Poznanski Yael, Tzelgov Joseph
Achva Academic College, Shikmim, Israel.
Q J Exp Psychol (Hove). 2010 Aug;63(8):1495-515. doi: 10.1080/17470210903398121. Epub 2010 Jan 8.
The aim of this study was to conceptualize artificial grammar learning (AGL) in terms of two orthogonal dimensions--the mode of knowledge acquisition and the mode of knowledge retrieval--as was done by Perlman and Tzelgov (2006) for sequence learning. Experiment 1 was carried out to validate our experimental task; Experiments 2-4 tested, respectively, performance in the intentional, incidental, and automatic retrieval modes, for each of the three modes of acquisition. Furthermore, signal detection theory (SDT) was used as an analytic tool, consistent with our assumption that the processing of legality-relevant information involves decisions along a continuous dimension of fluency. The results presented support the analysis of AGL in terms of the proposed dimensions. They also indicate that knowledge acquired during training may include many aspects of the presented stimuli (whole strings, relations among elements, etc.). The contribution of the various components to performance depends on both the specific instruction in the acquisition phase and the requirements of the retrieval task.
本研究的目的是按照两个相互正交的维度——知识获取模式和知识检索模式，对人工语法学习（AGL）进行概念化，就像佩尔曼和策尔戈夫（2006）对序列学习所做的那样。进行了实验1以验证我们的实验任务；实验2至4分别测试了三种获取模式中每种模式在有意、偶然和自动检索模式下的表现。此外，信号检测理论（SDT）被用作一种分析工具，这与我们的假设一致，即与合法性相关信息的处理涉及沿流畅性连续维度做出的决策。呈现的结果支持按照所提出的维度对AGL进行分析。它们还表明，训练期间获得的知识可能包括所呈现刺激的许多方面（整个字符串、元素之间的关系等）。各个组成部分对表现的贡献取决于获取阶段的具体指导以及检索任务的要求。
