Categories and Causality: The Neglected Direction

Autor/inn/en	Waldmann, Michael R.; Hagmayer, York
Titel	Categories and Causality: The Neglected Direction
Quelle	In: Cognitive Psychology, 53 (2006) 1, S.27-58 (32 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0010-0285
DOI	10.1016/j.cogpsych.2006.01.001
Schlagwörter	Classification; Causal Models; Learning Processes; Attribution Theory; Shift Studies; Predictor Variables; Behavioral Science Research; Novelty (Stimulus Dimension); Sensory Integration + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Kausalanalyse; Learning process; Lernprozess; Schichtunterricht; Prädiktor; Sensorische Integration
Abstract	The standard approach guiding research on the relationship between categories and causality views categories as reflecting causal relations in the world. We provide evidence that the opposite direction also holds: categories that have been acquired in previous learning contexts may influence subsequent causal learning. In three experiments we show that identical causal learning input yields different attributions of causal capacity depending on the pre-existing categories to which the learning exemplars are assigned. There is a strong tendency to continue to use old conceptual schemes rather than switch to new ones even when the old categories are not optimal for predicting the new effect, and when they were motivated by goals that differed from the present context of causal discovery. However, we also found that the use of prior categories is dependent on the match between categories and causal effect. Whenever the category labels suggest natural kinds which can be plausibly related to the causal effects, transfer was observed. When the categories were arbitrary, or could not be plausibly related to the causal effect learners abandoned the categories, and used different categories to predict the causal effect. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10