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Predicting Arabic word reading: A cross-classified generalized random-effects analysis showing the critical role of morphology

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A Correction to this article was published on 08 July 2020

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Abstract

The distinctive features of the Arabic language and orthography offer opportunities to investigate multiple word characteristics at the item level. The aim of this paper was to model differences in word reading at the item level among 3rd grade native Arabic-speaking children (n = 303) using cross-classified generalized random-effects (CCGRE) analysis. The participants read 80 vowelized words that varied in multiple elements that may contribute to their decodability: number of letters, number of syllables, number of morphemes, ligaturing (connectivity), semantics (concrete vs. abstract), orthographic frequency, root type frequency, and part of speech. Morphological awareness (MA) was included as a person-level predictor. Results of individual models showed that MA, number of letters, number of syllables, number of morphemes, number of ligatures, orthographic frequency, and part of speech were significantly related to the probability of a correct response. However, when all predictors were entered simultaneously, only MA and number of morphemes remained significant. These results underscore the important role of morphology in the lexical structure of Arabic words and in Arabic word reading. Discussion focuses on the role of morphology in Arabic reading and the implications for intervention to improve word recognition in children learning to read Arabic.

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Change history

  • 08 July 2020

    The original version of this article unfortunately contained the following errors.

Notes

  1. Clitics are morphemes that may attach to the word as unstressed prefixes or suffixes and more than one can co-occur within the same word, resulting in one-word phrases and clauses.

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Acknowledgments

The authors would like to give special thanks to the Ministry of Education in Dubai and the Abu Dhabi Council for Education, United Arab Emirates, who allowed us to work with school children to collect data for this project.

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Authors and Affiliations

  1. School of Communication Science and Disorders, Florida State University, Tallahassee, FL, USA

    Sana Tibi

  2. Department of Psychology, Florida State University, Tallahassee, FL, USA

    Ashley A. Edwards & Christopher Schatschneider

  3. Faculty of Education, Queen’s University, Ontario, Canada

    John R. Kirby

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  1. Sana Tibi
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  2. Ashley A. Edwards
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  3. Christopher Schatschneider
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  4. John R. Kirby
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Correspondence to Sana Tibi.

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Tibi, S., Edwards, A.A., Schatschneider, C. et al. Predicting Arabic word reading: A cross-classified generalized random-effects analysis showing the critical role of morphology. Ann. of Dyslexia 70, 200–219 (2020). https://doi.org/10.1007/s11881-020-00193-y

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  • DOI: https://doi.org/10.1007/s11881-020-00193-y

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