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注意不一定总是适用:心流阻碍了显式但不阻碍内隐序列学习。

Attention need not always apply: Mind wandering impedes explicit but not implicit sequence learning.

机构信息

Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.

Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.

出版信息

Cognition. 2021 Apr;209:104530. doi: 10.1016/j.cognition.2020.104530. Epub 2020 Dec 28.

DOI:10.1016/j.cognition.2020.104530
PMID:33383469
Abstract

According to the attentional resources account, mind wandering (or "task-unrelated thought") is thought to compete with a focal task for attentional resources. Here, we tested two key predictions of this account: First, that mind wandering should not interfere with performance on a task that does not require attentional resources; second, that as task requirements become automatized, performance should improve and depth of mind wandering should increase. Here, we used a serial reaction time task with implicit- and explicit-learning groups to test these predictions. Providing novel evidence for the attentional resource account's first prediction, results indicated that depth of mind wandering was negatively associated with learning in the explicit, but not the implicit, group, indicating that mind wandering is associated with impaired explicit, but not implicit, learning. Corroborating the attention resource account's second prediction, we also found that, overall, performance improved while at the same time depth of mind wandering increased. From an implicit-learning perspective, these results are consistent with the claim that explicit learning is impaired under attentional load, but implicit learning is not. Data, analysis code, manuscript preparation code, and pre-print available at osf.io/qzry7/.

摘要

根据注意力资源理论,思维漫游(或“与任务无关的思维”)被认为与焦点任务争夺注意力资源。在这里,我们检验了该理论的两个关键预测:首先,思维漫游不应干扰不需要注意力资源的任务的表现;其次,随着任务要求变得自动化,表现应该提高,思维漫游的深度也应该增加。在这里,我们使用了一个具有内隐和外显学习组的序列反应时间任务来检验这些预测。为注意力资源理论的第一个预测提供了新的证据,结果表明,在显式学习组中,思维漫游的深度与学习呈负相关,而在隐式学习组中则没有,这表明思维漫游与显式学习的受损有关,而与隐式学习无关。与注意力资源理论的第二个预测相符,我们还发现,总体而言,表现提高的同时,思维漫游的深度也增加了。从内隐学习的角度来看,这些结果与注意力负荷下外显学习受损而内隐学习不受影响的观点是一致的。数据、分析代码、手稿准备代码和预印本可在 osf.io/qzry7/ 获得。

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