The role of textual coherence in incremental analogical mapping

Tate T. Kubose; Keith J. Holyoak; John E. Hummel

doi:10.1016/S0749-596X(02)00011-6

The role of textual coherence in incremental analogical mapping

Tate T. Kubose, Keith J. Holyoak, John E. Hummel

Research output: Contribution to journal › Article › peer-review

Abstract

The LISA model of analogical reasoning (Hummel & Holyoak, 1997) assumes that mapping is performed incrementally within limited-capacity working memory, and that processing is guided by principles of text coherence. Predictions of the model derived by computer simulations were tested in four experiments, using both semantically impoverished structural analogs and semantically rich story analogs. Results for college students revealed a grouping effect. Processing multiple propositions together generated more accurate mappings than did processing individual propositions, but only when propositions that jointly provided strong structural constraints were grouped together. Other experiments revealed asymmetries in mapping and inference accuracy: mappings and inferences generated from a more coherent analog to a less coherent analog were more accurate than those made in the reverse direction. Implications for computational models of analogical reasoning and for education are discussed.

Original language	English (US)
Pages (from-to)	407-435
Number of pages	29
Journal	Journal of Memory and Language
Volume	47
Issue number	3
DOIs	https://doi.org/10.1016/S0749-596X(02)00011-6
State	Published - 2002
Externally published	Yes

Keywords

Analogy
Coherence
Computational model
Mapping
Working memory

ASJC Scopus subject areas

Neuropsychology and Physiological Psychology
Language and Linguistics
Experimental and Cognitive Psychology
Linguistics and Language
Artificial Intelligence

Online availability

10.1016/S0749-596X(02)00011-6

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title = "The role of textual coherence in incremental analogical mapping",

abstract = "The LISA model of analogical reasoning (Hummel & Holyoak, 1997) assumes that mapping is performed incrementally within limited-capacity working memory, and that processing is guided by principles of text coherence. Predictions of the model derived by computer simulations were tested in four experiments, using both semantically impoverished structural analogs and semantically rich story analogs. Results for college students revealed a grouping effect. Processing multiple propositions together generated more accurate mappings than did processing individual propositions, but only when propositions that jointly provided strong structural constraints were grouped together. Other experiments revealed asymmetries in mapping and inference accuracy: mappings and inferences generated from a more coherent analog to a less coherent analog were more accurate than those made in the reverse direction. Implications for computational models of analogical reasoning and for education are discussed.",

keywords = "Analogy, Coherence, Computational model, Mapping, Working memory",

author = "Kubose, {Tate T.} and Holyoak, {Keith J.} and Hummel, {John E.}",

note = "Funding Information: Preparation of this paper was supported by NSF Grant SBR-9729023. The paper is based in part on a Ph.D. dissertation completed at UCLA by the first author under the direction of the second and third authors. Preliminary reports of some experiments were presented as posters at the 1997 meeting of the Psychonomic Society, at the 1997 and 1998 meetings of the Cognitive Science Society, and as a talk at the 2000 meeting of the Psychonomic Society. We thank Andrew Scholer for running the initial experiment discussed in Experiment 1, and Joe Leung and An Tran for their assistance in data collection. Mark Keane, Art Markman, and anonymous reviewers provided helpful comments on earlier drafts. ",

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doi = "10.1016/S0749-596X(02)00011-6",

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AU - Kubose, Tate T.

AU - Holyoak, Keith J.

AU - Hummel, John E.

N1 - Funding Information: Preparation of this paper was supported by NSF Grant SBR-9729023. The paper is based in part on a Ph.D. dissertation completed at UCLA by the first author under the direction of the second and third authors. Preliminary reports of some experiments were presented as posters at the 1997 meeting of the Psychonomic Society, at the 1997 and 1998 meetings of the Cognitive Science Society, and as a talk at the 2000 meeting of the Psychonomic Society. We thank Andrew Scholer for running the initial experiment discussed in Experiment 1, and Joe Leung and An Tran for their assistance in data collection. Mark Keane, Art Markman, and anonymous reviewers provided helpful comments on earlier drafts.

PY - 2002

Y1 - 2002

N2 - The LISA model of analogical reasoning (Hummel & Holyoak, 1997) assumes that mapping is performed incrementally within limited-capacity working memory, and that processing is guided by principles of text coherence. Predictions of the model derived by computer simulations were tested in four experiments, using both semantically impoverished structural analogs and semantically rich story analogs. Results for college students revealed a grouping effect. Processing multiple propositions together generated more accurate mappings than did processing individual propositions, but only when propositions that jointly provided strong structural constraints were grouped together. Other experiments revealed asymmetries in mapping and inference accuracy: mappings and inferences generated from a more coherent analog to a less coherent analog were more accurate than those made in the reverse direction. Implications for computational models of analogical reasoning and for education are discussed.

AB - The LISA model of analogical reasoning (Hummel & Holyoak, 1997) assumes that mapping is performed incrementally within limited-capacity working memory, and that processing is guided by principles of text coherence. Predictions of the model derived by computer simulations were tested in four experiments, using both semantically impoverished structural analogs and semantically rich story analogs. Results for college students revealed a grouping effect. Processing multiple propositions together generated more accurate mappings than did processing individual propositions, but only when propositions that jointly provided strong structural constraints were grouped together. Other experiments revealed asymmetries in mapping and inference accuracy: mappings and inferences generated from a more coherent analog to a less coherent analog were more accurate than those made in the reverse direction. Implications for computational models of analogical reasoning and for education are discussed.

KW - Analogy

KW - Coherence

KW - Computational model

KW - Mapping

KW - Working memory

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The role of textual coherence in incremental analogical mapping

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Keywords

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