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Aßfalg, André; Klauer, Karl Christoph – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
We consider the proposition that reasoners represent causal conditionals such as "if John studies hard, he will do well in the test" as a causal model in which the antecedent ("John studies hard") is a potential cause of the consequent ("John does well in the test"). Some studies suggest that reasoners ignore…
Descriptors: Logical Thinking, Causal Models, Evaluative Thinking, Probability
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Mayrhofer, Ralf; Waldmann, Michael R. – Cognitive Science, 2016
Research on human causal induction has shown that people have general prior assumptions about causal strength and about how causes interact with the background. We propose that these prior assumptions about the parameters of causal systems do not only manifest themselves in estimations of causal strength or the selection of causes but also when…
Descriptors: Causal Models, Bayesian Statistics, Inferences, Probability
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Nikiforidou, Zoi – European Early Childhood Education Research Journal, 2017
Risk is a fundamental component of well-being and is interconnected with all aspects of child development. The aim of this paper is to explore children's (N = 50) own perspectives and perceptions of risky situations. Semi-structured interviews were conducted and images were used as prompts. Children aged five to six years were asked to identify…
Descriptors: Risk, Preschool Children, Well Being, Childhood Attitudes
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Gopnik, Alison; Walker, Caren M. – American Journal of Play, 2013
Many researchers have long assumed imaginative play critical to the healthy cognitive, social, and emotional development of children, which has important implications for early-education policy and practice. But, the authors find, a careful review of the existing literature highlights a need for a better theory to clarify the nature of the…
Descriptors: Play, Child Development, Imagination, Logical Thinking
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Kemp, Charles; Shafto, Patrick; Tenenbaum, Joshua B. – Cognitive Psychology, 2012
Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single…
Descriptors: Generalization, Logical Thinking, Inferences, Probability
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Fernbach, Philip M.; Erb, Christopher D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…
Descriptors: Causal Models, Logical Thinking, Statistical Analysis, Validity
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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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Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B. – Psychological Review, 2011
The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…
Descriptors: Causal Models, Logical Thinking, Cognitive Development, Bayesian Statistics
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Holyoak, Keith J.; Lee, Hee Seung; Lu, Hongjing – Journal of Experimental Psychology: General, 2010
A fundamental issue for theories of human induction is to specify constraints on potential inferences. For inferences based on shared category membership, an analogy, and/or a relational schema, it appears that the basic goal of induction is to make accurate and goal-relevant inferences that are sensitive to uncertainty. People can use source…
Descriptors: Inferences, Logical Thinking, Bayesian Statistics, Causal Models
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Over, David E.; Hadjichristidis, Constantinos; Evans, Jonathan St. B. T.; Handley, Simon J.; Sloman, Steven A. – Cognitive Psychology, 2007
Conditionals in natural language are central to reasoning and decision making. A theoretical proposal called the Ramsey test implies the conditional probability hypothesis: that the subjective probability of a natural language conditional, P(if p then q), is the conditional subjective probability, P(q [such that] p). We report three experiments on…
Descriptors: Probability, Decision Making, Predictor Variables, Hypothesis Testing
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Griffiths, Thomas L.; Tenenbaum, Joshua B. – Cognitive Psychology, 2005
We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…
Descriptors: Probability, Logical Thinking, Inferences, Causal Models
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers