Developmental changes in children’s recognition of the relevance of evidence to causal explanations

Contributions of causal reasoning to early scientific literacy

Although early causal reasoning has been studied extensively, inconsistency in the tasks used to assess it has clouded our understanding of its structure, development, and relevance to broader developmental outcomes. The current research attempted to bring clarity to these questions by exploring patterns of performance across several commonly used measures of causal reasoning, and their relation to scientific literacy, in a sample of 3- to 5-year-old children from diverse backgrounds (N = 153). A longitudinal confirmatory factor analysis revealed that some measures of causal reasoning (counterfactual reasoning, causal learning, and causal inference), but not all of them (tracking cause-effect associations and resolving confounded evidence), assess a unidimensional factor and that this resulting factor was relatively stable across time. A cross-lagged panel model analysis revealed associations between causal reasoning and scientific literacy across each age tested. Causal reasoning and scientific literacy related to each other concurrently, and each predicted the other in subsequent years. These relations could not be accounted for by children's broader cognitive skills. Implications for early STEM (science, technology, engineering, and math) engagement and success are discussed.

"I know it's complicated": Children detect relevant information about object complexity

Mechanistic complexity is an important property that affects how we interact with and learn from artifacts. Although highly complex artifacts have only recently become part of human material culture, they are ever-present in contemporary life. In previous research, children successfully detected complexity contrasts when given information about the functions of simple and complex objects. However, whether children spontaneously favor relevant information about an object's causal mechanisms and functions when trying to determine an object's complexity remains an open question. In Study 1, 7- to 9-year-olds and adults, but not 5- and 6-year-olds, rated information about relevant actions (e.g., the difficulty in fixing an object) as more helpful than information about irrelevant actions (e.g., the difficulty in spelling an object's name) for making determinations of mechanistic complexity. Only in Study 2, in which the relevance contrasts were extreme, did the youngest age group rate relevant actions as more helpful than irrelevant actions. In Study 3, in which participants rated the complexity of the actions themselves, participants performed differently than in the previous studies, suggesting that children in the prior studies did not misinterpret the study instructions as prompts to rate the actions' complexity. These results suggest that the ability to detect which object properties imply complexity emerges during the early school years. Younger children may be misled by features that are not truly diagnostic of mechanistic complexity, whereas older children more easily disregard such features in favor of relevant information.