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个体差异预测低发生率视觉搜索表现和错误来源:一项眼动追踪研究。

Individual differences predict low prevalence visual search performance and sources of errors: An eye-tracking study.

机构信息

Department of Psychology, Michigan State University.

出版信息

J Exp Psychol Appl. 2020 Dec;26(4):646-658. doi: 10.1037/xap0000273. Epub 2020 Apr 20.

Abstract

Targets in real-world visual search tasks, such as baggage screening, may appear on as few as 2% of searches (Hofer & Schwaninger, 2005). Rare targets are missed more frequently than common targets, a phenomenon known as the . Given the importance of rare target detection, researchers have sought to increase performance through technological improvements, experimental manipulations, and individual differences approaches. Here we focus on the individual differences approach, which has shown that it is possible to predict an individual's low prevalence search accuracy in a T among Ls search using basic cognitive tasks. Here, we address limitations of previous work by using both basic Ts and Ls and more representative baggage screening items. Results show we can account for 53% of variance in low prevalence search accuracy. Eye-tracking results show that fluid intelligence and near transfer search performance predict selection errors (misses caused by never inspecting the target) while working memory capacity and near transfer search performance predict identification errors (misses caused by misidentifying an inspected target). We conclude that the individual differences approach can be an effective tool to select who will perform well in real-world searches. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

摘要

在现实世界的视觉搜索任务中,目标(如行李检查)可能只出现在 2%的搜索中(Hofer 和 Schwaninger,2005)。罕见目标比常见目标更容易被错过,这一现象被称为“罕见目标效应”。鉴于罕见目标检测的重要性,研究人员通过技术改进、实验操作和个体差异方法来寻求提高性能。在这里,我们关注个体差异方法,该方法表明,使用基本认知任务,有可能预测个体在 T 中搜索 L 时的低患病率搜索准确性。在这里,我们通过使用基本 T 和 L 以及更具代表性的行李检查项目来解决以前工作的局限性。结果表明,我们可以解释低患病率搜索准确性的 53%的方差。眼动追踪结果表明,流体智力和近迁移搜索表现预测选择错误(由于从未检查目标而导致的错过),而工作记忆容量和近迁移搜索表现预测识别错误(由于错误识别检查过的目标而导致的错过)。我们得出结论,个体差异方法可以成为一种有效的工具,用于选择在现实世界搜索中表现良好的人。(PsycInfo 数据库记录(c)2020 APA,保留所有权利)。

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