Use of predictive text in text messaging over the course of a year and its relationship with spelling, orthographic processing and grammar

Sam Waldron, Clare Wood, N. Kemp

Research output: Contribution to journalArticle

5 Citations (Scopus)
151 Downloads (Pure)

Abstract

An investigation into the impact of predictive text use upon the literacy skills of primary school, secondary school and university cohorts was conducted over the course of a year. No differences in use of text abbreviations (‘textisms’) were found between predictive text users and non-users. However, secondary school children who used predictive text made more genuine spelling errors than non-users. Predictive text was related to use of some specific grammatical violations in school-age children’s text messages, but was not related overall to the tendency to make grammatical errors when texting. University students, however, made significantly fewer grammatical errors in their text messages when they used predictive text. Over the course of a year, predictive text use was variable for all age groups. Consistency of predictive text use was unrelated to grammatical understanding, spelling or orthographic processing for primary and secondary school cohorts. Predictive text use was negatively related to morphological awareness for adult participants This is the peer reviewed version of the following article: Waldron, S, Wood, C & Kemp, N 2016, 'Use of predictive text in text messaging over the course of a year and its relationship with spelling, orthographic processing and grammar' Journal of Research in Reading, vol (In Press). DOI: 10.1111/1467-9817.12073, which has been published in final form at https://dx.doi.org/10.1111/1467-9817.12073 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Original languageEnglish
JournalJournal of Research in Reading
Volume(In Press)
DOIs
Publication statusPublished - 10 May 2016

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Keywords

  • computer-mediated communication
  • SMS
  • grammar
  • predictive text

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