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| Research article summary (published 27 Feb 2002): |
Why aggregated learning follows the power law of practice when individual learning does not: comment on Rickard (1997, 1999), Delaney et al. (1998), and Palmeri (1999).
Full Abstract
The power law of practice is often considered a benchmark test for theories of cognitive skill acquisition. Recently, P. F. Delaney, L. M. Reder, J. J. Staszewski, and F. E. Ritter (1998), T. J. Palmeri (1999), and T. C. Rickard (1997, 1999) have challenged its validity by showing that empirical data can systematically deviate from power-function fits. The main purpose of the present article is to extend their explanations in two ways. First, the authors empirically show that abrupt changes in performance are not necessarily based on a shift from algorithm to memory-based processing, but rather and more generally, that they occur whenever a more efficient task strategy is generated. Second, the authors show mathematically and per simulation that power functions can perfectly fit aggregated learning curves even when all underlying individual curves are discontinuous. Therefore, the authors question conclusions drawn from fits to aggregated data.
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Author information
Author/s: Haider, Hilde (H); Frensch, Peter A (PA);
Affiliation: Institut für Psychologie, University of Köln, Germany. hilde.haider@uni-koeln.de
Journal and publication information
Publication Type: Journal Article
Journal: Journal of experimental psychology. Learning, memory, and cognition (J Exp Psychol Learn Mem Cogn), published in United States. (Language: eng)
Reference: 2002-Mar; vol 28 (issue 2) : pp 392-406
Dates: Created 2002/03/25; Completed 2002/09/06; Revised 2004/11/17;
PMID: 11911396, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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