Implications of search accuracy for serial self-terminating models of search
Implications of search accuracy for serial self-terminating models of search
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DOI：
10.1080/13506280444000788
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发表时间：
2005-10-01
期刊：
影响因子：
2
通讯作者：
Klein, RM
中科院分区：
文献类型：
--
作者：
Dukewich, KR;Klein, RM
在两个实验中，共有35名参与者的数据与两个相互竞争的序列搜索模型的预测结果进行了比较，其中一个具有完美记忆，另一个没有记忆。反应时间从无限暴露时间，4-alternative，目标识别搜索任务中收集，数组大小为8,12或16项。从RT与干扰物数量的线性函数出发，在SSTS假设下，计算出假设的“检查时间/项目”。使用相同的显示器从相同的参与者获得目标识别准确性，但使用前和后面罩来限制总检查时间（到120,180,300和540英寸）。有内存模型和无内存模型都没有提供足够好的数据拟合来支持串行检查是决定搜索时间的主要过程的假设。尽管有直接证据表明在视觉搜索中存在连续的注意力分配，但这些结果表明，学者们应该认真考虑串行和并行策略共同作用的混合搜索模型的可能性。
In two experiments, the data from a total of 35 participants was compared to predictions from two competing serial search models, one with perfect memory and one with no memory. Reaction times were collected from an unlimited exposure duration, 4-alternative, target identification search task with array sizes of 8, 12, or 16 items. From the linear function relating RT to number of distractors a hypothetical "inspection time/item" was computed under the assumption of SSTS. Target identification accuracy was obtained from the same participants using the same displays, but with pre- and post-masks used to limit total inspection time (to 120, 180, 300, and 540 ins). Neither the memoryful nor memoryless model provided a good enough fit to the data to support the assumption that serial inspection is the primary process determining search time. Despite direct evidence for serial allocation of attention in visual search, these results suggest that scholars should seriously consider the possibility of hybrid search models in which serial and parallel strategies operate jointly.