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

Abstract

Several studies have demonstrated that dynamic assessment can be a less biased, valid approach for the identification of language disorder among diverse school-age children. However, all prior studies have included a relatively small number of participants, which is generally not adequate for psychometric research. This is the first large-scale study to (a) examine whether a dynamic assessment of narrative language yields indifferent outcomes regardless of several demographic variables including age, race/ethnicity, multilingualism, or gender; (b) examine the sensitivity and specificity of the dynamic assessment of language among a large sample of students with and without language disorder; and (c) identify specific cut-points by grade to provide clinically useful data. Participants included 634 diverse first- through fifth-grade students with and without language learning disorder. Students were confirmed as having a language disorder using a triangulation technique involving several sources of data. A dynamic assessment of narrative language, which took approximately 10 min, was administered to all students. Results indicated that the dynamic assessment had excellent (> 90%) sensitivity and specificity and that modifiability scores were not meaningfully different across any of the demographic variables. The dynamic assessment of narrative language accurately identified language disorder across all student demographic groups. These findings suggest that dynamic assessment may provide less biased classification than traditional, static forms of assessment.