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McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…
Descriptors: Probability, Age Differences, Children, Intervention
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Khemlani, Sangeet S.; Oppenheimer, Daniel M. – Psychological Bulletin, 2011
Discounting is a phenomenon in causal reasoning in which the presence of one cause casts doubt on another. We provide a survey of the descriptive and formal models that attempt to explain the discounting process and summarize what current models do not account for and where room for improvement exists. We propose a levels-of-analysis framework…
Descriptors: Causal Models, Probability, Computation, Logical Thinking
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Lombrozo, Tania – Cognitive Psychology, 2010
Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…
Descriptors: Causal Models, Intention, Attribution Theory, Cognitive Processes
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Jonassen, David H.; Ionas, Ioan Gelu – Educational Technology Research and Development, 2008
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…
Descriptors: Cognitive Processes, Inferences, Thinking Skills, Causal Models
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Lombrozo, Tania; Carey, Susan – Cognition, 2006
Teleological explanations (TEs) account for the existence or properties of an entity in terms of a function: we have hearts because they pump blood, and telephones for communication. While many teleological explanations seem appropriate, others are clearly not warranted--for example, that rain exists for plants to grow. Five experiments explore…
Descriptors: Philosophy, Experiments, Psychology, Artificial Intelligence
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Sloman, Steven A.; Lagnado, David A. – Cognitive Science, 2005
A normative framework for modeling causal and counterfactual reasoning has been proposed by Spirtes, Glymour, and Scheines (1993; cf. Pearl, 2000). The framework takes as fundamental that reasoning from observation and intervention differ. Intervention includes actual manipulation as well as counterfactual manipulation of a model via thought. To…
Descriptors: Observation, Intervention, Causal Models, Prediction
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Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David – Psychological Review, 2004
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…
Descriptors: Causal Models, Young Children, Learning Strategies, Cognitive Processes
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Hirschfeld, Lawrence A. – Cognition, 1997
Responds to John J. Kim's critique of his studies of preschoolers' understanding of race. Maintains that his and others' investigations demonstrate that preschoolers differentiate the pattern of causal reasoning governing transmission and maintenance of racial characteristics from that governing transmission and maintenance of perceptually similar…
Descriptors: Attribution Theory, Causal Models, Childhood Attitudes, Cognitive Development
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Deary, Ian J. – Developmental Psychology, 1995
Tested three competing structural equation models concerning auditory inspection time (AIT) and cognitive ability. Found that auditory inspection times near age 11 correlate most strongly with later high IQ. (ET)
Descriptors: Adolescents, Attribution Theory, Auditory Perception, Causal Models