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Cognitive Discourse Analysis: accessing cognitive representations and processes through language data*

Published online by Cambridge University Press:  14 July 2014

THORA TENBRINK
THORA TENBRINK*
Affiliation:
School of Linguistics and English Language, Bangor University, Wales, UK
*
†Address for correspondence: Thora Tenbrink, School of Linguistics & English Language, Room 306 Linguistics, Bangor University, 39 College Road, Bangor, Gwynedd, LL57 2DG, UK. tel: +44 1248 382263; fax: +44 1248 383267; e-mail: [email protected]
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Abstract

This paper offers the first general introduction to CODA (Cognitive Discourse Analysis), a methodology for analyzing verbal protocols and other types of unconstrained language use, as a resource for researchers interested in mental representations and high-level cognitive processes. CODA can be used to investigate verbalizations of perceived scenes and events, spatio-temporal concepts, complex cognitive processes such as problem-solving and cognitive strategies and heuristics, and other concepts that are accessible for verbalization. CODA builds on and extends relevant established methodologies such as cognitive linguistic perspectives, verbal protocol analysis in cognitive psychology and interdisciplinary content analysis, linguistic discourse analysis, and psycholinguistic experimentation.

Keywords

applied cognitive linguisticsverbalization of thoughtconceptualizationproblem solvingdiscourse analysis
Type
Research Article
Information
Language and Cognition , Volume 7 , Issue 1 , March 2015 , pp. 98 - 137
Copyright
Copyright © UK Cognitive Linguistics Association 2014 

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Footnotes

*

I feel privileged for the many opportunities of collaborating with diverse experts across disciplines. My sincere thanks go to the numerous project partners and collaborators in projects and publications mentioned throughout this paper, especially to Holly Taylor for intense collaboration over the past years, and to Vyv Evans for support and inspiring discussion. I am also grateful for diverse comments from many people on earlier versions of this paper, most prominently Michel Denis, Vivien Mast, Dan Montello, Holly Taylor, and Matthew Walsh.

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