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Related Experiment Video

Updated: May 23, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
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Published on: June 25, 2019

Lexical decision in children: sublexical processing or lexical search?

Madelon van den Boer1, Peter F de Jong, Marleen M Haentjens-van Meeteren

  • 1Research Institute of Child Development and Education, University of Amsterdam, The Netherlands. m.vandenboer@uva.nl

Quarterly Journal of Experimental Psychology (2006)
|April 12, 2012
PubMed
Summary

Children

Area of Science:

  • Cognitive Psychology
  • Developmental Psychology
  • Psycholinguistics

Background:

  • Children's reading development involves understanding word recognition processes.
  • Length effects in lexical decision tasks may suggest reliance on sublexical processing.
  • The role of sublexical vs. lexical processing in child reading is debated.

Purpose of the Study:

  • To investigate whether children use sublexical processing during lexical decision tasks.
  • To examine the influence of neighborhood size and articulatory suppression on children's lexical decisions.
  • To compare children's lexical decision strategies with those of adults.

Main Methods:

  • Lexical decision task administered to beginning and advanced child readers.
  • Manipulated variables included word length, neighborhood size, and articulatory suppression.

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  • Performance was assessed across standard, articulatory suppression, and tapping conditions.
  • Main Results:

    • Length effects were observed in children's lexical decisions for both words and nonwords.
    • Neighborhood size effects in children mirrored adult lexical decision patterns.
    • Articulatory suppression did not significantly impact children's lexical decision performance.

    Conclusions:

    • Children's lexical decision-making appears to rely on lexical search, similar to adults.
    • Despite length effects, children do not primarily use a naming task approach.
    • Findings challenge existing computational models of reading development.