TY - JOUR
T1 - Coh-metrix
T2 - Providing multilevel analyses of text characteristics
AU - Graesser, Arthur C.
AU - McNamara, Danielle S.
AU - Kulikowich, Jonna M.
N1 - Funding Information:
This research was supported by the National Science Foundation (Grants BCS 0904909 and DRK-12-0918409 ), the Institute of Education Sciences (Grants R305G020018 and R305A080589 ), and the Gates Foundation (Student Achievement Partners). Any opinions, findings, conclusions, or recommendations expressed here are those of the authors and do not necessarily reflect the views of the funding agencies. We thank Zhiqiang Cai for developing the Coh-Metrix software and Phil McCarthy and Jeremiah Sullins for statistical analyses.
PY - 2011/6
Y1 - 2011/6
N2 - 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.
AB - 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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U2 - 10.3102/0013189X11413260
DO - 10.3102/0013189X11413260
M3 - Article
AN - SCOPUS:79959808773
SN - 0013-189X
VL - 40
SP - 223
EP - 234
JO - Educational Researcher
JF - Educational Researcher
IS - 5
ER -