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Generating explanations via analogical comparison

Overview of attention for article published in Psychonomic Bulletin & Review, April 2017
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Title
Generating explanations via analogical comparison
Published in
Psychonomic Bulletin & Review, April 2017
DOI 10.3758/s13423-017-1289-5
Pubmed ID
Authors

Christian Hoyos, Dedre Gentner

Abstract

Generating explanations can be highly effective in promoting learning in both adults and children. Our interest is in the mechanisms that underlie this effect and in whether and how they operate in early learning. In adult reasoning, explanation may call on many subprocesses-including comparison, counterfactual reasoning, and reasoning by exclusion; but it is unlikely that all these processes are available to young children. We propose that one process that may serve both children and adults is comparison. In this study, we asked whether children would use the results of a comparison experience when asked to explain why a model skyscraper was stable. We focused on a challenging principle-that diagonal cross-bracing lends stability to physical structures (Gentner et al., Cognitive Science, 40, 224-240, 2016). Six-year-olds either received no training or interacted with model skyscrapers in one of three different conditions, designed to vary in their potential to invite and support comparison. In the Single Model condition, children interacted with a single braced model. In the comparison conditions (Low Alignability and High Alignability), children compared braced and unbraced models. Following experience with the models, children were asked to explain why the braced model was stable. They then received two transfer tasks. We found that children who received highly alignable pairs were most likely to (a) produce brace-based explanations and (b) transfer the brace principle to a dissimilar context. This provides evidence that children can benefit from analogical comparison in generating explanations and also suggests limitations on this ability.

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Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 30%
Student > Master 11 17%
Researcher 5 8%
Lecturer 4 6%
Professor > Associate Professor 3 5%
Other 8 13%
Unknown 14 22%
Readers by discipline Count As %
Psychology 16 25%
Computer Science 7 11%
Philosophy 4 6%
Linguistics 3 5%
Social Sciences 3 5%
Other 13 20%
Unknown 18 28%