Bilingual narrative development: Analyzing sentences and stories within and across languages

Aims and objectives: Narrative samples provide an ecologically valid measurement of bilingual children’s skills at the sentence (microstructure) and story levels (macrostructure). Cross-language transfer of narrative macrostructure would indicate that children can leverage their storytelling skills in one language to support storytelling in the other. A rigorous test of cross-language transfer needs to control for age and within-language microstructure skills. Methodology: We analyzed Spanish and English narrative retells produced by 109 typically developing bilingual participants, aged 5–7 years, using the Multilingual Assessment Instrument for Narratives. Microstructure measures included the number of different words (NDW) and the mean length of utterance in words (MLUw). Macrostructure was measured using the MAIN’s goal–attempt–outcome (GAO) complexity rating. Data and analysis: To examine associations between L1 and L2 macrostructure, analyses included bivariate correlations and two hierarchical linear regressions predicting L1 and L2 macrostructure, respectively, with cross-language macrostructure, age, and microstructure measures as predictors. Findings/conclusion: As anticipated, within-language microstructure contributed to macrostructure, suggesting that microstructure skills like vocabulary (e.g., NDW) are the strongest predictors of storytelling within each language. We also found bidirectional cross-language associations, with L1 macrostructure predicting L2 macrostructure and vice versa, even after controlling for the effects of age, L1 microstructure, and L2 microstructure. These cross-language associations indicate that storytelling may tap into underlying domain-general cognitive mechanisms (e.g., episodic memory and statistical learning). Originality: Few studies have accounted for microstructure and age effects when investigating cross-language transfer of narrative macrostructure in both L1 and L2. This study investigates cross-language transfer of macrostructure (MAIN GAO) while controlling for age and L1 and L2 microstructure (NDW and MLU), which resulted in bidirectional cross-language associations between L1 and L2 macrostructure. Implications: Robust vocabulary skills in the L1 and L2 can support narrative development within each language. Bidirectional cross-language associations in macrostructure suggest that storytelling reflects underlying cognitive mechanisms that are not language-specific.

Authors

Institutions

Publication Details

Journal
International Journal of Bilingualism
Published
2026-03-22
DOI
https://doi.org/10.1177/13670069261423482
Primary Topic
Language Development and Disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bilingual narrative development: Analyzing sentences and stories within and across languages

Giang Pham, Kerry Danahy Ebert, Michelle N. Ramos, Tatiana I. Ramos Gallardo
International Journal of Bilingualism
Language Development and Disorders
article

Bilingual narrative development: Analyzing sentences and stories within and across languages

Giang Pham, Kerry Danahy Ebert, Michelle N. Ramos, Tatiana I. Ramos Gallardo
article en

Abstract

Aims and objectives: Narrative samples provide an ecologically valid measurement of bilingual children’s skills at the sentence (microstructure) and story levels (macrostructure). Cross-language transfer of narrative macrostructure would indicate that children can leverage their storytelling skills in one language to support storytelling in the other. A rigorous test of cross-language transfer needs to control for age and within-language microstructure skills. Methodology: We analyzed Spanish and English narrative retells produced by 109 typically developing bilingual participants, aged 5–7 years, using the Multilingual Assessment Instrument for Narratives. Microstructure measures included the number of different words (NDW) and the mean length of utterance in words (MLUw). Macrostructure was measured using the MAIN’s goal–attempt–outcome (GAO) complexity rating. Data and analysis: To examine associations between L1 and L2 macrostructure, analyses included bivariate correlations and two hierarchical linear regressions predicting L1 and L2 macrostructure, respectively, with cross-language macrostructure, age, and microstructure measures as predictors. Findings/conclusion: As anticipated, within-language microstructure contributed to macrostructure, suggesting that microstructure skills like vocabulary (e.g., NDW) are the strongest predictors of storytelling within each language. We also found bidirectional cross-language associations, with L1 macrostructure predicting L2 macrostructure and vice versa, even after controlling for the effects of age, L1 microstructure, and L2 microstructure. These cross-language associations indicate that storytelling may tap into underlying domain-general cognitive mechanisms (e.g., episodic memory and statistical learning). Originality: Few studies have accounted for microstructure and age effects when investigating cross-language transfer of narrative macrostructure in both L1 and L2. This study investigates cross-language transfer of macrostructure (MAIN GAO) while controlling for age and L1 and L2 microstructure (NDW and MLU), which resulted in bidirectional cross-language associations between L1 and L2 macrostructure. Implications: Robust vocabulary skills in the L1 and L2 can support narrative development within each language. Bidirectional cross-language associations in macrostructure suggest that storytelling reflects underlying cognitive mechanisms that are not language-specific.

International Journal of Bilingualism
University of Minnesota (US), San Diego State University (US), University of California San Diego (US)
Quality Education
Openalex Percentile: Top 14%
Language Development and Disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.