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IES Grant

Title: Coh-Metrix: Automated Cohesion and Coherence Scores to Predict Text Readability and Facilitate Comprehension
Center: NCER Year: 2002
Principal Investigator: McNamara, Danielle Awardee: University of Memphis
Program: Literacy      [Program Details]
Award Period: 3 years Award Amount: $1,477,200
Type: Measurement Award Number: R305G020018

Co-Principal Investigators: Graesser, Arthur; Louwerse, Max

Purpose:In the early 2000s, the tools used to determine the readability of texts were severely limited, may not have helped schools or researchers appropriately identify texts that are well-matched to readers, and may have been paradoxically aggravating comprehension difficulties. To address this issue, the research team proposed to develop two automated tools: Coh-Metrix and Coh-GIT. These tools aimed to enable writers, editors, and educators to more accurately estimate the appropriateness of a text for their audience and to pinpoint specific problems with the text. As part of their studies, the researchers used these tools to experimentally examine the effects of text cohesion on reading comprehension with respect to reader aptitudes (such as prior knowledge, reading ability, and motivation) in third- to fifth-grade students and college undergraduates.

Related IES Projects: Center for the Study of Adult Literacy (CSAL): Developing Instructional Approaches Suited to the Cognitive and Motivational Needs for Struggling Adults (R305C120001)


ERIC Citations: Find available citations in ERIC for this award here.

Project Website: and

Select Publications:


McNamara, D.S., Graesser, A.C., McCarthy, P.M., and Cai, Z. (2014). Automated Evaluation of Text and Discourse With Coh-Metrix.Cambridge, MA: Cambridge University Press.

Book chapters

Crossley, S.A. and McNamara, D.S. (2017). Educational Technologies and Literacy Development. Adaptive Educational Technologies for Literacy Instruction. Taylor and Francis eBooks.

Graesser, A., Louwerse, M., McNamara, D., Olney, A., Cai, Z., and Mitchell, H. (2007). Inference Generation and Cohesion in the Construction of Situation Models: Some Connections With Computational Linguistics. In F. Schmalhofer, and C.A. Perfetti (Eds.), Higher Level Language Processes in the Brain: Inference and Comprehension Processes (pp. 289–310). Mahwah, NJ: Erlbaum.

Graesser, A.C., and Petschonek, S. (2005). Automated Systems That Analyze Text and Discourse: QUAID, Coh-Metrix, and Autotutor. In W.R. Lenderking, and D. Revicki (Eds.), Advancing Health Outcomes Research Methods and Clinical Applications (pp. 95–112). Mclean, VA: Degnon Associates.

Graesser, A.C., Hu, X., and McNamara, D.S. (2005). Computerized Learning Environments That Incoporate Research in Discourse Psychology, Cognitive Science, and Computational Linguistics. In A.F. Healy (Ed.), Experimental Cognitive Psychology and Its Applications: Festschrift in Honor of Lyle Bourne, Walter Kintsch, and Thomas Landauer (pp. 183–194). Washington, D.C.: American Psychological Association.

Graesser, A.C., Keshtkar, F., and Li, H. (2014). The Role of Natural Language and Discourse Processing in Advanced Tutoring Systems. In T. Holtgraves (Ed.), The Oxford Handbook of Language and Social Psychology (pp. 491–509). New York: Oxford Handbooks Online.

McNamara, D.S., Cai, Z., and Louwerse, M.M. (2007). Optimizing LSA Measures of Cohesion. In T. Landauer, D.S., McNamara, S. Dennis, and W. Kintsch (Eds.), Handbook of Latent Semantic Analysis (pp. 379–400). Mahwah, NJ: Erlbaum.

Snow, E.L., Jacovina, M.E., Jackson, G.T., and McNamara, D.S. (2017). iSTART-2: A Reading Comprehension and Strategy Instruction Tutor. Adaptive Educational Technologies for Literacy Instruction. Taylor and Francis eBooks.

Journal articles

Best, R.M., Floyd, R.G., and McNamara, D.S. (2008). Differential Competencies Contributing to Children's Comprehension of Narrative and Expository Texts. Reading Psychology, 29(2): 137–164.

Crossley, S.A., McCarthy, P.M., Louwerse, M., and McNamara, D.S. (2007). Linguistic Analysis of Simplified and Authentic Texts. Modern Language Journal, 91(1): 15–30.

