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Cognitive and Linguistic Skills Associated With Cross-Linguistic Transfer in the Production of Oral Narratives in English as a Foreign Language by Arabic- and Hebrew-Speaking Children: Finding Common Denominators

Summary

This study looks at oral language in English as a foreign language (EFL), an area that has received far less cross-linguistic research than reading and writing. The authors asked which first-language and English skills help children tell a coherent story in English. They tested 171 Israeli sixth graders: 85 native Arabic speakers, who also study Modern Standard Arabic and Hebrew, and 86 native Hebrew speakers. The battery covered general cognition, phonological memory, vocabulary, morphosyntax and reading comprehension in each child's languages. English narratives were elicited with the "Cookie Theft" picture and rated on two levels: microstructure, which captured how complex the children's word use and morphosyntax were, and macrostructure, which captured the story elements they included. The two were combined into a Total Narrative score.

Morphological awareness and reading comprehension were linked across languages, which suggests transfer even between distant languages. The strongest English-side predictor differed by group: English reading comprehension for Hebrew speakers and English morphological awareness for Arabic speakers. One shared third variable emerged for both groups: Hebrew derivational morphology on pseudo-words. The findings suggest that one national curriculum may not fit learners with different language repertoires.

Key points

  • The sample was 171 sixth graders in Israel: 85 Arabic speakers and 86 Hebrew speakers. All follow the same national English curriculum.
  • The Arabic speakers' language path is long:
    • a spoken dialect at home;
    • Modern Standard Arabic (MSA) from school entry;
    • Hebrew from grade 2;
    • English from grade 3, making it their fourth spoken language.
  • Narratives came from the "Cookie Theft" picture task. Adapted scales scored microstructure and macrostructure, and these were combined into a Total Narrative score. Macrostructure covered:
    • setting;
    • protagonist;
    • pronouns with antecedents;
    • attempts to solve the problem.
  • Regression results differed by group:
    • for Hebrew speakers, English reading comprehension (ERC) was the main predictor of the English narrative score;
    • for Arabic speakers, English morphological awareness (EMA) was the main predictor.
    • The authors link the Arabic result to these children's experience with several morphological systems.
  • Hebrew morphological derivation of pseudo-words acted as a confounding (third) variable for narrative skill in both groups. The results are framed with the Interdependence Hypothesis, the Linguistic Proximity Model, and accounts of direct versus indirect transfer.

Interesting ideas

  • I1. The paper scores a story on two separate axes: surface form (word choice, inflection, sentence complexity) and global structure (setting, protagonist, resolved references, problem solving). A text can then be fluent yet incomplete, or complete yet clumsy, and the scores show which. — For Mova (back): Generated retellings from the meaning graph could get two separate scores, a grammatical-form score and a story-element checklist, so failures in realization are not confused with lost content.
  • I2. Morphological knowledge is tested by asking children to derive forms from pseudo-words, which separates rule knowledge from memorized vocabulary. — For Mova (tokens): A nonce-word test set for the tagger and lemmatizer, using invented stems with real affixes, would show whether the morphology generalizes rules or just recalls the lexicon.
  • I3. The authors check for a third variable that correlates with both the predictor and the outcome before crediting a direct effect. — For Mova (learn): When an intermediate metric such as LAS seems to drive downstream accuracy, search for a hidden common driver (for example, sentence length or genre) as a negative control before claiming the link.
  • I4. The same task given to two related groups showed different underlying skill profiles, so an aggregate score would have hidden different mechanisms. — For Mova (learn): Report evaluation separately per text source or genre (fables, school tests, word problems), since each may lean on a different pipeline stage.
  • I5. The macrostructure scale treats pronouns that correctly point back to antecedents as part of story coherence, not just grammar. — For Mova (frames): Coreference quality could be judged at the narrative level, by whether every protagonist mention resolves to an entity, as a coherence check on the frame layer.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.3389/fpsyg.2021.664152

@inproceedings{russak2021cognitive,
  title = {{Cognitive and Linguistic Skills Associated With Cross-Linguistic Transfer in the Production of Oral Narratives in English as a Foreign Language by Arabic- and Hebrew-Speaking Children: Finding Common Denominators}},
  author = {Russak, Susie and Zaretsky, Elena},
  booktitle = {Frontiers in Psychology 12},
  year = {2021},
  doi = {10.3389/fpsyg.2021.664152},
  url = {https://doi.org/10.3389/fpsyg.2021.664152}
}

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