Probability Prediction in Children with ASD


Individuals with Autism Spectrum Disorder (ASD) often struggle with making inductive generalizations. Yet for typically developing children, the capacity to make such generalizations is a hallmark of human learning. This ability requires some understanding of “intuitive statistics” (i.e., the understanding that there is a relationship between samples and populations), which have been previously demonstrated to emerge early on in infancy. We hypothesized that the challenges with inductive generalization among the ASD population may have its roots in weaknesses in probabilistic reasoning. In the current study, we gave children with ASD a probability prediction task adapted from the method used with infants in Teglas et al. (2007), and our results over two experiments with two groups (one from the U.S. and one from Singapore) suggest that compared with typically developing children, children with autism may have difficulties in engaging in probabilistic reasoning.

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