Preschoolers search longer when there is more information to be gained.

What drives children to explore and learn when external rewards are uncertain or absent? Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24-56-month-olds' persistence in a game where they had to search for an object (animal or toy), which they never find, hidden behind a series of doors, manipulating the degree of uncertainty about which specific object was hidden. We found that children were more persistent in their search when there was higher uncertainty, and therefore, more information to be gained with each action, highlighting the importance of research on artificial intelligence to invest in curiosity-driven algorithms. RESEARCH HIGHLIGHTS: Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate preschoolers' actions. We measured preschoolers' persistence when searching for an object behind a series of doors, manipulating the uncertainty about which specific object was hidden. We found that preschoolers were more persistent when there was higher uncertainty, and therefore, more information to be gained with each action. Our results highlight the importance of research on artificial intelligence to invest in curiosity-driven algorithms.

Preschoolers and adults metonymically extend proper names to owned objects.

Three preregistered experiments, conducted in 2021, investigated whether English-speaking American preschoolers (N = 120; 4-6 years; 54 females, predominantly White) and adults (N = 80; 18-52 years; 59 females, predominantly Asian) metonymically extend owners' names to owned objects-an extension not typically found in English. In Experiment 1, 5- and 6-year-olds and adults extended names to owned objects over duplicates (d = 0.34 in children; d = 1.13 in adults). In Experiment 2, 5- and 6-year-olds and adults extended names to owned over borrowed objects (d = 1.37 in children; d = 4.34 in adults). Experiment 3 replicated this finding with 4-year-olds (d = 0.43). Thus, English-speaking preschoolers can acquire semantic generalizations, even those not present in their language.

Structural explanations lead young children and adults to rectify resource inequalities.

Decisions about how to divide resources have profound social and practical consequences. Do explanations regarding the source of existing inequalities influence how children and adults allocate new resources? When 3- to 6-year-old children (N = 201) learned that inequalities were caused by structural forces (stable external constraints affecting access to resources) as opposed to internal forces (effort), they rectified inequalities, overriding previously documented tendencies to perpetuate inequality or divide resources equally. Adults (N = 201) were more likely than children to rectify inequality spontaneously; this was further strengthened by a structural explanation but reversed by an effort-based explanation. Allocation behaviors were mirrored in judgments of which allocation choices by others were appropriate. These findings reveal how explanations powerfully guide social reasoning and action from childhood through adulthood.

Distinct electrophysiological signatures of task-unrelated and dynamic thoughts.

Humans spend much of their lives engaging with their internal train of thoughts. Traditionally, research focused on whether or not these thoughts are related to ongoing tasks, and has identified reliable and distinct behavioral and neural correlates of task-unrelated and task-related thought. A recent theoretical framework highlighted a different aspect of thinking-how it dynamically moves between topics. However, the neural correlates of such thought dynamics are unknown. The current study aimed to determine the electrophysiological signatures of these dynamics by recording electroencephalogram (EEG) while participants performed an attention task and periodically answered thought-sampling questions about whether their thoughts were 1) task-unrelated, 2) freely moving, 3) deliberately constrained, and 4) automatically constrained. We examined three EEG measures across different time windows as a function of each thought type: stimulus-evoked P3 event-related potentials and non-stimulus-evoked alpha power and variability. Parietal P3 was larger for task-related relative to task-unrelated thoughts, whereas frontal P3 was increased for deliberately constrained compared with unconstrained thoughts. Frontal electrodes showed enhanced alpha power for freely moving thoughts relative to non-freely moving thoughts. Alpha-power variability was increased for task-unrelated, freely moving, and unconstrained thoughts. Our findings indicate distinct electrophysiological patterns associated with task-unrelated and dynamic thoughts, suggesting these neural measures capture the heterogeneity of our ongoing thoughts.

Preschoolers and Adults Learn From Novel Metaphors.

