↓ Skip to main content

The GO model: A reconsideration of the role of structural units in guiding and organizing text on line

Overview of attention for article published in Psychonomic Bulletin & Review, June 2004
Altmetric Badge

Mentioned by

wikipedia
1 Wikipedia page
googleplus
3 Google+ users

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
37 Mendeley
Title
The GO model: A reconsideration of the role of structural units in guiding and organizing text on line
Published in
Psychonomic Bulletin & Review, June 2004
DOI 10.3758/bf03196590
Pubmed ID
Authors

Seth N. Greenberg, Alice F. Healy, Asher Koriat, Hamutal Kreiner

Abstract

Healy (1994) and Koriat and Greenberg (1994) offered different theoretical accounts of the missing-letter effect (MLE) in the letter-detection task, whereby a disproportionate number of letter-detection errors occur in frequent function words. Healy emphasized identification processes, whereas Koriat and Greenberg viewed the structural role of the embedding word to be crucial. Recent research suggests that neither position alone can account for the complete set of observations pertaining to the MLE. The present paper offers a theoretical integration of these competing explanations of letter detection in terms of a GO (guidance-organization) model of reading. This model specifies how structural processing of connected text helps guide eye movements to semantically informative parts of the text, enabling readers to achieve on-line fluency.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 5%
Japan 1 3%
United Kingdom 1 3%
Unknown 33 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 19%
Student > Master 5 14%
Professor 5 14%
Student > Ph. D. Student 4 11%
Professor > Associate Professor 4 11%
Other 10 27%
Unknown 2 5%
Readers by discipline Count As %
Psychology 18 49%
Linguistics 7 19%
Physics and Astronomy 2 5%
Medicine and Dentistry 2 5%
Computer Science 1 3%
Other 3 8%
Unknown 4 11%