Coh-Metrix
A computational text-analysis tool developed by Arthur Graesser, Danielle McNamara, and colleagues at the University of Memphis (now hosted at Arizona State University). Coh-Metrix produces over 200 measures of cohesion, language, and readability, grounded in multilevel theories of comprehension that distinguish surface form, textbase, and situation model. Where classical readability formulas like Flesch-Kincaid Grade Level capture only sentence length and word length, Coh-Metrix adds discourse-level cohesion, lexical concreteness, and rhetorical structure.
The five Easability dimensions
The Text Easability Assessor (Coh-Metrix-TEA) funnels the 200-plus measures into five factors that vary systematically across genre and grade level (Graesser, McNamara & Kulikowich 2011):
- Narrativity: the degree to which a text resembles a story. Narratives draw on everyday oral language, are easier to comprehend, and load on familiar story-grammar structures.
- Syntactic simplicity: short sentences, low embedding, familiar word order. Higher values mean lower processing load.
- Word concreteness: concreteness ratings averaged across the text. Concrete words evoke mental images and ground abstract argument.
- Referential cohesion: overlap of words and ideas across sentences. High-cohesion texts thread the same referents through, easing inference.
- Deep cohesion: density of causal, intentional, and logical connectives. Marks whether the text scaffolds the situation model explicitly.
A text scoring high on all five is comprehensible to a wider readership; a text low on cohesion but high on syntactic simplicity may still confuse readers because the sentences-to-situation-model bridge is left implicit.
Use in test development
Coh-Metrix-TEA is the closest thing to an off-the-shelf passage profiler usable in item-bank curation. Three uses recur in the literature: stratifying passages across CEFR-aligned bands using more than just sentence/word length; flagging passages with anomalous cohesion that may produce construct-irrelevant difficulty; and comparing AI-generated passages to a human reference set to detect stylistic drift before bank entry.
The tool is freely available for research; the production-grade variant is licensed.
Key References
- Graesser, A. C., McNamara, D. S. & Kulikowich, J. M. (2011). Coh-Metrix: Providing multilevel analyses of text characteristics. Educational Researcher, 40(5), 223–234.
- McNamara, D. S., Graesser, A. C., McCarthy, P. M. & Cai, Z. (2014). Automated Evaluation of Text and Discourse with Coh-Metrix. Cambridge University Press.
- Graesser, A. C., McNamara, D. S., Louwerse, M. M. & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36(2), 193–202.
See Also
- Readability: the broader construct
- Flesch-Kincaid Grade Level: a surface-only counterpart
- Cohesion: the textual property the tool foregrounds
- Reading Comprehension Test Design: where Coh-Metrix scores feed passage selection