Duran, N.D., McCarthy, P.M., Graesser, A.C., and McNamara, D. (2007). Using Temporal Cohesion to Predict Temporal Coherence in Narrative and Expository Texts. Behavior Research Methods, 39(2): 212–223.

Graesser, A.C., and McNamara, D.S. (2011). Computational Analyses of Multilevel Discourse Comprehension. Topics in Cognitive Science, 3(2): 371–398.

Graesser, A.C., Jeon, M., Yan, Y., and Cai, Z. (2007). Discourse Cohesion in Text and Tutorial Dialogue. Information Design Journal, 15(3): 199–213.

Graesser, A.C., McNamara, D.S., Cai, Z., Conley, M., Li, H., and Pennebaker, J. (2014). Coh-Metrix Measures Text Characteristics at Multiple Levels of Language and Discourse. Elementary School Journal, 115(2): 210–229.

Graesser, A.C., McNamara, D.S., Louwerse, M.M., and Cai, Z. (2004). Coh-Metrix: Analysis of Text on Cohesion and Language. Behavioral Research Methods, Instruments and Computers, 36: 193–202.

Hempelmann, C.F., Rus, V., Graesser, A.C., and McNamara, D.S. (2006). Evaluating State-of-the-Art Treebank-Style Parsers for Coh-Metrix and Other Learning Technology Environments. Natural Language Engineering Special Issue: Building Educational Applications Using Natural Language Processing, 12(2): 131–144.

Nye, B.D., Graesser, A.C., and Hu, X. (2014). AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring. International Journal of Artificial Intelligence in Education, 24(4): 427–469.

O'Reilly, T., and McNamara, D.S. (2007). Reversing the Reverse Cohesion Effect: Good Texts can be Better for Strategic, High-Knowledge Readers. Discourse Processes, 43(2): 121–152.


Bruss, M., Albers, M., and McNamara, D.S. (2004). Changes in Scientific Articles Over Two Hundred Years: A Coh-Metrix Analysis. In Proceedings of the 22nd Annual International Conference on Computer Documentation (pp. 104–109). Memphis, TN: ACM Press.

Cai, Z., McNamara, D.S., Louwerse, M., Hu, X., Rowe, M., and Graesser, A.C. (2004). NLS: Non-Latent Similarity Algorithm. In Proceedings of the 26th Annual Meeting of the Cognitive Science Society (pp. 180–185). Mahwah, NJ: Erlbaum.

Dufty, D.F., McNamara, D., Louwerse, M., Cai, Z., and Graesser, A.C. (2004). Automatic Evaluation of Aspects of Document Quality. In Proceedings of the 22nd Annual International Conference on Documentation (pp. 14–16). Memphis,TN: ACM Press.

Hempelmann, C.F., Dufty, D., McCarthy, P.M., Graesser, A.C., Cai, Z., and McNamara, D.S. (2005). Using LSA to Automatically Identify Givenness and Newness of Noun Phrases in Written Discourse. In Proceedings of the 27th Annual Meeting of the Cognitive Science Society (pp. 941–946). Mahwah, NJ: Erlbaum.

Louwerse, M.M., McCarthy, P.M., McNamara, D.S., and Graesser, A.C. (2004). Variation in Language and Cohesion Across Written and Spoken Registers. In Proceedings of the 26th Annual Meeting of the Cognitive Science Society(pp. 843–848). Mahwah, NJ: Erlbaum.

McNamara, D.S., Floyd, R.G., Best, R., and Louwerse, M. (2004). World Knowledge Driving Young Readers' Comprehension Difficulties. In Proceedings of the Sixth International Conference of the Learning Sciences: Embracing Diversity in the Learning Sciences (pp. 326–333). Mahwah, NJ: Erlbaum.

McNamara, D.S., Ozuru, Y., Graesser, A.C., and Louwerse, M. (2006). Validating Coh-Metrix. In Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 573). Mahwah, NJ: Erlbaum.

Ozuru, Y., Dempsey, K., Sayroo, J., and McNamara, D.S. (2005). Effect of Text Cohesion on Comprehension of Biology Texts. In Proceedings of the 27th Annual Meeting of the Cognitive Science Society (pp. 1696–1701). Hillsdale, NJ: Erlbaum.