Investigating the network structure of domain-specific knowledge using the semantic fluency task.

Cognitive scientists have a long-standing interest in quantifying the structure of semantic memory. Here, we investigate whether a commonly used paradigm to study the structure of semantic memory, the semantic fluency task, as well as computational methods from network science could be leveraged to...

Descripción completa

Detalles Bibliográficos
Publicado en:Memory & Cognition Vol. 51; no. 3; pp. 623 - 647
Autores principales: Siew, Cynthia S. Q., Guru, Anutra
Formato: Artículo
Publicado: Springer Nature Apr2023
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=162260003&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 162260003
    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: Apr2023
      vid: 51
      iid: 3
      pid: 237
      pub: Springer Nature
    artinfo:
      ui:
        162260003
        10.3758/s13421-022-01314-1
      ppf: 623
      ppct: 24
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 1.5MB
      tig:
        atl: Investigating the network structure of domain-specific knowledge using the semantic fluency task.
      aug:
        au:
          Siew, Cynthia S. Q.
          Guru, Anutra
        affil: Department of Psychology, National University of Singapore, 9 Arts Link, Block AS4, 117570, Singapore, Singapore
      su:
        Task performance
        Undergraduates
        Paradigms (Social sciences)
        Intellect
        Psychology of high school students
        Large-scale brain networks
        Semantic memory
        Research funding
        Prompts (Psychology)
      sug:
        subj:
          Task performance
          Undergraduates
          Paradigms (Social sciences)
          Intellect
          Psychology of high school students
          Large-scale brain networks
          Semantic memory
          Research funding
          Prompts (Psychology)
      keyword:
        Expertise
        Knowledge representation
        Semantic fluency task
        Semantic networks
        Expertise
        Knowledge representation
        Semantic fluency task
        Semantic networks
      ab: Cognitive scientists have a long-standing interest in quantifying the structure of semantic memory. Here, we investigate whether a commonly used paradigm to study the structure of semantic memory, the semantic fluency task, as well as computational methods from network science could be leveraged to explore the underlying knowledge structures of academic disciplines such as psychology or biology. To compare the knowledge representations of individuals with relatively different levels of expertise in academic subjects, undergraduate students (i.e., experts) and preuniversity high school students (i.e., novices) completed a semantic fluency task with cue words corresponding to general semantic categories (i.e., animals, fruits) and specific academic domains (e.g., psychology, biology). Network analyses of their fluency networks found that both domain-general and domain-specific semantic networks of undergraduates were more efficiently connected and less modular than the semantic networks of high school students. Our results provide an initial proof-of-concept that the semantic fluency task could be used by educators and cognitive scientists to study the representation of more specific domains of knowledge, potentially providing new ways of quantifying the nature of expert cognitive representations.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N