When correlation equals causation: A behavioral and computational account of second-order correlation learning in children.
Clicks: 147
ID: 204869
2020
We examined 2- and 3-year-old children's ability to use second-order correlation learning-in which a learned correlation between two pairs of features (e.g., A and B, A and C) is generalized to the noncontiguous features (i.e., B and C)-to make causal inferences. Previous findings showed that 20- and 26-month-old children can use second-order correlation learning to learn about static and dynamic features in category and noncategory contexts. The current behavioral study and computational model extend these findings to show that 2- and 3-year-olds can detect the second-order correlation between an object's surface feature and its capacity to activate a novel machine, but only if the children had encoded the first-order correlations on which the second-order correlation was based. These results have implications for children's developing information-processing capacities on their ability to use second-order correlations to infer causal relations in the world.
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| Authors | Benton, Deon T;Rakison, David H;Sobel, David M; |
| Journal | journal of experimental child psychology |
| Year | 2020 |
| DOI | S0022-0965(20)30462-8 |
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