Writing Planning Page: Expository Sample - SlideShare

In one of the few studies with genre and modality comparisons, several sentence measures distinguished children with language learning disabilities (LLD, mean age 11;6) from age peers (). Children gave both oral and written summaries of two educational videos, one that told a story about a young Greek boy (narrative), and another that described plant and animal adaptations and interdependencies in the desert (informational). Summing across genre and modality, grammatical complexity as measured by average sentence length was significantly lower for children with LLD, but did not differ significantly from language-matched peers (who were on average 2.5 years younger). Instances of grammatical error distinguished children with LLD from language peers, however. In a more fine-grained analysis of the same data, reported that children with LLD had significantly lower rates of relative and other postmodifying clauses, object complement clauses, and coordinated clauses. A second analysis () revealed significantly less subordination depth (i.e., using more than one level of subordination). For all children, genre affected frequency of subordinate clause type, such that adverbials and relative clauses occurred at significantly higher rates in expository summaries. Scott and Lane also calculated sensitivity rates—the ability of sentence complexity measures to accurately identify LLD participants, and they did this for each of the four types of language. Important for our topic here, written expository text was the most sensitive context for identifying LLD. A recent finding () provides additional evidence of the sensitivity of informational text for identifying individuals with LI. Nippold and colleagues examined both conversational and expository (describing a favorite game) oral discourse in a large group of adolescents (average age of 13) who were participants in a longitudinal study of language. As kindergarteners, they had been identified as either language impaired (specific or nonspecific) or as typical language participants. Whereas sentence complexity measures failed to distinguish the groups in conversational samples, significant differences were found in the expository samples.

Expository Format Sample

Once a sample is collected, there are a number of quantitative and qualitative analyses that can help establish levels of performance and pinpoint particular areas of need. Quantitatively, it is possible to summarize the overall length and complexity of sentences used in a sample with measures such as Mean Length T-Unit (MLTU) and a clause density metric. MLTU is calculated by dividing the total number of words in a sample by the total number of T-units (defined as a main clause and any subordinate clauses that are attached to it (). For example, the expository sample in has 27 T-units, numbered consecutively. The total number of words in the sample is 335, and thus MLTU = 335/27 = 12.41. MLTU is sensitive to variables such as amount of subordination and noun phrase expansion; however, MLTU does not indicate the relative proportions of features contributing to length ().

Expository Sample Essay #4 (STAAR Test Prep)

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