9 found
Order:
  1.  24
    Linguistic entrenchment: Prior knowledge impacts statistical learning performance.Noam Siegelman, Louisa Bogaerts, Amit Elazar, Joanne Arciuli & Ram Frost - 2018 - Cognition 177 (C):198-213.
    No categories
    Direct download (3 more)  
     
    Export citation  
     
    Bookmark   22 citations  
  2.  38
    Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?Noam Siegelman, Louisa Bogaerts, Ofer Kronenfeld & Ram Frost - 2018 - Cognitive Science 42 (S3):692-727.
    From a theoretical perspective, most discussions of statistical learning have focused on the possible “statistical” properties that are the object of learning. Much less attention has been given to defining what “learning” is in the context of “statistical learning.” One major difficulty is that SL research has been monitoring participants’ performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow a brief visual or auditory familiarization (...)
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   16 citations  
  3.  22
    Regularity Extraction Across Species: Associative Learning Mechanisms Shared by Human and Non‐Human Primates.Arnaud Rey, Laure Minier, Raphaëlle Malassis, Louisa Bogaerts & Joël Fagot - 2019 - Topics in Cognitive Science 11 (3):573-586.
    One of the themes that has been widely addressed in both the implicit learning and statistical learning literatures is that of rule learning. While it is widely agreed that the extraction of regularities from the environment is a fundamental facet of cognition, there is still debate about the nature of rule learning. Rey and colleagues show that the comparison between human and non‐human primates can contribute important insights to this debate.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   9 citations  
  4.  9
    When the “Tabula” is Anything but “Rasa:” What Determines Performance in the Auditory Statistical Learning Task?Amit Elazar, Raquel G. Alhama, Louisa Bogaerts, Noam Siegelman, Cristina Baus & Ram Frost - 2022 - Cognitive Science 46 (2):e13102.
    Cognitive Science, Volume 46, Issue 2, February 2022.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  5.  13
    What exactly is learned in visual statistical learning? Insights from Bayesian modeling.Noam Siegelman, Louisa Bogaerts, Blair C. Armstrong & Ram Frost - 2019 - Cognition 192 (C):104002.
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  6.  53
    Can Chunk Size Differences Explain Developmental Changes in Lexical Learning?Eleonore H. M. Smalle, Louisa Bogaerts, Morgane Simonis, Wouter Duyck, Michael P. A. Page, Martin G. Edwards & Arnaud Szmalec - 2015 - Frontiers in Psychology 6.
    Direct download (9 more)  
     
    Export citation  
     
    Bookmark   8 citations  
  7.  6
    Implicit Statistical Learning Across Modalities and Its Relationship With Reading in Childhood.Elpis V. Pavlidou & Louisa Bogaerts - 2019 - Frontiers in Psychology 10.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  8.  13
    Literacy improves short-term serial recall of spoken verbal but not visuospatial items – Evidence from illiterate and literate adults.Eleonore H. M. Smalle, Arnaud Szmalec, Louisa Bogaerts, Mike P. A. Page, Vaishna Narang, Deepshikha Misra, Susana Araújo, Nishant Lohagun, Ouroz Khan, Anuradha Singh, Ramesh K. Mishra & Falk Huettig - 2019 - Cognition 185 (C):144-150.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  9.  10
    What Determines Visual Statistical Learning Performance? Insights From Information Theory.Noam Siegelman, Louisa Bogaerts & Ram Frost - 2019 - Cognitive Science 43 (12):e12803.
    In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests that variance in statistical learning (SL) performance reflects efficiency in encoding representations as well as efficiency in detecting their statistical properties. These processes have been taken to be independent and temporally modular, where first, elements in the stream are encoded into internal representations, and then the co‐occurrences between them are (...)
    No categories
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark