Date
2013-06-18Metadata
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Aufsatz
Comparing apples and pears in studies on magnitude estimations
Abstract
The present article is concerned with studies on magnitude estimations that strived to uncover the underlying mental representation(s) of magnitudes. We point out a number of methodological differences and shortcomings that make it difficult drawing general conclusions. To solve this problem, we propose a taxonomy by which those studies could be classified, taking into account central methodological aspects of magnitude estimation tasks. Finally, we suggest perspectives for future research on magnitude estimations, which might abandon the hunt for the mathematical model that explains estimations best and turn, instead, to investigate the underlying principles of estimations (e.g., strategies) and ways of their improvement.
Citation
@article{doi:10.17170/kobra-202011052084,
author={Ebersbach, Mirjam and Luwel, Koen and Verschaffel, Lieven},
title={Comparing apples and pears in studies on magnitude estimations},
journal={Frontiers in Psychology},
year={2013}
}
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3010 Verschaffel, Lieven
4000 Comparing apples and pears in studies on magnitude estimations / Ebersbach, Mirjam
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5550 {{Bias}}
5550 {{Taxonomie}}
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<resource xsi:schemaLocation="http://datacite.org/schema/kernel-2.2 http://schema.datacite.org/meta/kernel-2.2/metadata.xsd"> 2020-11-17T11:12:32Z 2020-11-17T11:12:32Z 2013-06-18 doi:10.17170/kobra-202011052084 http://hdl.handle.net/123456789/11986 eng Namensnennung 4.0 International http://creativecommons.org/licenses/by/4.0/ magnitude estimations mental representation number line symbolic and non-symbolic magnitudes estimation biases 150 Comparing apples and pears in studies on magnitude estimations Aufsatz The present article is concerned with studies on magnitude estimations that strived to uncover the underlying mental representation(s) of magnitudes. We point out a number of methodological differences and shortcomings that make it difficult drawing general conclusions. To solve this problem, we propose a taxonomy by which those studies could be classified, taking into account central methodological aspects of magnitude estimation tasks. Finally, we suggest perspectives for future research on magnitude estimations, which might abandon the hunt for the mathematical model that explains estimations best and turn, instead, to investigate the underlying principles of estimations (e.g., strategies) and ways of their improvement. open access Ebersbach, Mirjam Luwel, Koen Verschaffel, Lieven doi:10.3389/fpsyg.2013.00332 Schätzung Wissensrepräsentation Bias Taxonomie publishedVersion EISSN: 1664-1078 Frontiers in Psychology Volume 4 false 332 </resource>
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