Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector,” a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine's activation that (...) required them to use indirect evidence to make causal inferences. Critically, associative models either made no predictions, or made incorrect predictions about these inferences. In general, children were able to make these inferences, but some developmental differences between 3- and 4-year-olds were found. We suggest that children's causal inferences are not based on recognizing associations, but rather that children develop a mechanism for Bayesian structure learning. Experiment 3 explicitly tests a prediction of this account. Children were asked to make an inference about ambiguous data based on the base rate of certain events occurring. Four-year-olds, but not 3-year-olds were able to make this inference. (shrink)

Children approach counterfactual questions about stories with a reasoning strategy that falls short of adults’ Counterfactual Reasoning (CFR). It was dubbed “Basic Conditional Reasoning” (BCR) in Rafetseder et al. (Child Dev 81(1):376–389, 2010). In this paper we provide a characterisation of the differences between BCR and CFR using a distinction between permanent and nonpermanent features of stories and Lewis/Stalnaker counterfactual logic. The critical difference pertains to how consistency between a story and a conditional antecedent incompatible with a nonpermanent feature of (...) the story is achieved. Basic conditional reasoners simply drop all nonpermanent features of the story. Counterfactual reasoners preserve as much of the story as possible while accommodating the antecedent. (shrink)

The authors examined cue competition effects in young children using the blicket detector paradigm, in which objects are placed either singly or in pairs on a novel machine and children must judge which objects have the causal power to make the machine work. Cue competition effects were found in a 5- to 6-year-old group but not in a 4-year-old group. Equivalent levels of forward and backward blocking were found in the former group. Children's counterfactual judgments were subsequently examined by asking (...) whether or not the machine would have gone off in the absence of I of 2 objects that had been placed on it as a pair. Cue competition effects were demonstrated only in 5- to 6-year-olds using this mode of assessing causal reasoning. (shrink)

The application of the formal framework of causal Bayesian Networks to children’s causal learning provides the motivation to examine the link between judgments about the causal structure of a system, and the ability to make inferences about interventions on components of the system. Three experiments examined whether children are able to make correct inferences about interventions on different causal structures. The first two experiments examined whether children’s causal structure and intervention judgments were consistent with one another. In Experiment 1, children (...) aged between 4 and 8 years made causal structure judgments on a three-component causal system followed by counterfactual intervention judgments. In Experiment 2, children’s causal structure judgments were followed by intervention judgments phrased as future hypotheticals. In Experiment 3, we explicitly told children what the correct causal structure was and asked them to make intervention judgments. The results of the three experiments suggest that the representations that support causal structure judgments do not easily support simple judgments about interventions in children. We discuss our findings in light of strong interventionist claims that the two types of judgments should be closely linked. (shrink)

We provide an introduction to some of the key issues raised in this volume by considering how individual chapters bear on the prospects of what may be called a ‘counterfactual process view’ of causal reasoning. According to such a view, counterfactual thought is an essential part of the processing involved in making causal judgements, at least in a central range of cases that are critical to a subject’s understanding of what it is for one thing to cause another. We argue (...) that one fruitful way of approaching the different contributions to the volume is to think of them as providing materials, conceptual as well as empirical, for challenging counterfactual process views of causal thinking, or for responding to such challenges. Amongst the challenges we consider are ones that arise out of or parallel objections to counterfactual theories of causation in philosophy, or ones that appeal to apparent developmental dissociations between causal and counterfactual reasoning abilities. Possible responses turn on questions such as the following: What should count as engaging in counterfactual reasoning? How should we think of the cognitive prerequisites of such reasoning? Is it right to ask what the relationship is between causal and counterfactual reasoning, or are there in fact a number of different ways in which the two are connected? (shrink)

In most developmental studies the only error children could make on counterfactual tasks was to answer with the current state of affairs. It was concluded that children who did not show this error are able to reason counterfactually. However, children might have avoided this error by using basic conditional reasoning (Rafetseder, Cristi-Vargas, & Perner, 2010). Basic conditional reasoning takes background assumptions represented as conditionals about how the world works. If an antecedent of one of these conditionals is provided by the (...) task, then a likely conclusion can be inferred based only on background assumptions. A critical feature of counterfactual reasoning is that the selection of these additional assumptions is constrained by actual events to which the counterfactual is taken to be counterfactual. In contrast, in basic conditional reasoning one enriches the given antecedent with any plausible assumptions, unconstrained by actual events. In our tasks basic conditional reasoning leads to different answers from counterfactual reasoning. For instance, a doctor, sitting in the park with the intention of reading a paper, is called to an emergency at the swimming pool. The question, “If there had been no emergency, where would the doctor be?” should counterfactually be answered “in the park”. But by ignoring the doctor's intentions, and just reasoning from premises about the default location of a hospital doctor who has not been called out to an emergency, one might answer: “in the hospital”. Only by 6 years of age did children mostly give correct answers. (shrink)

Young children spend a large portion of their time pretending about non-real situations. Why? We answer this question by using the framework of Bayesian causal models to argue that pretending and counterfactual reasoning engage the same component cognitive abilities: disengaging with current reality, making inferences about an alternative representation of reality, and keeping this representation separate from reality. In turn, according to causal models accounts, counterfactual reasoning is a crucial tool that children need to plan for the future and learn (...) about the world. Both planning with causal models and learning about them require the ability to create false premises and generate conclusions from these premises. We argue that pretending allows children to practice these important cognitive skills. We also consider the prevalence of unrealistic scenarios in children's play and explain how they can be useful in learning, despite appearances to the contrary. (shrink)