Developmental Language Disorder: Exploring the Diagnostic Accuracy of Parent & Teacher Reports of Bilingual Children’s Language Proficiency (Poster 17)

• In Event: AERA Poster Session Friday 3:45pm
  In Invited Poster Session: 2026 AERA Undergraduate Fellows Research Poster Fair

Abstract

The goal of this study was to examine the diagnostic accuracy and criterion validity of the Inventory to Assess Language Knowledge (ITALK; Peña et al., 2018) parent and teacher questionnaire using speech-language pathologist (SLP) diagnosis of developmental language disorder (DLD) and multiple measures of children’s language skills, in alignment with the current best practice for diagnosing DLD- the converging evidence framework (Castilla-Earls et al., 2020).

Five to seven-year-old kindergartners (N = 255) in Texas and South Carolina who were either in English-only or dual-language instruction classrooms completed the Expressive One Word Picture Vocabulary Test-4: Spanish Bilingual Edition (EOWPVT-4:SBE; Martin, 2013), Bilingual English Spanish Assessment (BESA; Peña et al., 2018) sentence repetition subtests, and English narrative story retells using Frog Where Are You? (Mayer, 1994). Parents and teachers completed the ITALK. DLD status was agreed upon by three bilingual SLPs according to the Bilingual Multidimensional Ability Scale (B-MAS; Wang et al., 2025).

Receiver Operating Characteristic (ROC) curves were used to examine the diagnostic accuracy of parent and teacher reports using the ITALK questionnaire. Using a combination of teacher English and Spanish reports yielded the best diagnostic accuracy (AUC = .86; p<.001; sensitivity = .86; specificity = .74; PPV = 30%; NPV = 98%). Linear regression models controlling for background factors will be run to examine the validity of parent/teacher reports in relation to children’s English and Spanish expressive vocabulary and morphosyntax. Future
studies will examine the diagnostic accuracy of parent and teacher reports in conjunction with direct measures of children’s language skills.

Author

• Rachel Aurora Williams, Texas A&M University