Analyzing Texts using Coh-Metrix
Nia Dowell, Zhiqiang Cai & Art Graesser, Institute for Intelligent Systems, University of Memphis
The workshop will focus on the utility of Coh-Metrix in discourse theory and educational practice. We will begin with an introduction to the Coh-Metrix and Test Easability Assessor (TEA) tools, including a detailed description of the indices in the context of multilevel theoretical frameworks of discourse comprehension and learning. A review of published studies will help illustrate the relationship between discourse and learning. We will then walk participants through a series of practical exercises that will give hands-on experience with cleaning, preparing, and analyzing texts using Coh-Metrix, conducting statistical analyses with Coh-Metrix data, and data interpretation.
Intended learning outcomes:
Participants will become familiar with the structure of the Coh-Metrix and Test Easability Assessor (TEA) tools and their applications, with particular focus on the analysis of educational data. Participants will learn about the various indices available in each tool, and how to interpret their significance.
- Please bring your laptop and have the Firefox browser installed
- Please visit the Coh-Metrix (http://cohmetrix.com) and Test Easability Assessor (TEA) (http://tea.cohmetrix.com) sites and create a user account
- Please set up a dropbox account (https://www.dropbox.com/home) for easy access to workshop materials
- Having your preferred data analysis package (spss, R, stata, matlab etc.) installed and available is ideal, but not mandatory
- Participants are encouraged to bring sample texts from their own projects
- Other helpful material
- Notepad ++ can be downloaded at (http://notepad-plus-plus.org)
- Text crawler can be downloaded at (http://textcrawler.en.softonic.com)
You may wish to read the following materials in preparation (available on request):
Graesser, A.C., Foltz, P., Forsyth, C., & Germany, M. (in press). Discourse and collaborative problem-solving. In Beno and Funke (Eds.) The Nature of Problem Solving. OECD series.
Graesser, A. C., McNamara, D. S., & Kulikowich, J. M. (2011). Coh-Metrix: Providing Multilevel Analyses of Text Characteristics. Educational Researcher, 40(5), 223–234.
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
Graesser, A. C., & McNamara, D. S. (2011). Computational Analyses of Multilevel Discourse Comprehension. Topics in Cognitive Science, 3(2), 371–398.
New Coh-Metrix Book:
McNamara, D. S., Graesser, A. C., McCarthy, P. M., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. Cambridge, M.A.: Cambridge University Press.
Nia Dowell is a cognitive psychology doctoral student in the Institute for Intelligent Systems at the University of Memphis. Nia is currently pursuing her PhD under the direction and mentorship of Dr. Arthur Graesser. Her primary interests are in cognitive psychology, discourse processing and affective sciences. In general, her research focuses are on using language and discourse to uncover the dynamics of socially significant, cognitive, and affective processes. She is currently applying computational techniques to model discourse and social dynamics in authoritarian regimes, as well as in adaptive intelligent tutoring systems and collaborative learning environments.
Zhiqiang Cai is a research assistant professor in the Institute for Intelligent Systems, the University of Memphis. He has a M Sc. degree in computational mathematics received in 1985 from Huazhong University of Science and Technology, P. R. China. He was an associate professor at Huazhong University of Science and Technology from 1994 through 2001, a visiting associate professor at Sudan University of Science and Technology from 1996 through 2000, a visiting associate professor at the University of Paris VI in 1995. His is the chief software designer and developer of QUAID, Coh-Metrix, ACE (AutoTutor Conversation Engine) and ASAT (AutoTutor Script Authoring Tool). His current research interests are in algorithm design and software development for tutoring systems and natural language processing.
Dr. Art Graesser is a professor in the Department of Psychology and the Institute of Intelligent Systems at the University of Memphis and is a Senior Research Fellow in the Department of Education at the University of Oxford. Dr. Graesser’s primary research interests are in cognitive science, discourse processing, and the learning sciences. Dr. Graesser served as editor of the journal Discourse Processes (1996–2005) and Journal of Educational Psychology (2009-2014) and as president of the Empirical Studies of Literature, Art, and Media (1989-1992), the Society for Text and Discourse (2007-2010), International Society for Artificial Intelligence in Education (2007-2009), and the FABBS Foundation (2012-13). He has published over 500 articles in journals, books, and conference proceedings.