Accurately Identifying Language Disorder in School-Age Children Using Dynamic Assessment of Narrative Language.

Area of Science:

• Speech-Language Pathology
• Educational Psychology
• Developmental Psychology

Background:

• Dynamic assessment (DA) is a promising, less biased method for identifying language disorders in children.
• Previous studies lacked sufficient sample sizes for robust psychometric validation.
• Large-scale validation is needed to confirm DA's utility across diverse populations.

Purpose of the Study:

• To validate a dynamic assessment of narrative language in a large, diverse student sample.
• To examine DA's invariance across demographic variables (age, race/ethnicity, multilingualism, gender).
• To determine the sensitivity, specificity, and grade-specific cut-points for clinical use.

Main Methods:

• A large-scale study involving 634 diverse first- through fifth-grade students.
• Language disorder diagnosis confirmed via triangulation of multiple data sources.
• Administration of a brief (10-minute) dynamic assessment of narrative language.

Main Results:

• The dynamic assessment demonstrated excellent sensitivity and specificity (>90%).
• Modifiability scores were consistent across all demographic variables.
• The assessment accurately identified language disorders in all student groups.

Conclusions:

• Dynamic assessment of narrative language is a valid and reliable tool for identifying language disorders.
• DA provides unbiased classification across diverse student populations.
• Findings support the use of DA as a less biased alternative to static assessments.