Although adults use metaphors to guide their thinking and reasoning, less is known about whether metaphors might facilitate cognition earlier in development. Previous research shows that preschoolers understand metaphors, but less is known about whether preschoolers can learn from metaphors. The current preregistered experiment investigated whether adults (n = 64) and 3- and 4-year-olds (n = 128) can use metaphors to make new inferences. In a between-subjects design, participants heard information about novel artifacts, conveyed through either only positive metaphors (e.g., "Daxes are suns") or positive and negative metaphors (e.g., "Daxes are suns. Daxes are not clouds."). In both conditions, participants of all ages successfully formed metaphor-consistent inferences about abstract, functional features of the artifacts (e.g., that daxes light up rather than let out water). Moreover, participants frequently provided explanations appealing to the metaphors when justifying their responses. Consequently, metaphors may be a powerful learning mechanism from early childhood onward.

Ask me why, don't tell me why: Asking children for explanations facilitates relational thinking.

Identifying abstract relations is essential for commonsense reasoning. Research suggests that even young children can infer relations such as "same" and "different," but often fail to apply these concepts. Might the process of explaining facilitate the recognition and application of relational concepts? Based on prior work suggesting that explanation can be a powerful tool to promote abstract reasoning, we predicted that children would be more likely to discover and use an abstract relational rule when they were prompted to explain observations instantiating that rule, compared to when they received demonstration alone. Five- and 6-year-olds were given a modified Relational Match to Sample (RMTS) task, with repeated demonstrations of relational (same) matches by an adult. Half of the children were prompted to explain these matches; the other half reported the match they observed. Children who were prompted to explain showed immediate, stable success, while those only asked to report the outcome of the pedagogical demonstration did not. Findings provide evidence that explanation facilitates early abstraction over and above demonstration alone.

Transformations and Transfer: Preschool Children Understand Abstract Relations and Reason Analogically in a Causal Task.

Previous research suggests that preschoolers struggle with understanding abstract relations and with reasoning by analogy. Four experiments find, in contrast, that 3- and 4-year-olds (N = 168) are surprisingly adept at relational and analogical reasoning within a causal context. In earlier studies preschoolers routinely favored images that share thematic or perceptual commonalities with a target image (object matches) over choices that match the target along abstract relations (relational matches). The present studies embed such choice tasks within a cause-and-effect framework. Without causal framing, preschoolers strongly favor object matches, replicating the results of previous studies. But with causal framing, preschoolers succeed at analogical transfer (i.e., choose relational matches). These findings suggest that causal framing facilitates early analogical reasoning.

Young Children Are Wishful Thinkers: The Development of Wishful Thinking in 3- to 10-Year-Old Children.

Previously, research on wishful thinking has found that desires bias older children's and adults' predictions during probabilistic reasoning tasks. In this article, we explore wishful thinking in children aged 3- to 10-years-old. Do young children learn to be wishful thinkers? Or do they begin with a wishful thinking bias that is gradually overturned during development? Across five experiments, we compare low- and middle-income United States and Peruvian 3- to 10-year-old children (N = 682). Children were asked to make predictions during games of chance. Across experiments, preschool-aged children from all backgrounds consistently displayed a strong wishful thinking bias. However, the bias declined with age.

Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood.

How was the evolution of our unique biological life history related to distinctive human developments in cognition and culture? We suggest that the extended human childhood and adolescence allows a balance between exploration and exploitation, between wider and narrower hypothesis search, and between innovation and imitation in cultural learning. In particular, different developmental periods may be associated with different learning strategies. This relation between biology and culture was probably coevolutionary and bidirectional: life-history changes allowed changes in learning, which in turn both allowed and rewarded extended life histories. In two studies, we test how easily people learn an unusual physical or social causal relation from a pattern of evidence. We track the development of this ability from early childhood through adolescence and adulthood. In the physical domain, preschoolers, counterintuitively, perform better than school-aged children, who in turn perform better than adolescents and adults. As they grow older learners are less flexible: they are less likely to adopt an initially unfamiliar hypothesis that is consistent with new evidence. Instead, learners prefer a familiar hypothesis that is less consistent with the evidence. In the social domain, both preschoolers and adolescents are actually the most flexible learners, adopting an unusual hypothesis more easily than either 6-y-olds or adults. There may be important developmental transitions in flexibility at the entry into middle childhood and in adolescence, which differ across domains.

