Title: Using Nvivo for Data Analysis in Qualitative Research
Abstract:Qualitative data is characterized by its subjectivity, richness, and comprehensive text-based information. Analyzing qualitative data is often a muddled, vague and time-consuming process. Qualitative ...Qualitative data is characterized by its subjectivity, richness, and comprehensive text-based information. Analyzing qualitative data is often a muddled, vague and time-consuming process. Qualitative data analysis is, the pursuing of the relationship between categories and themes of data seeking to increase the understanding of the phenomenon. Traditionally, researchers utilized colored pens to sort and then cut and categorized these data. The innovations in software technology designed for qualitative data analysis significantly diminish complexity and simplify the difficult task, and consequently make the procedure relatively bearable. NVivo, the qualitative data analysis software developed to manage the 'coding' procedures is considered the best in this regards. This article is devoted to demonstrate the methods in which NVivo can be employed in qualitative data analysis. Qualitative research has become widely accepted across a wide range of education science, including administrative, curriculum, and psychology research. This wide acceptance of qualitative research in education is attributed to large extent to the advantage of this type of research. Unlike the quantitative approach, qualitative inquiry is a method of research that describes phenomena based on the point of view of the informants, discovers multiple realities and develops holistic understanding of the phenomena within a particular context (1). It has been acknowledged that properly employing the qualitative data gleaned from face to face interviews, field observation and document analysis can lead the researcher to gain a deeper understanding of the problem than merely analyzing data on a large scale (2).Read More
Publication Year: 2013
Publication Date: 2013-02-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 363
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