Category learning in a transitive inference paradigm.

The implied order of a ranked set of visual images can be learned without reliance on information that explicitly signals their order. Such learning is difficult to explain by associative mechanisms, but can be accounted for by cognitive representations and processes such as transitive inference. Ou...

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Publicado en:Memory & Cognition Vol. 49; no. 5; pp. 1020 - 1036
Autores principales: Jensen, Greg, Kao, Tina, Michaelcheck, Charlotte, Borge, Saani Simms, Ferrera, Vincent P., Terrace, Herbert S.
Formato: Artículo
Publicado: Springer Nature Jul2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2021
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      pub: Springer Nature
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        10.3758/s13421-020-01136-z
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        atl: Category learning in a transitive inference paradigm.
      aug:
        au:
          Jensen, Greg
          Kao, Tina
          Michaelcheck, Charlotte
          Borge, Saani Simms
          Ferrera, Vincent P.
          Terrace, Herbert S.
        affil:
          Department of Neuroscience, Columbia University, New York, NY, USA
          Zuckerman Mind Brain Behavior Institute, Columbia University, 3227 Broadway, 10027, New York, NY, USA
          Department of Psychology, Columbia University, New York, NY, USA
          Department of Psychology, Barnard College, New York, NY, USA
          Department of Psychology, New York City College of Technology, CUNY, New York, NY, USA
          Department of Psychiatry, Columbia University, New York, NY, USA
      su:
        Teaching methods
        Cognition
        Student attitudes
        Speech perception
        Auditory perception
        Audiovisual materials
        Learning strategies
        Prompts (Psychology)
        Space perception
        Educational outcomes
      sug:
        subj:
          Teaching methods
          Cognition
          Student attitudes
          Speech perception
          Auditory perception
          Audiovisual materials
          Learning strategies
          Prompts (Psychology)
          Space perception
          Educational outcomes
      keyword:
        Categorization
        Serial learning
        Symbolic distance effect
        Transitive inference
        Categorization
        Serial learning
        Symbolic distance effect
        Transitive inference
      ab: The implied order of a ranked set of visual images can be learned without reliance on information that explicitly signals their order. Such learning is difficult to explain by associative mechanisms, but can be accounted for by cognitive representations and processes such as transitive inference. Our study sought to determine if those processes also apply to learning categories of images. We asked whether participants can (a) infer that stimulus images belonged to familiar categories, even when the images for each trial were unique, and (b) sort those categories into an ordering that obeys transitivity. Participants received minimal verbal instruction and a single session of training. Despite this, they learned the implied order of lists of fixed stimuli and lists of ordered categories, using trial-unique exemplars. We trained two groups, one for which stimuli were constant throughout training and testing (n = 60), and one for which exemplars of each category were trial-unique (n = 50). Our findings suggest that differing cognitive processes may underpin serial learning when learning about specific stimuli as opposed to stimulus categories.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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