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Pineño, O.; Miller, R.R. |
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Title |
Comparing associative, statistical, and inferential reasoning accounts of human contingency learning |
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Journal Article |
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2007 |
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Quarterly Journal of Experimental Psychology |
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60 |
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3 |
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310-329 |
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associative processes; statistics; inferential reasoning; human contingency learning; Inference; Learning; Reasoning |
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For more than two decades, researchers have contrasted the relative merits of associative and statistical theories as accounts of human contingency learning. This debate, still far from resolution, has led to further refinement of models within each family of theories. More recently, a third theoretical view has joined the debate: the inferential reasoning account. The explanations of these three accounts differ critically in many aspects, such as level of analysis and their emphasis on different steps within the information-processing sequence. Also, each account has important advantages (as well as critical flaws) and emphasizes experimental evidence that poses problems to the others. Some hybrid models of human contingency learning have attempted to reconcile certain features of these accounts, thereby benefiting from some of the unique advantages of different families of accounts. A comparison of these families of accounts will help us appreciate the challenges that research on human contingency learning will face over the coming years. (PsycINFO Database Record (c) 2007 APA, all rights reserved) (from the journal abstract) |
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Taylor & Francis |
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Miller, Ralph R., Department of Psychology, SUNY-Binghamton, Binghamton, NY, US, 13902-6000, rmiller |
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1747-0218Accession Number: 2007-03928-003. First Author & Affiliation: Pineño, Oskar; University of Seville, Seville, Spain. Other Journal Title: Quarterly Journal of Experimental Psychology. Release Date: 20070326. Publication Type: Journal (0100) Peer Reviewed Journal (0110). Media Covered: Electronic. Media Available: Electronic; Print. Document Type: Journal Article. Language: English. Major Descriptor: Associative Processes; Inference; Learning; Reasoning; Statistics. Classification: Learning & Memory (2343) . Population: Human (10) . Grant Information: The development of this paper was possible due to support from Department of Universities, Research, and Technology of the AndalucÃa Government (Junta de AndalucÃa) and NIMH Grant 33881. References Available: Y. |
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refbase @ user @ Pineño2007 |
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5012 |
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