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使用过程分离法进行序列学习时自动加工的证据。

Evidence of automatic processing in sequence learning using process-dissociation.

作者信息

Mong Heather M, McCabe David P, Clegg Benjamin A

机构信息

Department of Psychology, Colorado State University, Fort Collins, CO, USA.

出版信息

Adv Cogn Psychol. 2012;8(2):98-108. doi: 10.2478/v10053-008-0107-z. Epub 2012 May 21.

Abstract

This paper proposes a way to apply process-dissociation to sequence learning in addition and extension to the approach used by Destrebecqz and Cleeremans (2001). Participants were trained on two sequences separated from each other by a short break. Following training, participants self-reported their knowledge of the sequences. A recognition test was then performed which required discrimination of two trained sequences, either under the instructions to call any sequence encountered in the experiment "old" (the inclusion condition), or only sequence fragments from one half of the experiment "old" (the exclusion condition). The recognition test elicited automatic and controlled process estimates using the process dissociation procedure, and suggested both processes were involved. Examining the underlying processes supporting performance may provide more information on the fundamental aspects of the implicit and explicit constructs than has been attainable through awareness testing.

摘要

本文提出了一种将过程分离应用于序列学习的方法,这是对德斯特雷贝克兹和克莱尔曼斯(2001年)所采用方法的补充和扩展。参与者接受了两个序列的训练,两个序列之间有短暂的休息间隔。训练后,参与者自行报告他们对序列的了解情况。然后进行了一项识别测试,要求在以下两种指令下辨别两个训练过的序列:一是将实验中遇到的任何序列都称为“旧的”(包含条件),二是仅将实验一半的序列片段称为“旧的”(排除条件)。识别测试使用过程分离程序得出自动和受控过程的估计值,并表明这两个过程都参与其中。与通过意识测试所能获得的信息相比,研究支持表现的潜在过程可能会提供有关内隐和外显结构基本方面的更多信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9d0/3367867/52c95917e342/acp-08-098-g001.jpg

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