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视觉搜索中的自动化与训练

Automatization and training in visual search.

作者信息

Czerwinski M, Lightfoot N, Shiffrin R M

机构信息

Compaq Computer Corporation.

出版信息

Am J Psychol. 1992 Summer;105(2):271-315.

PMID:1621883
Abstract

In several search tasks, the amount of practice on particular combinations of targets and distractors was equated in varied-mapping (VM) and consistent-mapping (CM) conditions. The results indicate the importance of distinguishing between memory and visual search tasks, and implicate a number of factors that play important roles in visual search and its learning. Visual search was studied in Experiment 1. VM and CM performance were almost equal, and slope reductions occurred during practice for both, suggesting the learning of efficient attentive search based on features, and no important role for automatic attention attraction. However, positive transfer effects occurred when previous CM targets were re-paired with previous CM distractors, even though these targets and distractors had not been trained together. Also, the introduction of a demanding simultaneous task produced advantages of CM over VM. These latter two results demonstrated the operation of automatic attention attraction. Visual search was further studied in Experiment 2, using novel characters for which feature overlap and similarity were controlled. The design and many of the findings paralleled Experiment 1. In addition, enormous search improvement was seen over 35 sessions of training, suggesting the operation of perceptual unitization for the novel characters. Experiment 3 showed a large, persistent advantage for CM over VM performance in memory search, even when practice on particular combinations of targets and distractors was equated in the two training conditions. A multifactor theory of automatization and attention is put forth to account for these findings and others in the literature.

摘要

在若干搜索任务中,在变化映射(VM)和一致映射(CM)条件下,对目标与干扰项的特定组合的练习量是相等的。结果表明区分记忆任务和视觉搜索任务的重要性,并涉及在视觉搜索及其学习中起重要作用的一些因素。实验1对视觉搜索进行了研究。VM和CM的表现几乎相同,并且在练习过程中两者的斜率都降低了,这表明基于特征的高效注意力搜索的学习,且自动注意力吸引没有起到重要作用。然而,当先前的CM目标与先前的CM干扰项重新配对时,即使这些目标和干扰项没有一起训练,也会出现正向迁移效应。此外,引入一项要求较高的同时进行的任务产生了CM相对于VM的优势。后两个结果证明了自动注意力吸引的作用。实验2使用特征重叠和相似性得到控制的新字符对视觉搜索进行了进一步研究。该实验的设计和许多发现与实验1相似。此外,在35节训练课程中观察到了巨大的搜索改进,这表明对新字符进行了感知单元化操作。实验3表明,在记忆搜索中,CM的表现相对于VM具有很大且持久的优势,即使在两种训练条件下对目标与干扰项的特定组合的练习量是相等的。本文提出了一种自动化和注意力的多因素理论来解释这些发现以及文献中的其他发现。

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