Much research on cognitive development focuses either on early-emerging domain-specific knowledge or domain-general learning mechanisms. However, little research examines how these sources of knowledge interact. Previous research suggests that young infants can make inferences from samples to populations (Xu & Garcia, 2008) and 11- to 12.5-month-old infants can integrate psychological and physical knowledge in probabilistic reasoning (Teglas, Girotto, Gonzalez, & Bonatti, 2007; Xu & Denison, 2009). Here, we ask whether infants can integrate a physical constraint of immobility into a statistical (...) inference mechanism. Results from three experiments suggest that, first, infants were able to use domain-specific knowledge to override statistical information, reasoning that sometimes a physical constraint is more informative than probabilistic information. Second, we provide the first evidence that infants are capable of applying domain-specific knowledge in probabilistic reasoning by using a physical constraint to exclude one set of objects while computing probabilities over the remaining sets. (shrink)

Cognitive Science, Volume 45, Issue 11, November 2021.

The current investigation examines children’s learning about a novel machine in a local history museum. Parent–child dyads were audio-recorded as they navigated an exhibit that contained a novel artifact: a coffee grinder from the turn of the 20th century. Prior to entering the exhibit, children were randomly assigned to receive an experimental “component” prompt that focused their attention on the machine’s internal mechanisms or a control “history” prompt. First, we audio-recorded children and their caregivers while they freely explored the exhibit, (...) and then, we measured children’s learning by asking them two questions in a test phase. Children of all ages, regardless of the prompt given, discussed most aspects of the machine, including the whole machine, its parts, and, to a lesser extent, its mechanisms. In the test phase, older children recalled more information than younger children about all aspects of the machine and appeared more knowledgeable to adult coders. Overall, this suggests that children of all ages were motivated to discuss all aspects of a machine, but some scaffolding may be necessary to help the youngest children take full advantage of these learning opportunities. While the prompts did not significantly influence the number of children who discussed the machine’s mechanisms, children who received the component prompt were rated as more knowledgeable about the machine in the test phase, suggesting that this prompt influenced what they learned. Implications for visitor experience and exhibit design are discussed. (shrink)