Abstract
Background
Children who speak African American English (AAE) may have an elevated likelihood
of being diagnosed with language disorders. Traditional language sample analysis (LSA)
metrics, such as Developmental Sentence Scoring (DSS), are based on the morphosyntax
of General American English (GAE) and may not accurately reflect the language abilities
of AAE-speaking children. We examined the effectiveness of computerized Black English
Sentence Scoring (BESS) in distinguishing between typically developing (TD) and developmental
language disorder (DLD) in AAE- and GAE-speaking children compared with DSS.
Method
Language samples from 88 children (22 DLD, 66 TD) ages 5;0 to 7;02, comprising 44
AAE-speaking children and 44 GAE-speaking children, were analyzed using Computerized
Language ANalysis (CLAN) DSS and BESS options.
Results
Results of a two-level ANOVA did not show evidence of any effect by dialect and scoring
method. Logistic regression analyses revealed that both DSS and BESS exhibited poor
classification accuracy, suggesting that they are statistically unreliable methods
of DLD identification in children who speak either AAE or GAE.
Discussion
Although BESS is intended to minimize linguistic bias compared with DSS, neither approach
yielded adequate diagnostic accuracy in this study. However, both can provide valuable
information on grammatical features in a child's expressive language to guide intervention.
Keywords
pediatric language - language sample analysis - Developmental Sentence Scoring (DSS)
- Black English Sentence Scoring (BESS) - language variation