心理学
语义推理机
变量(数学)
心理信息
随意的
认知心理学
集合(抽象数据类型)
鉴定(生物学)
因果推理
因果模型
因果推理
发展心理学
因果关系(物理学)
认知
计算机科学
人工智能
梅德林
计量经济学
经济
政治学
数学
法学
程序设计语言
材料科学
植物
量子力学
神经科学
生物
复合材料
病理
数学分析
物理
医学
作者
Mariel K. Goddu,Alison Gopnik
摘要
Novel causal systems pose a problem of variable choice: How can a reasoner decide which variable is causally relevant? Which variable in the system should a learner manipulate to try to produce a desired, yet unfamiliar, casual outcome? In much causal reasoning research, participants learn how a particular set of preselected variables produce a particular effect. Here, we investigate 3- to 5-year-olds' ability to select the relevant variable for intervention in a novel causal system. Results demonstrate that even young children can learn which variable is causally relevant from sparse evidence. In particular, children infer that variables that are "difference-making" in one causal system will also be relevant to other, novel, causal problems. If manipulating a causal variable in a particular way leads to one effect, children assume that other manipulations of that variable will lead to other novel effects. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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