Computer analyses of text characteristics are often used by reading teachers, researchers, and policy makers when selecting texts for students. The authors of this article identify components of language, discourse, and cognition that underlie traditional automated metrics of text difficulty and their new Coh-Metrix system. Coh-Metrix analyzes texts on multiple measures of language and discourse that are aligned with multilevel theoretical frameworks of comprehension. The authors discuss five major factors that account for most of the variance in texts across grade levels and text categories: word concreteness, syntactic simplicity, referential cohesion, causal cohesion, and narrativity. They consider the importance of both quantitative and qualitative characteristics of texts for assigning the right text to the right student at the right time.
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