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首页> 外文期刊>The quarterly journal of experimental psychology: QJEP >Goal relevance and artificial grammar learning
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Goal relevance and artificial grammar learning

机译：目标相关性和人工语法学习

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This investigation used a newly developed artificial grammar learning (AGL) paradigm in which par-ticipants were exposed to sequences of stimuli that varied in two dimensions (colours and letters) thatwere superimposed on each other. Variation within each dimension was determined by a differentgrammar. The results of two studies strongly suggest that implicit learning in AGL depends onthe goal relevance of the to-be-learned dimension. Specifically, when only one of the two stimulusdimensions was relevant for their task (Experiment 1) participants learned the structure underlyingthe relevant, but not that of the irrelevant dimension. However, when both dimensions were relevant,both structures were learned (Experiment 2). These findings suggest that implicit learning occurs onlyin dimensions to which we are attuned. Based on the present results and on those of Eitam, Hassin,and Schul (2008) we suggest that focusing on goal relevance may provide new insights into the mech-anisms underlying implicit learning.
机译：这项研究使用了新开发的人工语法学习（AGL）范式，其中参与者被暴露于彼此重叠的二维（颜色和字母）变化的刺激序列中。每个维度内的差异由不同的语法确定。两项研究的结果强烈表明，AGL中的隐式学习取决于要学习的维度的目标相关性。具体而言，当两个刺激维度中的一个与他们的任务相关时（实验1），参与者就会了解相关的基础结构，而不是无关紧要的维度。然而，当两个维度都相关时，两个结构都被学习了（实验2）。这些发现表明，隐性学习仅发生在我们所适应的维度上。根据目前的结果以及Eitam，Hassin和Schul（2008）的结果，我们建议关注目标相关性可能会为隐性学习背后的机制提供新的见解。

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