Metaphors are ubiquitous in both everyday speech (e.g., “I was lost in a sea of people”) and creative literature (e.g, “A word is elegy to what it signifies”). Metaphors provide frameworks for reasoning about abstract concepts, influencing how humans attend to, remember, and process information. Metaphors are also a force for creative change across various disparate domains, for example by spurring the creation of new explanatory theories in science and new word meanings in language. While metaphors are a powerful tool for thinking and reasoning in adulthood, previous research suggests that children do not understand metaphors until quite late in development, by some accounts not until adolescence. However, using novel experimental paradigms, the current dissertation provides new data suggesting that children as young as four years of age can not only understand, but also learn from, metaphors.

Chapter 1 outlines previous research on the development of metaphor comprehension. Chapter 2 uses novel paradigms to demonstrate that preschoolers can understand metaphors based on shared abstract, functional similarities (e.g., “Clouds are sponges”; “Roofs are hats”). Chapter 3 explores whether preschoolers can select the most relevant metaphor to learn from, and finds that providing preschoolers with explanations can shift their metaphor preferences in a manner that is conducive to further learning. Chapter 4 shows that preschoolers can successfully use metaphors to make additional inferences about novel concepts. Finally, Chapter 5 discusses the implications of this work for research in linguistic and cognitive development, as well as future directions.

Overall, this series of experiments suggest that children possess an early-emerging capacity to understand and use complex non-literal language. Moreover, metaphors may be a powerful cognitive mechanism that facilitates learning, even early in ontogenesis.

Learning is a complex process that requires integrating new evidence with existing beliefs. This task is relatively straightforward when the evidence is consistent with and thus supported by existing beliefs. In such instances the evidence serves to confirm and hence strengthen beliefs. It becomes less clear, however, when the evidence is inconsistent—that is, when the evidence directly conflicts with one’s prior knowledge. Will learners revise their beliefs to reflect the new evidence or will they instead maintain their existing beliefs, perhaps ignoring the conflicting data as anomalous? How might their responses differ as a function of development, and what might this reveal about the mechanisms that support learning (and relearning)?

The current dissertation addresses these questions by asking how children and adults respond to evidence that violates their beliefs. Chapter 1 begins by describing a surprising developmental pattern: younger children are sometimes better than older children and adults at using statistical evidence to revise their beliefs. I then provide a Bayesian explanation for these findings, noting that younger learners may outperform older ones because they are intrinsically more flexible in their search for alternative hypotheses. Chapter 2 then provides empirical evidence that young children revise their higher-order beliefs by attending to the statistical strength of the data and weighing it against their prior belief. When shown a single event that conflicts with their belief, 4- and 5-year-olds largely maintain their higher-order belief. However, when shown several events that each support the same alternative hypothesis, children reliably update their belief to account for the new data. Chapter 3 then replicates these findings with even younger children, demonstrating that 3-year-olds similarly update their beliefs when the counterevidence is strong enough to outweigh the prior belief. Notably, children’s ability to update their beliefs is independent of their executive ability to deliberately change their behaviors in response to new goals and demands. Chapter 4 then contrasts children’s epistemic flexibility with adults’ inflexibility, exposing a striking developmental decline in adults’ sensitivity to new data. In particular, these findings highlight the robustness of adults’ beliefs by demonstrating that adults continue to endorse a weakly supported belief even after they are primed or incentivized to reason more broadly and creatively. Finally, Chapter 5 discusses the implications of this work and suggests future directions.

Taken together, these experiments contribute to our emerging understanding of belief revision by demonstrating how, as knowledge is accumulated and as beliefs are strengthened, our sensitivity to new evidence decreases and our willingness to revise declines. This pattern, although at times counterproductive, may be adaptive as learners transition from a strategy of exploration to one of exploitation.

This series of studies examines the relationship between causal inference and attribution from a developmental and cross-cultural perspective. In the first study, we consider how children at the ages of four and six reason about person by situation covariation information (Kelley, 1967), both younger than previously demonstrated trait biases or spontaneously using trait words. We then compare children's explanations of people's behavior to the actual behavioral evidence. Next, we extend the paradigm to include physical causation and the potential overhypotheses that guide the formation of domain specific reasoning. We will determine whether there are domain differences in perceiving virtually identical data construed as physical events or intentional actions. And finally, in the last study, we examine the role of culture in shaping the developmental trajectory of attributional style. As in physical causal inference, social causal inference combines covariational evidence and prior knowledge. We can use the tools of causal inference to understand how culturally-mediated prior beliefs affect the construal of person-by-situation information in a domain specific manner and trace the origins of attributional biases in adults.