Marsh Jessecae K, Ahn Woo-Kyoung
Department of Psychology, Texas Tech University, Lubbock, TX 79409-2051, USA.
J Exp Psychol Learn Mem Cogn. 2009 Mar;35(2):334-52. doi: 10.1037/a0014929.
Existing models of causal induction primarily rely on the contingency between the presence and the absence of a causal candidate and an effect. Yet, classification of observations into these four types of covariation data may not be straightforward because (a) most causal candidates, in real life, are continuous with ambiguous, intermediate values and because (b) effects may unfold after some temporal lag, providing ambiguous contingency information. Although past studies suggested various reasons why ambiguous information may not be used during causal induction, the authors examined whether learners spontaneously use ambiguous information through a process called causal assimilation. In particular, the authors examined whether learners willingly place ambiguous observations into one of the categories relevant to the causal hypothesis, in accordance with their current causal beliefs. In Experiment 1, people's frequency estimates of contingency data reflected that information ambiguous along a continuous quantity dimension was spontaneously categorized and assimilated in a causal induction task. This assimilation process was moderated by the strength of the upheld causal hypothesis (Experiment 2), could alter the overall perception of a causal relationship (Experiment 3), and could occur over temporal sequences (Experiment 4).
现有的因果归纳模型主要依赖于因果候选因素的出现与缺失和结果之间的偶然性。然而,将观察结果分类为这四种共变数据类型可能并非易事,原因如下:(a) 在现实生活中,大多数因果候选因素都是连续的,具有模糊的中间值;(b) 结果可能在一段时间后才显现,从而提供模糊的偶然性信息。尽管过去的研究提出了各种关于在因果归纳过程中模糊信息可能未被使用的原因,但作者通过一个称为因果同化的过程,研究了学习者是否会自发地使用模糊信息。具体而言,作者研究了学习者是否会根据他们当前的因果信念,自愿将模糊的观察结果归入与因果假设相关的类别之一。在实验1中,人们对偶然性数据的频率估计表明,在因果归纳任务中,沿着连续数量维度模糊的信息会被自发地分类和同化。这一同化过程受到所坚持的因果假设强度的调节(实验2),会改变对因果关系的整体认知(实验3),并且会在时间序列中发生(实验4)。