| Summary: | This study examines the potential for computational tools and human raters to classify paragraphs based on positioning. In this study, a corpus of 182 paragraphs was collected from student, argumentative essays. The paragraphs selected were initial, middle, and final paragraphs and their positioning related to introductory, body, and concluding paragraphs. The paragraphs were analyzed by the computational tool Coh-Metrix on a variety of linguistic features with correlates to textual cohesion and lexical sophistication and then modeled using statistical techniques. The paragraphs were also classified by human raters based on paragraph positioning. The performance of the reported model was well above chance and reported an accuracy of classification that was similar to human judgments of paragraph type (66% accuracy for human versus 65% accuracy for our model). The model's accuracy increased when longer paragraphs that provided more linguistic coverage and paragraphs judged by human raters to be of higher quality were examined. The findings support the notions that paragraph types contain specific linguistic features that allow them to be distinguished from one another. The finding reported in this study should prove beneficial in classroom writing instruction and in automated writing assessment.
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