Literature DB >> 10495802

Automatically deriving readers' knowledge structures from texts.

P W Foltz1, A D Wells.   

Abstract

Latent semantic analysis (LSA) serves as both a theory and a method for representing the meaning of words based on a statistical analysis of their contextual usage (Foltz, 1996; Landauer & Dumais, 1997). In experiments in the domains of psychology and history, we compared the representation of readers' knowledge structures of information learned from texts with the representation generated by LSA. Results indicated that LSA's representation is similar to readers' representations. In addition, the degree to which the reader's representation is similar to LSA's representation is indicative of the amount of knowledge the reader has acquired and of the reader's reading ability. This approach has implications both as a model of learning from text and as a practical tool for performing knowledge assessment.

Mesh:

Year:  1999        PMID: 10495802     DOI: 10.3758/bf03207712

Source DB:  PubMed          Journal:  Behav Res Methods Instrum Comput        ISSN: 0743-3808


  2 in total

1.  Collective memory shapes the organization of individual memories in the medial prefrontal cortex.

Authors:  Pierre Gagnepain; Thomas Vallée; Serge Heiden; Matthieu Decorde; Jean-Luc Gauvain; Antoine Laurent; Carine Klein-Peschanski; Fausto Viader; Denis Peschanski; Francis Eustache
Journal:  Nat Hum Behav       Date:  2019-12-16

2.  Measuring information acquisition from sensory input using automated scoring of natural-language descriptions.

Authors:  Daniel R Saunders; Peter J Bex; Dylan J Rose; Russell L Woods
Journal:  PLoS One       Date:  2014-04-02       Impact factor: 3.240

  2 in total

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