Rational Higher-Order Belief Revision in Young Children.

Belief revision can occur at multiple levels of abstraction, including lower-level and higher-order beliefs. It remains unclear, however, how conflicting evidence interacts with prior beliefs to encourage higher-order belief revision. This study explores how 4- and 5-year-olds (N = 96) respond to evidence that directly conflicts with their causal higher-order beliefs. When shown a single event that directly violated a strongly supported prior belief, preschoolers largely maintained their initial higher-order belief. However, when the prior belief was more weakly supported and the counterevidence was stronger, children changed their minds. These findings indicate that young children can revise their higher-order beliefs and, furthermore, do so depending on the strength of both the evidence and their prior beliefs.

Causal Learning Across Culture and Socioeconomic Status.

Extensive research has explored the ability of young children to learn about the causal structure of the world from patterns of evidence. These studies, however, have been conducted with middle-class samples from North America and Europe. In the present study, low-income Peruvian 4- and 5-year-olds and adults, low-income U.S. 4- and 5-year-olds in Head Start programs, and middle-class children from the United States participated in a causal learning task (N = 435). Consistent with previous studies, children learned both specific causal relations and more abstract causal principles across culture and socioeconomic status (SES). The Peruvian children and adults generally performed like middle-class U.S. children and adults, but the low-SES U.S. children showed some differences.

Explaining Constrains Causal Learning in Childhood.

Three experiments investigate how self-generated explanation influences children's causal learning. Five-year-olds (N = 114) observed data consistent with two hypotheses and were prompted to explain or to report each observation. In Study 1, when making novel generalizations, explainers were more likely to favor the hypothesis that accounted for more observations. In Study 2, explainers favored a hypothesis that was consistent with prior knowledge. Study 3 pitted a hypothesis that accounted for more observations against a hypothesis consistent with prior knowledge. Explainers were more likely to base generalizations on prior knowledge. Findings suggest that attempts to explain drive children to evaluate hypotheses using features of "good" explanations, or those supporting generalizations with broad scope, as informed by children's prior knowledge and observations.

How Universal Are Free Will Beliefs? Cultural Differences in Chinese and U.S. 4- and 6-Year-Olds.

This study explores the development of free will beliefs across cultures. Sixty-seven Chinese 4- and 6-year-olds were asked questions to gauge whether they believed that people could freely choose to inhibit or act against their desires. Responses were compared to those given by the U.S. children in Kushnir, Gopnik, Chernyak, Seiver, and Wellman (). Results indicate that children from both cultures increased the amount of choice they ascribed with age. For inhibition questions, Chinese children ascribed less choice than the U.S. children. Qualitative explanations revealed that the U.S. children were also more likely to endorse notions of autonomous choice. These findings suggest both cultural differences and similarities in free will beliefs.

Inferring action structure and causal relationships in continuous sequences of human action.

In the real world, causal variables do not come pre-identified or occur in isolation, but instead are embedded within a continuous temporal stream of events. A challenge faced by both human learners and machine learning algorithms is identifying subsequences that correspond to the appropriate variables for causal inference. A specific instance of this problem is action segmentation: dividing a sequence of observed behavior into meaningful actions, and determining which of those actions lead to effects in the world. Here we present a Bayesian analysis of how statistical and causal cues to segmentation should optimally be combined, as well as four experiments investigating human action segmentation and causal inference. We find that both people and our model are sensitive to statistical regularities and causal structure in continuous action, and are able to combine these sources of information in order to correctly infer both causal relationships and segmentation boundaries.

Causal learning from probabilistic events in 24-month-olds: an action measure.

How do young children learn about causal structure in an uncertain and variable world? We tested whether they can use observed probabilistic information to solve causal learning problems. In two experiments, 24-month-olds observed an adult produce a probabilistic pattern of causal evidence. The toddlers then were given an opportunity to design their own intervention. In Experiment 1, toddlers saw one object bring about an effect with a higher probability than a second object. In Experiment 2, the frequency of the effect was held constant, though its probability differed. After observing the probabilistic evidence, toddlers in both experiments chose to act on the object that was more likely to produce the effect. The results demonstrate that toddlers can learn about cause and effect without trial-and-error or linguistic instruction on the task, simply by observing the probabilistic patterns of evidence resulting from the imperfect actions of other social agents. Such observational causal learning from probabilistic displays supports human children's rapid cultural learning.

