School of Business and Law, Universitetet i Agder.
Wroclaw Faculty of Psychology, SWPS University of Social Sciences and Humanities.
Cogn Sci. 2022 Apr;46(4):e13132. doi: 10.1111/cogs.13132.
Existing research demonstrates that pre-decisional information sampling strategies are often stable within a given person while varying greatly across people. However, it remains largely unknown what drives these individual differences, that is, why in some circumstances we collect information more idiosyncratically. In this brief report, we present a pre-registered online study of spatial search. Using a novel technique that combines machine-learning dimension reduction and sequence alignment algorithms, we quantify the extent to which the shape and temporal properties of a search trajectory are idiosyncratic. We show that this metric increases (trajectories become more idiosyncratic) when a person is better informed about the likely location of the search target, while poorly informed individuals seem more likely to resort to default search routines determined bottom-up by the properties of the search field. This shows that when many people independently attempt to solve a task in a similar way, they are not necessarily "onto something."
现有研究表明，在给定的个体中，决策前信息采样策略往往是稳定的，而在不同个体之间则有很大的差异。然而，这些个体差异的驱动因素在很大程度上仍不清楚，也就是说，为什么在某些情况下我们会更独特地收集信息。在本简要报告中，我们展示了一项关于空间搜索的预先注册在线研究。我们使用一种新的技术，结合机器学习降维和序列对齐算法，量化了搜索轨迹的形状和时间特性的独特程度。我们表明，当一个人对搜索目标的可能位置有更好的了解时，这个度量值会增加（轨迹变得更加独特），而信息不足的个体似乎更有可能依赖于由搜索场的属性决定的默认搜索例程。这表明，当许多人以类似的方式独立尝试解决任务时，他们并不一定“有头绪”。
