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Article de revue:
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ID no. (ISBN etc.): 0033-295X
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Clé de citation BibTeX: Brown1993
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Brown, N. R., & Siegler, R. S. (1993). Metrics and mappings: A framework for understanding real-world quantitative estimation. Psychological Review, 100(3), pp. 511–534.
Ajoutée par: Sterenn Audo 2008-02-19 11:41:52 Dernièrement modifiée par: Sterenn Audo 2008-02-19 14:47:50
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Catégories: Full text, Raisonnement
Descripteurs: Estimation (Mathematics); Graphs; Heuristics; Higher Education; Induction; Intuition; Knowledge Level; Mathematical Models; Mathematics Education; Thinking Skills; Undergraduate Students, Mapping; Metrics
Auteurs: Brown, Siegler
Collection: Psychological Review
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Nombre de vues: 322
Popularité: 29.25%
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Résumé
Estimation is influenced by a variety of processes: application of heuristics, domain-specific reasoning, and intuitive statistical induction among them. In this article, the authors propose the metrics and mapping framework to account for how these processes are integrated to generate estimates. This framework identifies 2 types of information as critical: knowledge of distributional properties (metric knowledge) and knowledge of relative status of individual entities within the distribution (mapping knowledge). Heuristics and domain-specific knowledge are both viewed as cues that contribute to mapping knowledge; intuitive statistical induction is viewed as providing cues to metric properties. Results of 4 experiments illustrate the framework's usefulness for integrating these types of information and for predicting when people emphasize heuristics and when they emphasize domain-specific knowledge. (PsycINFO Database Record (c) 2006 APA, all rights reserved)
Ajoutée par: Sterenn Audo Dernièrement modifiée par: Sterenn Audo
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Ajoutée par: Sterenn Audo
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