Alison Gopnik

Children's understanding of representational change and its relation to the understanding of false belief and the appearance-reality distinction

This research concerns the development of childrens understanding of representational change and its relation to other cognitive developments. Children were shown deceptive objects, and the true nature of the objects was then revealed. Children were then asked what they thought the object was when they first saw it, testing their understanding of representational change; what another child would think the object was, testing their understanding of false belief; and what the object looked like and really was, testing their understanding of the appearance-reality distinction. Most 3-year-olds answered the representational change question incorrectly. Most 5-year-olds did not make this error. Childrens performance on the representational change question was poorer than their performance on the false-belief question. There were correlations between performance on all 3 tasks. Apparently children begin to be able to consider alternative representations of the same object at about age 4.

Mapping the mind: The theory theory

This is a book about domain-specific cognition – the proposal that at least some human conceptual abilities are specialized for some types of contents and not for others. In this chapter we address the development of a single domain: everyday understanding of the mind. We suggest that this development is best understood as the formulation of a succession of naive theories. Moreover, this “theory theory” can help to characterize cognitive domains more generally and to explain domain-specific development. Our chapter, therefore, joins company with a number of recent discussions drawing parallels between theory change in science and cognitive development (Carey, 1985, 1988; Gopnik, 1984, 1988; Karmiloff-Smith & Inhelder, 1974; Keil, 1987; Wellman, 1985, 1990). Theory of mind In the past five years there has been an explosion of interest in childrens early understanding of the mind (Butterworth, Harris, Leslie & Wellman, 1991; Astington, Harris, & Olson, 1988; Frye & Moore, 1991; Whiten, 1991). The research tackling this question has come to be called “childrens theory of mind.” This title reflects a leading explanatory position among investigators in this area. According to this position, our everyday conception of the mind is an implicit naive theory; childrens early conceptions of the mind are also implicit theories, and changes in those conceptions are theory changes. We refer to this explanatory position as the “theory theory.” If the theory theory has any content, it should be falsifiable. It should lead to empirical predictions about the course of development, and these predictions should be different from those of alternative accounts.

How we know our minds: the illusion of first-person knowledge of intentionality

As adults we believe that our knowledge of our own psychological states is substantially different from our knowledge of the psychological states of others: First-person knowledge comes directly from experience, but third-person knowledge involves inference. Developmental evidence suggests otherwise. Many 3-year-old children are consistently wrong in reporting some of their own immediately past psychological states and show similar difficulties reporting the psychological states of others. At about age 4 there is an important developmental shift to a representational model of the mind. This affects childrens understanding of their own minds as well as the minds of others. Our sense that our perception of our own minds is direct may be analogous to many cases where expertise provides an illusion of direct perception. These empirical findings have important implications for debates about the foundations of cognitive science.

Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers

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 3and 4year-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. Fouryear-olds, but not 3-year-olds were able to make this inference.

Mechanisms of theory formation in young children

Research suggests that by the age of five, children have extensive causal knowledge, in the form of intuitive theories. The crucial question for developmental cognitive science is how young children are able to learn causal structure from evidence. Recently, researchers in computer science and statistics have developed representations (causal Bayes nets) and learning algorithms to infer causal structure from evidence. Here we explore evidence suggesting that infants and children have the prerequisites for making causal inferences consistent with causal Bayes net learning algorithms. Specifically, we look at infants and childrens ability to learn from evidence in the form of conditional probabilities, interventions and combinations of the two.

Causal Learning Across Domains

Five studies investigated (a) childrens ability to use the dependent and independent probabilities of events to make causal inferences and (b) the interaction between such inferences and domain-specific knowledge. In Experiment 1, preschoolers used patterns of dependence and independence to make accurate causal inferences in the domains of biology and psychology. Experiment 2 replicated the results in the domain of biology with a more complex pattern of conditional dependencies. In Experiment 3, children used evidence about patterns of dependence and independence to craft novel interventions across domains. In Experiments 4 and 5, childrens sensitivity to patterns of dependence was pitted against their domain-specific knowledge. Children used conditional probabilities to make accurate causal inferences even when asked to violate domain boundaries.

The scientist as child

This paper argues that there are powerful similarities between cognitive development in children and scientific theory change. These similarities are best explained by postulating an underlying abstract set of rules and representations that underwrite both types of cognitive abilities. In fact, science may be successful largely because it exploits powerful and flexible cognitive devices that were designed by evolution to facilitate learning in young children. Both science and cognitive development involve abstract, coherent systems of entities and rules, theories. In both cases, theories provide predictions, explanations, and interpretations. In both, theories change in characteristic ways in response to counterevidence. These ideas are illustrated by an account of childrens developing understanding of the mind.

Scientific Thinking in Young Children: Theoretical Advances, Empirical Research, and Policy Implications

Kindergarten Scientists Becoming a scientist takes many years of training … or so it seems. It requires learning how to acquire data, to incorporate it into hypotheses, and then to test those hypotheses against newly acquired data; it requires learning how to think critically and to apply statistical analysis. Gopnik (p. 1623) reviews recent cognitive development findings that demonstrate how preschoolers act as young scientists in refining their intuitive representations of the world as they explore reality. New theoretical ideas and empirical research show that very young children’s learning and thinking are strikingly similar to much learning and thinking in science. Preschoolers test hypotheses against data and make causal inferences; they learn from statistics and informal experimentation, and from watching and listening to others. The mathematical framework of probabilistic models and Bayesian inference can describe this learning in precise ways. These discoveries have implications for early childhood education and policy. In particular, they suggest both that early childhood experience is extremely important and that the trend toward more structured and academic early childhood programs is misguided.

Words and Plans: Early Language and the Development of Intelligent Action.

Many early words encode aspects of plans, that is, actions performed in order to bring about events. Gone and down encode the fact that an action is intended to bring about a certain type of event. There and oh dear encode the success or failure of plans, no encodes the rejection of a plan. More encodes the repetition of a plan. It is argued that the concepts encoded by gone and down are like the concepts that underlie trial- and-error problem-solving and are developed after 12 months. The more abstract concepts encoded by there, oh dear, no and more are associated with the development of insight after 18 months. These early words are acquired because they are relevant to the childs cognitive problems.

Young Children Infer Causal Strength From Probabilities and Interventions

We examine the interaction of two cues that children use to make judgments about cause-effect relations: probabilities and interventions. Children were shown a “detector” that lit up and played music when a block was placed on its surface. We varied the probabilistic effectiveness of the block, as well as whether the experimenter or the child was performing the interventions. In Experiment 1, we found that children can use probabilistic evidence to make inferences about causal strength. However, when the results of their own interventions are in conflict with the overall frequencies, preschoolers favor the results of their own interventions. In Experiment 2, children used probabilistic evidence to infer a hidden causal mechanism. Though they again gave preference to their own interventions, they did not do so when their interventions were explicitly confounded by an alternative cause.