Between automatic and control processes: How relationships between problem elements interact to facilitate or impede insight.
Solving a problem requires relating the pieces of information available to each other and to the solution. We investigated how the strength of these relationships determines the likelihood of solving insight tasks based on remote associates. In these tasks, the solver is provided with several cues (...
| Publicado en: | Memory & Cognition Vol. 50; no. 8; pp. 1719 - 1735 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Nov2022
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=160894498&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 160894498 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0090502X MEG jtl: Memory & Cognition issn: 0090502X maglogo: N pubinfo: dt: Nov2022 vid: 50 iid: 8 pid: 237 pub: Springer Nature artinfo: ui: 160894498 10.3758/s13421-022-01277-3 ppf: 1719 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.2MB tig: atl: Between automatic and control processes: How relationships between problem elements interact to facilitate or impede insight. aug: au: Becker, Maxi Davis, Simon Cabeza, Roberto affil: Humboldt University of Berlin, Department of Psychology, Unter den Linden 6, 10177, Berlin, Germany Duke University, Center for Cognitive Neuroscience, 27708, Durham, NC, USA su: Semantics Problem solving Task performance Cognition Control (Psychology) Mathematical models Time Conceptual structures Theory Prompts (Psychology) sug: subj: Semantics Problem solving Task performance Cognition Control (Psychology) Mathematical models Time Conceptual structures Theory Prompts (Psychology) keyword: Cognitive control Insight Remote associates task Spreading activation Cognitive control Insight Remote associates task Spreading activation ab: Solving a problem requires relating the pieces of information available to each other and to the solution. We investigated how the strength of these relationships determines the likelihood of solving insight tasks based on remote associates. In these tasks, the solver is provided with several cues (e.g., drop, coat, summer) and has to find the solution that matches those cues (e.g., rain). We measured the semantic similarity between the cues and the solution (cue–solution similarity) as well as between cues (cue–cue similarity). We assume those relationships modulate two basic processes underlying insight problem-solving. First, there is an automatic activation process whereby conceptual activation spreads across a semantic network from each cue node to their associated nodes, potentially reaching the node of the solution. Thus, in general, the higher cue–solution similarity, the more likely the solution will be found (Prediction 1). Second, there is a controlled search process focused on an area in semantic space whose radius depends on competing cue–cue similarity. High cue–cue similarity will bias a search for the solution close to the provided cues because the associated nodes shared by both cues are highly coactivated. Therefore, high cue–cue similarity will have a beneficial effect when the cue–solution similarity is high but a detrimental effect when cue–solution similarity is low (Prediction 2). Our two predictions were confirmed using both verbal and pictorial remote association tasks, supporting the view that insight is dependent on an interaction of meaningful relationships between cues and solutions, and clarify the mechanisms of insight problem solving in remote associates. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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