To improve upon their current knowledge, learners must be able to generate informative data and accurately evaluate this evidence. However, there is substantial disagreement regarding self-directed learners' competence in these behaviors. Researchers in cognitive development have suggested that learners are "intuitive scientists," generating informative actions and rationally coordinating their current observations and prior beliefs from an early age. Conversely, researchers in scientific reasoning report that learners struggle with experimentation and often fail to reach appropriate conclusions from evidence, even as adults. According to the prevailing narrative, these inconsistent findings must be "bridged" to explain the gap between learners' successes and failures. Here, we advocate for an alternative approach. First, we review the research on scientific reasoning and find that there may be less evidence for learners' failures than is typically assumed. Second, we offer a novel interpretation that aims to account for both literatures: we suggest that self-directed learners may be best understood as competent causal reasoners. That is, many seemingly uninformative or irrational behaviors are consistent with the goals of causal learning. This account not only resolves the apparent contradictions in the existing research, but also offers a way forward towards a more accurate and integrated understanding of self-directed learning. This article is categorized under: Psychology > Development and Aging Psychology > Learning Psychology > Reasoning and Decision Making.

A large body of research has shown that engaging in self-explanation improves learning across a range of tasks. It has been proposed that the act of explaining draws attention and cognitive resources towards evidence that supports good explanations-information that is broad, abstract, and consistent with prior knowledge-which in turn aids discovery and promotes generalization. However, it remains unclear whether explanation impacts the learning process via improved hypothesis generation, increasing the probability that the most generalizable hypotheses are considered in the first place, or hypothesis evaluation, the appraisal of such hypotheses in light of observed evidence. In two experiments with adults, we address this question by separating hypothesis generation and evaluation in a novel category learning task and quantifying the effect of explaining on each process independently. We find that explanation supports learners' generation of broad and abstract hypotheses but does not impact their evaluation of them. These results provide a more precise account of the process by which explanation impacts learning and offer additional support for the claim that hypothesis generation and evaluation play distinct roles in problem solving.

The ability to represent same-different relations is an important condition for abstract thought. However, there is mixed evidence for when this ability develops, both ontogenetically and phylogenetically. Apparent success in relational reasoning may be evidence for genuine conceptual understanding or may be the result of low-level, perceptual strategies. We introduce a method to discriminate these possibilities by pitting two conditions that are perceptually matched but conceptually different: in a "fused" condition, same and different objects are joined, creating single objects that have the same perceptual features as the two object pairs in the "relational" condition. However, the "fused" objects do not provide evidence for the relation 'same.' Using this method with human toddlers in a causal relational reasoning task provides evidence for genuine conceptual understanding. This novel technique offers a simple manipulation that may be applied to a variety of existing match-to-sample procedures used to assess same-different reasoning to include in future research with non-human animals across species, as well as human infants.

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.

Self-directed learners are often described as ‘intuitive scientists’, yet they also tend to struggle in assessments of their scientific reasoning. We investigate a novel explanation for this apparent gap between formal and informal scientific inquiry. Specifically, we consider whether learners’ documented failure to correctly apply the control of variables strategy might stem from a mismatch between their causal intuitions and task presentation. Children (7- and 9-year-olds) and adults were tested on a version of a traditional multivariate reasoning task (Tschirgi, 1980) that we modified to clarify ambiguous elements of the causal logic. A significant majority of participants in all age groups selected informative experiments on this modified task, avoiding confounded actions with positive tangible outcomes. This finding contrasts with the longstanding claim that learners do not correctly employ control of variables without extensive training and suggests that self-directed scientific inquiry may be intuitively suited to support causal learning goals.

The review by Lillard et al. (2013) highlighted the need for additional research to better clarify the nature of the relationship between pretend play and development. However, the authors did not provide a proposal for how to structure the direction of this future work. Here, we provide a possible framework for generating additional research. This theoretical proposal is based on recent computational approaches to cognition, in which counterfactual reasoning plays a central role in causal learning. We propose that pretend play initially emerges as a product of the cognitive mechanisms underlying human learning and then feeds back to become critical for enhancing the optimal functioning of these same processes. More specifically, we argue that pretending is in fact 1 of several forms of counterfactual reasoning, which is essential to causal cognition-and that the act of engaging in pretend scenarios may provide early opportunities to practice the skills that were initially responsible for its appearance. Here, we provide a brief overview of this theoretical framework, consider how these ideas may be integrated with the previous work covered in Lillard et al.'s (2013) review, and suggest some empirically testable questions to direct future directions.

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy.

We investigated whether children preferentially select informative actions and make accurate inferences from the outcome of their own interventions in a causal learning task. Four- to six-year-olds were presented with a novel system composed of gears that could operate according to two possible causal structures (single or multiple cause). Given the choice between interventions (i.e., removing one of the two gears to observe the remaining gear in isolation), children demonstrated a clear preference for the action that revealed the true causal structure, and made subsequent causal judgments that were consistent with the outcome observed. Experiment 2 addressed the possibility that performance was driven by children's tendency to select an intervention that would produce a desirable effect (i.e., spinning gears), rather than to disambiguate the causal structure. These results replicate our initial findings in a context in which the informative action was less likely to produce a positive outcome than the uninformative one. Experiment 3 serves as a control demonstrating that children's success in the previous experiments is not due to their use of low-level strategies. We discuss these findings in terms of their significance for understanding the development of scientific reasoning and the role of self-directed actions in early causal learning.

We explore the link between children’s gesture production and analogical reasoning. Specifically, we ask whether children who spontaneously gesture when completing a retelling task are more likely to engage in analogical transfer, compared to those who do not gesture. To test this, 85 5-7-year-olds listened to three superficially distinct stories that shared a common abstract problem and solution. After each of the first two exemplar stories, participants were asked to retell the story events to a naïve listener and their speech and spontaneous gesture(s) were coded. For the third story, participants were asked to generate the analogous solution themselves. Results indicate a significant relationship between children’s analogical transfer and gesture production. This preliminary study suggests that children’s spontaneous gestures may provide a window into their analogical processing. We discuss future directions aimed at further examining the mechanism underlying this relationship.