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量化感知运动序列学习后的迁移:内隐学习有多不灵活?

Quantifying transfer after perceptual-motor sequence learning: how inflexible is implicit learning?

作者信息

Sanchez Daniel J, Yarnik Eric N, Reber Paul J

机构信息

Department of Psychology, Northwestern University, 2029 Sheridan Road, Evanston, IL, 60208, USA.

出版信息

Psychol Res. 2015 Mar;79(2):327-43. doi: 10.1007/s00426-014-0561-9. Epub 2014 Mar 26.

Abstract

Studies of implicit perceptual-motor sequence learning have often shown learning to be inflexibly tied to the training conditions during learning. Since sequence learning is seen as a model task of skill acquisition, limits on the ability to transfer knowledge from the training context to a performance context indicates important constraints on skill learning approaches. Lack of transfer across contexts has been demonstrated by showing that when task elements are changed following training, this leads to a disruption in performance. These results have typically been taken as suggesting that the sequence knowledge relies on integrated representations across task elements (Abrahamse, Jiménez, Verwey, & Clegg, Psychon Bull Rev 17:603-623, 2010a). Using a relatively new sequence learning task, serial interception sequence learning, three experiments are reported that quantify this magnitude of performance disruption after selectively manipulating individual aspects of motor performance or perceptual information. In Experiment 1, selective disruption of the timing or order of sequential actions was examined using a novel response manipulandum that allowed for separate analysis of these two motor response components. In Experiments 2 and 3, transfer was examined after selective disruption of perceptual information that left the motor response sequence intact. All three experiments provided quantifiable estimates of partial transfer to novel contexts that suggest some level of information integration across task elements. However, the ability to identify quantifiable levels of successful transfer indicates that integration is not all-or-none and that measurement sensitivity is a key in understanding sequence knowledge representations.

摘要

内隐感知运动序列学习的研究常常表明,学习在学习过程中与训练条件紧密相连且缺乏灵活性。由于序列学习被视为技能习得的一个典型任务,知识从训练情境迁移到执行情境的能力受限,这表明技能学习方法存在重要限制。通过表明训练后任务元素发生变化时会导致表现中断,已证实了跨情境迁移的缺乏。这些结果通常被认为表明序列知识依赖于跨任务元素的整合表征(亚伯拉罕斯、希门尼斯、韦尔韦和克莱格,《心理通报与评论》17:603 - 623,2010a)。本文报告了三个实验,使用一种相对较新的序列学习任务——连续拦截序列学习,在选择性地操纵运动表现或感知信息的各个方面后,对这种表现中断的程度进行量化。在实验1中,使用一种新颖的反应操作器来检验顺序动作的时间或顺序的选择性干扰,该操作器允许对这两个运动反应成分进行单独分析。在实验2和3中,在选择性地干扰感知信息而保持运动反应序列不变之后,检验迁移情况。所有这三个实验都提供了对向新情境的部分迁移的可量化估计,这表明跨任务元素存在一定程度的信息整合。然而,识别成功迁移的可量化水平的能力表明,整合并非全有或全无,测量敏感性是理解序列知识表征的关键。

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