Purpose: Over-identification of Navajo Head Start children into special education on the Navajo Reservation has come to the attention of Tribal leaders, Educational leaders, and parents due to the use of invalid assessment measures. Dynamic assessment (DA) of narratives may be a tool for distinguishing language differences from language disorders. The purpose of this study is to determine whether the Predictive Early Assessment of Reading and Language (PEARL), a dynamic assessment of narratives, accurately classifies Navajo Head Start students with typically developing (TD) language or with language impairment (LI), and to examine which measures best predict children’s overall performances on the PEARL.

Method: Ninety, 4- and 5-year-old Navajo preschoolers with LI and with TD language were selected. Children completed the PEARL, which measured both language comprehension and production using pretest and posttest scores, and a modifiability scale. In addition, children completed the Clinical Evaluation of Language Fundamental, Preschool, Second Edition (CELF – Preschool 2) and language samples. A Navajo Speech Language Pathologist confirmed the diagnosis of the participants. Research assistants pretested, briefly taught the principles of narrative structure (story grammar, language complexity and episode) and evaluated response to learning using an index of modifiability.

Results: Results of discriminant analysis indicated that PEARL pretest differentiated both ability groups with 89% accuracy. In addition, posttest scores discriminated with 89% accuracy and modifiability scores with 100% accuracy. Further, the subtest story grammar was the best predictor at pretest and posttest, although modifiability scores were better predictors of both ability groups.

Conclusion: Findings indicate that the PEARL is a promising assessment for accurately differentiating Navajo preschool children with LI from Navajo preschool children with TD language. The PEARL’s recommended pretest cut score over-identified Navajo children with TD language; therefore, a new recommended cut score was determined.