Ensemble perception of size in 4-5-year-old children.

Groups of objects are nearly everywhere we look. Adults can perceive and understand the 'gist' of multiple objects at once, engaging ensemble-coding mechanisms that summarize a group's overall appearance. Are these group-perception mechanisms in place early in childhood? Here, we provide the first evidence that 4-5-year-old children use ensemble coding to perceive the average size of a group of objects. Children viewed a pair of trees, with each containing a group of differently sized oranges. We found that, in order to determine which tree had the larger oranges overall, children integrated the sizes of multiple oranges into ensemble representations. This pooling occurred rapidly, and it occurred despite conflicting information from numerosity, continuous extent, density, and contrast. An ideal observer analysis showed that although children's integration mechanisms are sensitive, they are not yet as efficient as adults'. Overall, our results provide a new insight into the way children see and understand the environment, and they illustrate the fundamental nature of ensemble coding in visual perception.

Learning to learn from stories: children's developing sensitivity to the causal structure of fictional worlds.

Fiction presents a unique challenge to the developing child, in that children must learn when to generalize information from stories to the real world. This study examines how children acquire causal knowledge from storybooks, and whether children are sensitive to how closely the fictional world resembles reality. Preschoolers (N = 108) listened to stories in which a novel causal relation was embedded within realistic or fantastical contexts. Results indicate that by at least 3 years of age, children are sensitive to the underlying causal structure of the story: Children are more likely to generalize content if the fictional world is similar to reality. Additionally, children become better able at discriminating between realistic and fantastical story contexts between 3 and 5 years of age.

Of babies and birds: complex tool behaviours are not sufficient for the evolution of the ability to create a novel causal intervention.

Humans are capable of simply observing a correlation between cause and effect, and then producing a novel behavioural pattern in order to recreate the same outcome. However, it is unclear how the ability to create such causal interventions evolved. Here, we show that while 24-month-old children can produce an effective, novel action after observing a correlation, tool-making New Caledonian crows cannot. These results suggest that complex tool behaviours are not sufficient for the evolution of this ability, and that causal interventions can be cognitively and evolutionarily disassociated from other types of causal understanding.

Toddlers infer higher-order relational principles in causal learning.

Children make inductive inferences about the causal properties of individual objects from a very young age. When can they infer higher-order relational properties? In three experiments, we examined 18- to 30-month-olds' relational inferences in a causal task. Results suggest that at this age, children are able to infer a higher-order relational causal principle from just a few observations and use this inference to guide their own subsequent actions and bring about a novel causal outcome. Moreover, the children passed a revised version of the relational match-to-sample task that has proven very difficult for nonhuman primates. The findings are considered in light of their implications for understanding the nature of relational and causal reasoning, and their evolutionary origins.

Win-Stay, Lose-Sample: a simple sequential algorithm for approximating Bayesian inference.

People can behave in a way that is consistent with Bayesian models of cognition, despite the fact that performing exact Bayesian inference is computationally challenging. What algorithms could people be using to make this possible? We show that a simple sequential algorithm "Win-Stay, Lose-Sample", inspired by the Win-Stay, Lose-Shift (WSLS) principle, can be used to approximate Bayesian inference. We investigate the behavior of adults and preschoolers on two causal learning tasks to test whether people might use a similar algorithm. These studies use a "mini-microgenetic method", investigating how people sequentially update their beliefs as they encounter new evidence. Experiment 1 investigates a deterministic causal learning scenario and Experiments 2 and 3 examine how people make inferences in a stochastic scenario. The behavior of adults and preschoolers in these experiments is consistent with our Bayesian version of the WSLS principle. This algorithm provides both a practical method for performing Bayesian inference and a new way to understand people's judgments.