Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-45l2p Total loading time: 0 Render date: 2024-04-26T16:53:09.487Z Has data issue: false hasContentIssue false

6 - Using Coh-Metrix Measures

Studies of Cohesion in Text and Writing

Published online by Cambridge University Press:  05 June 2014

Danielle S. McNamara
Affiliation:
Institute for Intelligent Systems, The University of Memphis
Arthur C. Graesser
Affiliation:
Institute for Intelligent Systems, The University of Memphis
Philip M. McCarthy
Affiliation:
Institute for Intelligent Systems, The University of Memphis
Zhiqiang Cai
Affiliation:
Institute for Intelligent Systems, The University of Memphis
Get access

Summary

We discussed in Chapter 2 the importance of cohesion and coherence to comprehension and how these findings were the main impetus for developing Coh-Metrix. Our primary goal in the Coh-Metrix project has been to develop, explore, and validate measures of text cohesion. Throughout the Coh-Metrix Project we have developed and implemented many approaches to assessing cohesion as well as other levels of language and discourse. The magnifying glass has primarily been on cohesion, so we have developed literally hundreds of cohesion indices that vary in generality (see Chapter 4 for the distinction between measure, index, bank, and variable). Some indices have targeted one general construct, such as referential cohesion, whereas others have drilled to a more specific level, such as temporal and verb cohesion. A significant portion of our efforts has gone toward rooting among the indices to choose the best ones and validating new ones. When there are many indices to measure a similar construct, it has been necessary to identify which ones rise to the top across the various studies and within studies. The indices need to be validated so that we have some assurance that they assess what we think they are assessing and that they are theoretically compatible with patterns of data corresponding to types of texts or human performance. For example, some studies show how particular indices account for differences between texts that fit predictions based on theory or well-accepted empirical findings. Alternatively, some indices are validated by patterns of data in psychological experiments using behavioral tasks. We have conducted many such validation studies. This chapter describes some of the studies we have conducted, particularly as they relate to referential, semantic, and situation model cohesion. The chapter begins by examining measures of cohesion in the context of empirical text comprehension studies and differences between types of text. We subsequently describe our work examining the role of cohesion in writing.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Using Coh-Metrix Measures
  • Danielle S. McNamara, Institute for Intelligent Systems, The University of Memphis, Arthur C. Graesser, Institute for Intelligent Systems, The University of Memphis, Philip M. McCarthy, Institute for Intelligent Systems, The University of Memphis, Zhiqiang Cai, Institute for Intelligent Systems, The University of Memphis
  • Book: Automated Evaluation of Text and Discourse with Coh-Metrix
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9780511894664.008
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Using Coh-Metrix Measures
  • Danielle S. McNamara, Institute for Intelligent Systems, The University of Memphis, Arthur C. Graesser, Institute for Intelligent Systems, The University of Memphis, Philip M. McCarthy, Institute for Intelligent Systems, The University of Memphis, Zhiqiang Cai, Institute for Intelligent Systems, The University of Memphis
  • Book: Automated Evaluation of Text and Discourse with Coh-Metrix
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9780511894664.008
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Using Coh-Metrix Measures
  • Danielle S. McNamara, Institute for Intelligent Systems, The University of Memphis, Arthur C. Graesser, Institute for Intelligent Systems, The University of Memphis, Philip M. McCarthy, Institute for Intelligent Systems, The University of Memphis, Zhiqiang Cai, Institute for Intelligent Systems, The University of Memphis
  • Book: Automated Evaluation of Text and Discourse with Coh-Metrix
  • Online publication: 05 June 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9780511894664.008
Available formats
×