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2018 Abstracts

Grammatical Accuracy of Narratives Produced by Typically Developing Children Ages 4-7

Sarai Holbrook; Sierra Browning; Amanda Miller; Cortney Hoffman; Natalie Johnson; Sierra Southwick, Utah State University

Guo & Schneider (2016) explored different approaches to identifying grammatical impairments in 128 children developing typically (TL) and those with language impairments (LI) between the ages of 6 and 8. Their participants were 61 six-year-olds (50 TL, 11 LI), and 67 eight-year-olds (50 TL, 17 LI). The measures that they explored included: calculating the finite verb morphology composite (FVMC), the number of errors per C-unit (Errors/CU), and the percent of grammatical C-units (PGCUs) in narrative samples. Each outcome measure was evaluated for its sensitivity and specificity. They found that all three outcome measures provided acceptable diagnostic accuracy when applied to six-year-olds, but PCGUs were found to be the most accurate tool with eight-year-olds. The purpose of the current study was to analyze the narrative samples of 260 typically developing children ages 4-7 to determine typical scores for the previously listed grammatical measures at each age level. This knowledge may provide more information on the performance of typical children and how to accurately identify students with LI. This study extends the literature by testing whether the findings remain the same with addition data from children aged 6-7 and whether the findings extend to children aged 4 and 5 years. The participants in this study included 42 four-year-olds, 57 five-year-olds, 68 six-year-olds and 93 seven-year-olds. The participants were selected as part of the normative sample for the Test of Narrative Language-2. For the study, the children were asked to produce stories in three varying contexts. These contexts consisted of: a story retell after a model story, sequenced pictures were then provided for another story retell after a model, and lastly children were asked to produce a story based on a picture after a model. These stories were transcribed using Systematic Analysis of Language Transcripts (SALT). The transcriptions were double coded for grammaticality by two separate research assistants. Reliability was calculated by a graduate research assistant. The utterances were designated as grammatical or ungrammatical. Ungrammatical utterances were coded for the type of grammatical error present. The same three grammaticality outcome measures used in Guo & Schneider (2016) were used in this study. Data analysis will include examination of each outcome measure by age. Conclusions and clinical implications will be discussed.