Development of children's identity and position processing for letter, digit, and symbol strings

a cross-sectional study of the primary school years

Teresa Schubert*, Nicholas Badcock, Saskia Kohnen

*Corresponding author for this work

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Letter recognition and digit recognition are critical skills for literate adults, yet few studies have considered the development of these skills in children. We conducted a nine-alternative forced-choice (9AFC) partial report task with strings of letters and digits, with typographical symbols (e.g., $, @) as a control, to investigate the development of identity and position processing in children. This task allows for the delineation of identity processing (as overall accuracy) and position coding (as the proportion of position errors). Our participants were students in Grade 1 to Grade 6, allowing us to track the development of these abilities across the primary school years. Our data suggest that although digit processing and letter processing end up with many similarities in adult readers, the developmental trajectories for identity and position processing for the two character types differ. Symbol processing showed little developmental change in terms of identity or position accuracy. We discuss the implications of our results for theories of identity and position coding: modified receptive field, multiple-route model, and lexical tuning. Despite moderate success for some theories, considerable theoretical work is required to explain the developmental trajectories of letter processing and digit processing, which might not be as closely tied in child readers as they are in adult readers.

Original languageEnglish
Pages (from-to)163-180
Number of pages18
JournalJournal of Experimental Child Psychology
Volume162
DOIs
Publication statusPublished - Oct 2017

Keywords

  • digit identification
  • letter identification
  • letter position coding
  • partial report
  • reading
  • reading development
  • visual recognition

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