"Identifying Developmental Language Disorder in School Age Bilinguals: Semantics, Grammar, and Narratives"

Professor Elizabeth Peña (right) is lead author of an article in Language Assessment Quarterly identifying developmental language disorder in school age bilinguals.

The title of the article is “Identifying Developmental Language Disorder in School Age Bilinguals: Semantics, Grammar, and Narratives.”
 
Co-authors are Lisa M. Bedore (Temple University), Mirza J. Lugo (University of Texas at Austin), and Nahar Albudoor (University of Texas at Austin).
 
Peña is a certified Speech-Language Pathologist and Fellow of the American Speech Language Hearing Association. In the UCI School of Education, she serves as Associate Dean of Faculty Development and Diversity and directs the Human Abilities in Bilingual Language Acquisition (HABLA) Lab. Peña's research interests include bilingualism, language impairment, and test development and treatment.

​Abstract

Children with Developmental language disorder (DLD) have particular difficulty learning language despite otherwise general normal development. When school age bilingual children struggle with language, a common question is if the difficulties they present reflect lack of ability or lack of language experience. To address the question of identification of DLD in the context of bilingualism, we explore the diagnostic accuracy of measures administered in two languages. The Bilingual English Spanish Assessment Middle Extension (BESA-ME) assesses semantics and morphosyntax and the Test of Narrative Language (TNL) assesses comprehension and production of narratives. These measures were administered to 112 second graders (19 with DLD) and 64 fourth graders (7 with DLD). We explored the classification accuracy of each of these measures alone and in combination using receiver operator characteristic (ROC) curve analysis. The ROC curve illustrates diagnostic classification of a measure at various cutpoints. We compared the extent to which measures in English, Spanish, or best language account for area under the (ROC) curve. Discriminant function analysis using the best indicator (Spanish, English, best language) from each type of measure (semantics, morphosyntax, narrative) in combination demonstrate classification accuracy above 80%. Morphosyntax in the best language was the strongest predictor of DLD for second grade children. In fourth grade, the three measures contributed more equally in predicting DLD.