Deficits in category learning in older adults: Rule-based versus clustering accounts.

Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory,...

Descripción completa

Detalles Bibliográficos
Publicado en:Psychology & Aging Vol. 32; no. 5; pp. 473 - 489
Autores principales: Badham, Stephen P., Sanborn, Adam N., Maylor, Elizabeth A.
Formato: journal article
Publicado: American Psychological Association Aug2017
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=125047086&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 125047086
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        08827974
        PYG
      jtl: Psychology & Aging
      issn: 08827974
      maglogo: N
    pubinfo:
      dt: Aug2017
      vid: 32
      iid: 5
      pid: 34
      pub: American Psychological Association
    artinfo:
      ui:
        125047086
        10.1037/pag0000183
      ppf: 473
      ppct: 16
      formats:
      tig:
        atl: Deficits in category learning in older adults: Rule-based versus clustering accounts.
      aug:
        au:
          Badham, Stephen P.
          Sanborn, Adam N.
          Maylor, Elizabeth A.
        affil:
          Department of Psychology, Nottingham Trent University, Nottingham, United Kingdom
          Department of Psychology, University of Warwick, United Kingdom
      su:
        Psychological aspects of aging
        Aging
        Cognition
        Computer simulation
        Intelligence tests
        Learning
        Memory
        Mathematical models of psychology
        Research evaluation
        Research funding
      sug:
        subj:
          Psychological aspects of aging
          Aging
          Cognition
          Computer simulation
          Intelligence tests
          Learning
          Memory
          Mathematical models of psychology
          Research evaluation
          Research funding
      ab: Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory, and often on the process of learning relationships through trial and error. Categorization studies allow researchers to more accurately characterize age differences in cognition: whether older adults show declines in the way in which they represent categories with simple rules or declines in representing categories by similarity to past examples. In the current study, young and older adults participated in a set of classic category learning problems, which allowed us to distinguish between three hypotheses: (a) rule-complexity: categories were represented exclusively with rules and older adults had differential difficulty when more complex rules were required, (b) rule-specific: categories could be represented either by rules or by similarity, and there were age deficits in using rules, and (c) clustering: similarity was mainly used and older adults constructed a less-detailed representation by lumping more items into fewer clusters. The ordinal levels of performance across different conditions argued against rule-complexity, as older adults showed greater deficits on less complex categories. The data also provided evidence against rule-specificity, as single-dimensional rules could not explain age declines. Instead, computational modeling of the data indicated that older adults utilized fewer conceptual clusters of items in memory than did young adults. (PsycINFO Database Record
      pubtype: Academic Journal
      doctype: journal article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N