Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, grounded theory methodology, etc.

Definition

CAQDAS is used in psychology, marketing research, ethnography, public health and other social sciences. The CAQDAS networking project lists the following tools a CAQDAS program should have:

Comparison of CAQDAS software

Project Exchange Format

In 2019, the Rotterdam Exchange Format Initiative (REFI) launched a new open exchange standard for qualitative data called QDA-XML, however, the Computer Assisted Qualitative Data Analysis (CAQDAS) Network Project had been formally established in 1994. The aim is to allow users to bring coded qualitative data from one software package to another. Support was initially adopted by Atlas.ti, QDA Miner, Quirkos and Transana, and has since been implemented into Dedoose, MAXQDA, NVivo and more. Although this was not the first standard to be proposed, it was the first to be implemented by more than one software package, and came as the result of a collaboration between vendors and community representatives from the research community. Previously there was very little capability to bring data in from other software packages.

Training

The CAQDAS Network Project hosts events on the use of CAQDAS packages for qualitative and mixed-methods analysis. They include:

Pros and cons

Such software helps to organize, manage and analyse information. The advantages of using this software include saving time, managing huge amounts of qualitative data, having increased flexibility, having improved validity and auditability of qualitative research, and being freed from manual and clerical tasks. Concerns include increasingly deterministic and rigid processes, privileging of coding, and retrieval methods; reification of data, increased pressure on researchers to focus on volume and breadth rather than on depth and meaning, time and energy spent learning to use computer packages, increased commercialism, and distraction from the real work of analysis.

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