The current investigation examines children’s (N = 61; 4- to 8-year old) 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.

The current experiments investigate how infants use goal‐directed action to reason about intentionally sampled outcomes in a probabilistic inference paradigm. Older infants and young children are flexible in their expectations of sampling: They expect random samples to reflect population statistics and non‐random samples to reflect an agent's preferences or goals (Kushnir, Xu, & Wellman, 2010; Xu & Denison, 2009). However, more recent work shows that probabilistic inference comes online at approximately 6 months (Denison, Reed, & Xu, 2013; Kayhan, Gredebäck, & Lindskog, 2017; Ma & Xu, 2011; Wellman, Kushnir, Xu, & Brink, 2016), and thus, these sampling assumptions can be investigated at the age probabilistic reasoning first emerges. Results indicate that 6‐month‐old infants expect a human agent to sample in accord with their goal and do not expect the same of an unintentional agent—a mechanical claw. By 9.5 months, infants expect the mechanical claw to sample in accord with random sampling. These results suggest that infants use goals to make inferences about intentional sampling, under appropriate conditions at 6 months, and they have expectations of the kinds of samples a mechanical device should obtain by 9.5 months.

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Children are skilled reasoners who readily use causal, reliability, and base-rate (i.e., prior probability) information in their decisions. Though these abilities are typically studied in isolation, children often must consider multiple pieces of information to make an informed decision. Four experiments (N = 320) explored the development of children’s ability to use reliability and base-rate information when making decisions about draw outcomes. Experiment 1 examined the age at which children can first compare and choose between probabilistically reliable machines. Three- and 4-year-old children saw machines that were probabilistically reliable at obtaining objects while sampling from uniform distributions (i.e., all target or non-target objects). Although 4-year-old children correctly used reliability in their decisions, 3-year-olds did not. In Experiment 2a, 4- to 6-year-olds were presented with the same probabilistically reliable machines, although they sampled from a mixture of target and non-target items. Here, children tended to choose the machine with the better proportion of targets, regardless of reliability. This was replicated in Experiment 2b. In Experiment 3, children were presented with one perfectly reliable machine and one probabilistically unreliable machine. Here, children continued to mostly choose the machine with the better proportion of targets. These results raise questions about base-rate overuse early in development and highlight the need for additional work on children’s ability to use multiple pieces of information in decision-making.