Collaboration facilitates abstract category learning.
We examined the effects of collaboration (dyads vs. individuals) and category structure (coherent vs. incoherent) on learning and transfer. Working in dyads or individually, participants classified examples from either an abstract coherent category, the features of which are not fixed but relate in...
| Publicado en: | Memory & Cognition Vol. 46; no. 5; pp. 685 - 699 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Springer Nature
Jul2018
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| 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=130552657&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 130552657 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: Jul2018 vid: 46 iid: 5 pid: 237 pub: Springer Nature artinfo: ui: 130552657 10.3758/s13421-018-0795-7 ppf: 685 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P size: 650KB tig: atl: Collaboration facilitates abstract category learning. aug: au: Nokes-Malach, Timothy J. Cohen, Kara Richey, J. Elizabeth affil: Learning Research & Development Center, University of Pittsburgh, Pittsburgh, PA, USA Robert H. Smith School of Business, 4109 Susquehanna Hall, 7699 Mowatt Lane, 20742-1815, College Park, MD, USA su: Interpersonal relations Interprofessional relations Task performance Learning strategies sug: subj: Interpersonal relations Interprofessional relations Task performance Learning strategies keyword: Categories Collaboration Learning Metacognition Categories Collaboration Learning Metacognition ab: We examined the effects of collaboration (dyads vs. individuals) and category structure (coherent vs. incoherent) on learning and transfer. Working in dyads or individually, participants classified examples from either an abstract coherent category, the features of which are not fixed but relate in a meaningful way, or an incoherent category, the features of which do not relate meaningfully. All participants were then tested individually. We hypothesized that dyads would benefit more from classifying the coherent category structure because past work has shown that collaboration is more beneficial for tasks that build on shared prior knowledge and provide opportunities for explanation and abstraction. Results showed that dyads improved more than individuals during the classification task regardless of category coherence, but learning in a dyad improved inference-test performance only for participants who learned coherent categories. Although participants in the coherent categories performed better on a transfer test, there was no effect of collaboration. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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