Contrasting Predictive and Causal Values of Predictors and of Causes

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
James Denniston Ph.D., Associate Professor and Department Chairperson (Creator)
Appalachian State University (ASU )
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Abstract: Three experiments examined human processing of stimuli as predictors and causes. In Experiments 1A and 1B, two serial events that both preceded a third were assessed as predictors and as causes of the third event. Instructions successfully provided scenarios in which one of the serial (target) stimuli was viewed as a strong predictor but as a weak cause of the third event. In Experiment 2, participants’ preexperimental knowledge was drawn upon in such a way that two simultaneous antecedent events were processed as predictors or causes, which strongly influenced the occurrence of overshadowing between the antecedent events. Although a tendency toward overshadowing was found between predictors, reliable overshadowing was observed only between causes, and then only when the test question was causal. Together with other evidence in the human learning literature, the present results suggest that predictive and causal learning obey similar laws, but there is a greater susceptibility to cue competition in causal than predictive attribution.

Additional Information

Pineño, O., Denniston, J. C., Beckers, T., Matute, H., & Miller, R. R. (2005). Contrasting predictive and causal values of predictors and of causes. Learning & Behavior, 33(2): 184-196. (May 2005) Published by Springer Verlag (ISSN: 1543-4508). DOI: 10.3758/BF03196062
Language: English
Date: 2005

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