Language and Discourse Analysis with Coh-Metrix: Applications from Educational Material to Learning Environments at Scale

Authors

  • Nia M. Dowell University of Memphis & Institute for Intelligent Systems
  • Arthur C. Graesser University of Memphis & Institute for Intelligent Systems
  • Zhiqiang Cai University of Memphis & Institute for Intelligent Systems

DOI:

https://doi.org/10.18608/jla.2016.33.5

Abstract

The goal of this article is to preserve and distribute the information presented at the LASI (2014) workshop on Coh-Metrix, a theoretically grounded, computational linguistics facility that analyzes texts on multiple levels of language and discourse. The workshop focused on the utility of Coh-Metrix in discourse theory and educational practice. We discuss some of the motivating factors that led to the development of Coh-Metrix, situated within the context of multilevel theoretical frameworks of discourse comprehension and learning. A review of published studies will highlight the applications of Coh-Metrix, ranging from the scaling and selection of educational material to learning environments at scale. The examples illustrate the relationship between discourse and cognitive, affective, and social processes. We walk through the pedagogical guidelines that should be followed when analyzing texts using Coh-Metrix. Finally, we conclude the paper with a general discussion of the future directions for Coh-Metrix including methodological and practical implications for the learning analytics (LA) and educational data mining (EDM) community.

Author Biographies

Nia M. Dowell, University of Memphis & Institute for Intelligent Systems

Department of Psychology

Arthur C. Graesser, University of Memphis & Institute for Intelligent Systems

Department of Psychology

Zhiqiang Cai, University of Memphis & Institute for Intelligent Systems

Institute for Intelligent Systems

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Published

2016-12-19

How to Cite

Dowell, N. M., Graesser, A. C., & Cai, Z. (2016). Language and Discourse Analysis with Coh-Metrix: Applications from Educational Material to Learning Environments at Scale. Journal of Learning Analytics, 3(3), 72-95. https://doi.org/10.18608/jla.2016.33.5

Issue

Vol. 3 No. 3 (2016): Learning Analytics Tutorials

Section

Special section: Tutorials in learning analytics (LASI and LAK 2014)

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