Testimony and observation of statistical evidence interact in adults' and children's category-based induction.

Hearing generic or other kind-relevant claims can influence the use of information from direct observations in category learning. In the current study, we ask how both adults and children integrate their observations with testimony when learning about the causal property of a novel category. Participants were randomly assigned to hear one of four types of testimony: generic, quantified "all", specific, or only labels. In Study 1, adults (N = 1249) then observed that some proportion of objects (10%-100%) possessed a causal property. In Study 2, children (N = 123, Mage = 5.06 years, SD = 0.61 years, range 4.01-5.99 years) observed a sample where 30% of the objects had the causal property. Generic and quantified "all" claims led both adults and children to generalize the causal property beyond what was observed. Adults and children diverged, however, in their overall trust in testimony that could be verified by observations: adults were more skeptical of inaccurate quantified claims, whereas children were more accepting. Additional memory probes suggest that children's trust in unverified claims may have been due to misremembering what they saw in favor of what they heard. The current findings demonstrate that both child and adult learners integrate information from both sources, offering insights into the mechanisms by which language frames first-hand experience.

The Community-Engaged Lab: A Case-Study Introduction for Developmental Science.

Due to the closing of campuses, museums, and other public spaces during the pandemic, the typical avenues for recruitment, partnership, and dissemination are now unavailable to developmental labs. In this paper, we show how a shift in perspective has impacted our lab's ability to successfully transition to virtual work during the COVID-19 shut-down. This begins by recognizing that any lab that relies on local communities to engage in human research is itself a community organization. From this, we introduce a community-engaged lab model, and explain how it works using our own activities during the pandemic as an example. To begin, we introduce the vocabulary of mission-driven community organizations and show how we applied the key ideas of mission, vision, and culture to discussions of our own lab's identity. We contrast the community-engaged lab model with a traditional bi-directional model of recruitment from and dissemination to communities and describe how the community-engaged model can be used to reframe these and other ordinary lab activities. Our activities during the pandemic serve as a case study: we formed new community partnerships, engaged with child "citizen-scientists" in online research, and opened new avenues of virtual programming. One year later, we see modest but quantifiable impact of this approach: a return to pre-pandemic diversity in our samples, new engagement opportunities for trainees, and new sustainable partnerships. We end by discussing the promise and limitations of the community-engaged lab model for the future of developmental research.

Children's developing capacity to calibrate the verbal testimony of others with observed evidence when inferring causal relations.

Across two studies (N = 120), we investigated the development of children's ability to calibrate the certainty of verbal testimony with observable data that varied in the degree of predictive causal accuracy. In Study 1, 4- and 5-year-olds heard a certain explanation or an uncertain explanation about deterministic causal relations. The 5-year-olds made more accurate causal inferences when the informant provided a certain and more calibrated explanation. In Study 2, children heard similar explanations about probabilistic relations, making the uncertain informant more calibrated. The 5-year-olds were more likely to infer the correct causal relations when the informant was uncertain, but only when the explanation was attuned to the stochasticity of the individual causal events (or outcomes that sometimes occur). These findings imply that the capacity to integrate, and make efficient inferences, from distinct sources of knowledge emerges during the preschool years.

Exploration, Explanation, and Parent-Child Interaction in Museums.

Young children develop causal knowledge through everyday family conversations and activities. Children's museums are an informative setting for studying the social context of causal learning because family members engage together in everyday scientific thinking as they play in museums. In this multisite collaborative project, we investigate children's developing causal thinking in the context of family interaction at museum exhibits. We focus on explaining and exploring as two fundamental collaborative processes in parent-child interaction, investigating how families explain and explore in open-ended collaboration at gear exhibits in three children's museums in Providence, RI, San Jose, CA, and Austin, TX. Our main research questions examined (a) how open-ended family exploration and explanation relate to one another to form a dynamic for children's learning; (b) how that dynamic differs for families using different interaction styles, and relates to contextual factors such as families' science background, and (c) how that dynamic predicts children's independent causal thinking when given more structured tasks. We summarize findings on exploring, explaining, and parent-child interaction (PCI) styles. We then present findings on how these measures related to one another, and finally how that dynamic predicts children's causal thinking. In studying children's exploring we described two types of behaviors of importance for causal thinking: (a) Systematic Exploration: Connecting gears to form a gear machine followed by spinning the gear machine. (b) Resolute Behavior: Problem-solving behaviors, in which children attempted to connect or spin a particular set of gears, hit an obstacle, and then persisted to succeed (as opposed to moving on to another behavior). Older children engaged in both behaviors more than younger children, and the proportion of these behaviors were correlated with one another. Parents and children talked to each other while interacting with the exhibits. We coded causal language, as well as other types of utterances. Parents' causal language predicted children's causal language, independent of age. The proportion of parents' causal language also predicted the proportion of children's systematic exploration. Resolute behavior on the part of children did not correlate with parents' causal language, but did correlate with children's own talk about actions and the exhibit. We next considered who set goals for the play in a more holistic measure of parent-child interaction style, identifying dyads as parent-directed, child-directed, or jointly-directed in their interaction with one another. Children in different parent-child interaction styles engaged in different amounts of systematic exploration and had parents who engaged in different amounts of causal language. Resolute behavior and the language related to children engaging in such troubleshooting, seemed more consistent across the three parent-child interaction styles. Using general linear mixed modeling, we considered relations within sequences of action and talk. We found that the timing of parents' causal language was crucial to whether children engaged in systematic exploration. Parents' causal talk was a predictor of children's systematic exploration only if it occurred prior to the act of spinning the gears (while children were building gear machines). We did not observe an effect of causal language when it occurred concurrently with or after children's spinning. Similarly, children's talk about their actions and the exhibit predicted their resolute behavior, but only when the talk occurred while the child was encountering the problem. No effects were found for models where the talk happened concurrently or after resolving the problem. Finally, we considered how explaining and exploring related to children's causal thinking. We analyzed measures of children's causal thinking about gears and a free play measure with a novel set of gears. Principal component analysis revealed a latent factor of causal thinking in these measures. Structural equation modeling examined how parents' background in science related to children's systematic exploration, parents' causal language, and parent-child interaction style, and then how those factors predicted children's causal thinking. In a full model, with children's age and gender included, children's systematic exploration related to children's causal thinking. Overall, these data demonstrate that children's systematic exploration and parents' causal explanation are best studied in relation to one another, because both contributed to children's learning while playing at a museum exhibit. Children engaged in systematic exploration, which supported their causal thinking. Parents' causal talk supported children's exploration when it was presented at certain times during the interaction. In contrast, children's persistence in problem solving was less sensitive to parents' talk or interaction style, and more related to children's own language, which may act as a form of self-explanation. We discuss the findings in light of ongoing approaches to promote the benefit of parent-child interaction during play for children's learning and problem solving. We also examine the implications of these findings for formal and informal learning settings, and for theoretical integration of constructivist and sociocultural approaches in the study of children's causal thinking.

How Children Learn From Others: An Analysis of Selective Word Learning.

One way children are remarkable learners is that they learn from others. Critically, children are selective when assessing from whom to learn, particularly in the domain of word learning. We conducted an analysis of children's selective word learning, reviewing 63 papers on 6,525 participants. Children's ability to engage in selective word learning appeared to be present in the youngest samples surveyed. Their more metacognitive understanding that epistemic competence indicates reliability or that others are good sources of knowledge has more of a developmental trajectory. We also found that various methodological factors used to assess children influence performance. We conclude with a synthesis of theoretical accounts of how children learn from others.