studies 35 (1):27-49.score: 138.0
    This study takes an interest in instructions and instructed actions in the context of manual skills. The analysis focuses on a video recorded episode where a teacher demonstrates how to crochet chain stitches, requests a group of students to reproduce her actions, and then repeatedly corrects the attempts of one of the students. The initial request, and the students’ responses to it, could be seen as preliminary to the series of corrective sequences that come next: the request and the following (...)
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  32. Øyvind F. Standal (2011). Re-Embodiment: Incorporation Through Embodied Learning of Wheelchair Skills. [REVIEW] Medicine, Health Care and Philosophy 14 (2):177-184.score: 132.0
    In this article, the notion of re-embodiment is developed to include the ways that rearrangement and renewals of body schema take place in rehabilitation. More specifically, the embodied learning process of acquiring wheelchair skills serves as a starting point for fleshing out a phenomenological understanding of incorporation of assistive devices. By drawing on the work of Merleau-Ponty, the reciprocal relation between acquisition habits and incorporation of instruments is explored in relation to the learning of wheelchair skills. On the (...)
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  33. Johan M. Koedijker, Jamie M. Poolton, Jonathan P. Maxwell, Raôul R. D. Oudejans, Peter J. Beek & Rich S. W. Masters (2011). Attention and Time Constraints in Perceptual-Motor Learning and Performance: Instruction, Analogy, and Skill Level. Consciousness and Cognition 20 (2):245-256.score: 120.0
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  34. Paul Hager (2004). Front-Loading, Workplace Learning and Skill Development. Educational Philosophy and Theory 36 (5):523–534.score: 120.0
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  35. Clare MacMahon Ian Tobias Fuelscher, Kevin Ball (2012). Perspectives on Learning Styles in Motor and Sport Skills. Frontiers in Psychology 3.score: 120.0
    We present the perspective that while coaches and instructors commonly adapt learning styles to maximise training outcomes, there has been little to no empirical support for the efficacy of this practice. Learning styles is a learner’s preferred mode (e.g. visual, verbal) of taking in and processing new information. Although it is a relevant topic for the learning of motor and sport skills, few studies have used an appropriate methodology to test the effectiveness of learning style-based instruction. (...)
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  36. Susan L. Epstein (1994). For the Right Reasons: The FORR Architecture for Learning in a Skill Domain. Cognitive Science 18 (3):479-511.score: 120.0
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  37. R. A. Magill & Kj Green (1989). Implicit Learning in a Complex Tracking Skill. Bulletin of the Psychonomic Society 27 (6):488-488.score: 120.0
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  38. Dezso Nemeth, Karolina Janacsek, Katalin Király, Zsuzsa Londe, Kornél Németh, Kata Fazekas, Ilona Adam, Elemérné Király & Attila Csányi (2013). Probabilistic Sequence Learning in Mild Cognitive Impairment. Frontiers in Human Neuroscience 7.score: 120.0
    Mild Cognitive Impairment (MCI) causes slight but noticeable disruption in cognitive systems, primarily executive and memory functions. However, it is not clear if the development of sequence learning is affected by an impaired cognitive system and, if so, how. The goal of our study was to investigate the development of probabilistic sequence learning, from the initial acquisition to consolidation, in MCI and healthy elderly control groups. We used the Alternating Serial Reaction Time task (ASRT) to measure probabilistic sequence (...)
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  39. Ida Selbing, Björn Lindström & Andreas Olsson (2014). Demonstrator Skill Modulates Observational Aversive Learning. Cognition 133 (1):128-139.score: 120.0
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  40. Diane M. Ste-Marie, Kelly Vertes, Amanda M. Rymal & Rose Martini (2011). Feedforward Self-Modeling Enhances Skill Acquisition in Children Learning Trampoline Skills. Frontiers in Psychology 2:155.score: 120.0
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  41. Britne Shabbott, Roshni Ravindran, Joseph W. Schumacher, Paula B. Wasserman, Karen S. Marder & Pietro Mazzoni (2013). Learning Fast Accurate Movements Requires Intact Frontostriatal Circuits. Frontiers in Human Neuroscience 7.score: 108.0
    The basal ganglia are known to play a crucial role in movement execution, but their importance for motor skill learning remains unclear. Obstacles to our understanding include the lack of a universally accepted definition of motor skill learning (definition confound), and difficulties in distinguishing learning deficits from execution impairments (performance confound). We studied how healthy subjects and subjects with a basal ganglia disorder learn fast accurate reaching movements, and we addressed the definition and performance confounds by: 1) (...)
