Computer-Assisted Qualitative Research: An Overview

Abstract

Computer-assisted qualitative data analysis (CAQDAS)-based qualitative research is both an art and a science. It relies on creativity and disciplined imagination (Weick KE, Acad Manag Rev 14(4):516–531, 1989) plus systematic, accurate, reliable, and iterative approaches. The primary challenge in qualitative research is to transform “hundreds of pages of field notes to a final report” (Miles MB, Huberman AM, Qualitative data analysis: an expanded source book. 2nd ed. Sage, Thousand Oaks, 1994, p. 281) in a rigorous, defendable, and auditable process. Qualitative research is not “a disorganized stumble through a mass of data, full of ‘insightful’ observations of a mainly anecdotal nature” (Silverman D, Interpreting qualitative data: methods for analysing talk, text, and interaction. Sage, London, 1993, p. 43). Rather, it is a disciplined yet creative way to bring the messy, rich and thick data into discernible patterns, concepts, processes or mechanisms. To move from an anecdotal to a systematic approach in doing qualitative research, researchers can utilize the advances in computing technologies in the form of CAQDAS and adopt one of the dominant qualitative approach methodologies (see Chaps. 1 and 3). In this chapter, we describe the rationale for using CAQDAS in qualitative research as a strategy to professionalize and legitimize qualitative research. We also compare RQDA –– the R package for Qualitative Data Analysis –– the CAQDAS we introduce here, with three of the most well-known CAQDAS software (One of the earliest CAQDAS tools was NUDIST (Richards T, & Richards L, Qual Sociol 14(4):307–324, 1991). Other types of CAQDAS software, which are proprietary based (requires license fees), are MAXqda, QDA Miner, Dedoose, and webQDA. Open source (free) CAQDAS software includes Aquad, Coding Analysis Toolkit (CAT), Transana, and WeftQDA, among others) programs, NVivo, ATLAS.ti, and MaxQDA.