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Deon T. Benton; David Kamper; Rebecca M. Beaton; David M. Sobel – Developmental Science, 2024
Causal reasoning is a fundamental cognitive ability that enables individuals to learn about the complex interactions in the world around them. However, the mechanisms that underpin causal reasoning are not well understood. For example, it remains unresolved whether children's causal inferences are best explained by Bayesian inference or…
Descriptors: Preschool Children, Thinking Skills, Associative Learning, Abstract Reasoning
Minju Kim; Adena Schachner – Developmental Science, 2025
Listening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children…
Descriptors: Causal Models, Abstract Reasoning, Thinking Skills, Music
Verhaar, Erik; Medendorp, Wijbrand Pieter; Hunnius, Sabine; Stapel, Janny C. – Developmental Science, 2022
If cues from different sensory modalities share the same cause, their information can be integrated to improve perceptual precision. While it is well established that adults exploit sensory redundancy by integrating cues in a Bayes optimal fashion, whether children under 8 years of age combine sensory information in a similar fashion is still…
Descriptors: Bayesian Statistics, Causal Models, Statistical Inference, Visual Perception
Johnston, Angie M.; Johnson, Samuel G. B.; Koven, Marissa L.; Keil, Frank C. – Developmental Science, 2017
Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists--such as Einstein--do? Four experiments support the latter possibility. In particular, we…
Descriptors: Young Children, Thinking Skills, Inferences, Bayesian Statistics
Piantadosi, Steven T.; Kidd, Celeste; Aslin, Richard – Developmental Science, 2014
Studies of infant looking times over the past 50 years have provided profound insights about cognitive development, but their dependent measures and analytic techniques are quite limited. In the context of infants' attention to discrete sequential events, we show how a Bayesian data analysis approach can be combined with a rational cognitive…
Descriptors: Infants, Eye Movements, Infant Behavior, Cognitive Development
Hamlin, J. Kiley; Ullman, Tomer; Tenenbaum, Josh; Goodman, Noah; Baker, Chris – Developmental Science, 2013
Evaluating individuals based on their pro- and anti-social behaviors is fundamental to successful human interaction. Recent research suggests that even preverbal infants engage in social evaluation; however, it remains an open question whether infants' judgments are driven uniquely by an analysis of the mental states that motivate others' helpful…
Descriptors: Infants, Social Cognition, Bayesian Statistics, Infant Behavior
Xu, Fei; Tenenbaum, Joshua B. – Developmental Science, 2007
We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable of learning word meanings across a wide range of communicative contexts. In different contexts, learners may encounter different sampling processes generating the examples…
Descriptors: Semantics, Bayesian Statistics, Sampling, Inferences