Biomedical subjects

Alison Gopnik

Publications and source records attributed to Alison Gopnik.

8 recordsLinked to original sources

PubMed2007

Conditional probability versus spatial contiguity in causal learning: Preschoolers use new contingency evidence to overcome prior spatial assumptions.

This study examines preschoolers' causal assumptions about spatial contiguity and how these assumptions interact with new evidence in the form of conditional probabilities. Preschoolers saw a toy that activated in the presence of certain objects. Children were shown evidence for the toy's activation rule in the form of patterns of probability: The toy was more likely to activate either when objects made contact with its surface (on condition) or when objects were several inches above its surface (over condition). In Experiment 1, 61 three-year-olds saw a deterministic activation rule. In Experiments 2 and 3, 48 four-year-olds saw an activation rule that was probabilistic. In Experiment 4, 30 four-year-olds saw a screening-off pattern of activation. In all 4 experiments, children used new evidence in the form of patterns of probability to make accurate causal inferences, even in the face of conflicting prior beliefs about spatial contiguity. However, children were more likely to make correct inferences when causes were spatially contiguous, particularly when faced with ambiguous evidence.

Association Learning↗

PubMed2006

Reversing how to think about ambiguous figure reversals: spontaneous alternating by uninformed observers.

Ambiguous figures are a special class of images that can give rise to multiple interpretations. Traditionally, switching between the possible interpretations of an ambiguous figure, or reversing one's interpretation, has been attributed either to top-down or to bottom-up processes (e.g. attributed to having knowledge of the nature of the ambiguity, or to a form of neuronal fatigue). Here we present evidence that is incompatible with both forms of explanations. Observers aged 5-9 years can reverse ambiguous figures when uninformed about the ambiguity, negating purely top-down explanations. Further, those children who make these 'spontaneous' reversals are more likely to succeed on a high-order theory-of-mind task, negating purely bottom-up explanations.

Afterimage↗

PubMed2005

Asynchrony in the cognitive and lexical development of young children with Williams syndrome.

The present study investigates whether five-to-six-year-old children with Williams syndrome (N = 8) can form new object categories based on naming information alone, and compares them with five groups of typically developing children aged 2;0 to 6;0 (N = 34 children). Children were presented with triads of dissimilar objects; all objects in a triad were labelled, two of them with the same pseudoname. Name-based categorization was evaluated through object selection. Performance was above chance level for all groups. Performance reached a ceiling at about 4;0 for the typically developing children. For the children with Williams Syndrome, performance remained below chronological age level. The present results are discussed in light of previous findings of a failure to perform name-based categorization in younger children with Williams syndrome and the persistent asynchrony between cognitive and lexical development in this disorder.

Child↗

PubMed2005

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.

Child↗

PubMed2004

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 children's ability to learn from evidence in the form of conditional probabilities, interventions and combinations of the two.

Bayes Theorem↗

PubMed2004

Causal learning across domains.

Five studies investigated (a) children's 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, children's 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.

Association Learning↗

PubMed2004

A theory of causal learning in children: causal maps and Bayes nets.

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Adult↗

PubMed2002

Source monitoring reduces the suggestibility of preschool children.

The relation between source monitoring and suggestibility was examined among preschool children. Thirty-two 3- to 5-year-olds were simultaneously presented with a brief story in two different modalities, as a silent video vignette and a spoken narrative. Each modality presented unique information about the story, but the information in the two versions was mutually compatible. The children were then asked a series of questions, including questions about the source (modality) of story details, and leading questions about story details (to assess suggestibility). Performance on the source-monitoring questions was highly correlated with the ability to resist suggestion. In addition, children who were asked source-monitoring questions prior to leading questioning were less susceptible to suggestion than were those who were asked the leading questions first. This study provides evidence that source monitoring can play a causal role in reducing the suggestibility of preschool children.

Child, Preschool↗