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  42. Mohan Matthen (forthcoming). Play, Skill, and the Origins of Perceptual Art. British Journal of Aesthetics.score: 102.0
    Art is universal across cultures. Yet, it is biologically expensive because of the energy expended and reduced vigilance. Why do humans make and contemplate it? This paper advances a thesis about the psychological origins of perceptual art. First, it delineates the aspects of art that need explaining: not just why it is attractive, but why fine execution and form—which have to do with how the attraction is achieved—matter over and above attractiveness. Second, it states certain constraints: we need to explain (...)
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  43. Alexander Renkl (2014). Toward an Instructionally Oriented Theory of Example‐Based Learning. Cognitive Science 38 (1):1-37.score: 102.0
    Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from worked examples, observational learning, and analogical reasoning. This theory has descriptive and prescriptive elements. The descriptive subtheory deals with (a) the relevance and effectiveness of examples, (b) (...)
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  44. L. Andrew Coward & Ron Sun (2004). Criteria for an Effective Theory of Consciousness and Some Preliminary Attempts. Consciousness and Cognition 13 (2):268-301.score: 90.0
    In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...)
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  45. Gary F. Marcus (2012). Musicality: Instinct or Acquired Skill? Topics in Cognitive Science 4 (4):498-512.score: 90.0
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  46. Dario D. Salvucci (2013). Integration and Reuse in Cognitive Skill Acquisition. Cognitive Science 37 (5):829-860.score: 84.0
    Previous accounts of cognitive skill acquisition have demonstrated how procedural knowledge can be obtained and transformed over time into skilled task performance. This article focuses on a complementary aspect of skill acquisition, namely the integration and reuse of previously known component skills. The article posits that, in addition to mechanisms that proceduralize knowledge into more efficient forms, skill acquisition requires tight integration of newly acquired knowledge and previously learned knowledge. Skill acquisition also benefits from reuse of existing knowledge across disparate (...)
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  47. Magda Osman, Positive Transfer and Negative Transfer/Anti-Learning of Problem Solving Skills.score: 84.0
    In problem solving research insights into the relationship between monitoring and control in the transfer of complex skills remain impoverished. To address this, in four experiments participants solved two complex control tasks that were identical in structure but varied in presentation format. Participants learnt either to solve the second task, based on their original learning phase from the first task, or learnt to solve the second task, based on another participant’s learning phase. Experiment 1 showed that, under conditions (...)
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  48. Christian P. Janssen & Wayne D. Gray (2012). When, What, and How Much to Reward in Reinforcement Learning-Based Models of Cognition. Cognitive Science 36 (2):333-358.score: 84.0
    Reinforcement learning approaches to cognitive modeling represent task acquisition as learning to choose the sequence of steps that accomplishes the task while maximizing a reward. However, an apparently unrecognized problem for modelers is choosing when, what, and how much to reward; that is, when (the moment: end of trial, subtask, or some other interval of task performance), what (the objective function: e.g., performance time or performance accuracy), and how much (the magnitude: with binary, categorical, or continuous values). In (...)
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  49. Dagmar Sternad Masaki O. Abe (2013). Directionality in Distribution and Temporal Structure of Variability in Skill Acquisition. Frontiers in Human Neuroscience 7.score: 84.0
    Observable structure of variability presents a window into the underlying processes of skill acquisition, especially when the task affords a manifold of solutions to the desired task result. This study examined skill acquisition by analyzing variability in both its distributional and temporal structure. Using a virtual throwing task, data distributions were analyzed by the TNC-method (Tolerance, Noise, Covariation); the temporal structure was quantified by autocorrelation and detrended fluctuation analysis. We tested four hypotheses: 1) Tolerance and Covariation, not Noise, are major (...)
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  50. Ross Roberts Gavin Lawrence, Nichola Callow (2013). Watch Me If You Can: Imagery Ability Moderates Observational Learning Effectiveness. Frontiers in Human Neuroscience 7.score: 84.0
    Recent research has revealed similarities in brain activity during observational learning and motor execution. However, whilst action develops visual, motor and afferent representations during acquisition, action-observation has been proposed to only develop visual-spatial learning via visual representation. In addition, it has been suggested that the vividness of visual representations are determined by imagery ability. Thus, the purpose of the current investigation was to explore the possible moderating role of imagery ability in the effectiveness of observational learning. Participants (...)
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