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Coding is Not a Dirty Word: Theory-Driven Data Analysis Using NVivo

Coding is Not a Dirty Word: Theory-Driven Data Analysis Using NVivo
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Author(s): Kakali Bhattacharya (Kansas State University, USA)
Copyright: 2015
Pages: 30
Source title: Enhancing Qualitative and Mixed Methods Research with Technology
Source Author(s)/Editor(s): Shalin Hai-Jew (Hutchinson Community College, USA)
DOI: 10.4018/978-1-4666-6493-7.ch001

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Abstract

Current discourses in qualitative research, especially those situated in postmodernism, represent coding and the technology that assists with coding as reductive, lacking complexity, and detached from theory. In this chapter, the author presents a counter-narrative to this dominant discourse in qualitative research. The author argues that coding is not necessarily devoid of theory, nor does the use of software for data management and analysis automatically render scholarship theoretically lightweight or barren. A lack of deep analytical insight is a consequence not of software but of epistemology. Using examples informed by interpretive and critical approaches, the author demonstrates how NVivo can provide an effective tool for data management and analysis. The author also highlights ideas for critical and deconstructive approaches in qualitative inquiry while using NVivo. By troubling the positivist discourse of coding, the author seeks to create dialogic spaces that integrate theory with technology-driven data management and analysis, while maintaining the depth and rigor of qualitative research.

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