Today, powerful software for qualitative research helps researchers to create an analytical system of nodes for coding and interpreting the data in terms of interviewee’s thinking and activities.
Today there are multiple software packages (CAQDAS), born initially to analyze both documents and verbal texts, which were later developed to include nearly the whole spectrum of digital data, ranging from musical texts to audiovisuals.
Some of these software programs for qualitative research possess functions that go well beyond manipulating, searching and reporting on coded text. They assist with analytic procedures by providing a variety of facilities to help the analyst examine features and relationships in the texts.
Most notably, the most professional software for qualitative research such as ATLAS.ti also sports facilities that enable the exchange of data and analyzes between researchers working together collaboratively. Software for qualitative research is often referred to as theory or model building software, not because on their own they can build theory, but because they contain various research tools that assist researchers to develop theoretical ideas and test hypotheses.
Such features, present in one form or another in software packages for qualitative research have extended the forms of work supported beyond the lone researcher examining plain text.
Using powerful software for qualitative research, researchers produce not only even new presentations (e.g. in a visual, tree-based form) since they offer a high degree of reflexivity that informs the analysis.
A holistic processing of complexity based on the philosophical concept of comprehension and explanation, enables the reseracher to cope with the large, diverse and often controversial data created in areas such as conflict studies, organizations, innovation studies and sociology.
Typically, the approach enabled by software for qualitative research is multi-stage: After initial coding, data are assessed, rated and organized into a conceptual structure, i.e. mindmaps based on the underlying verbal data and linguistic Gestalt. Furthermore, causal assumptions can be examined in the form of a complex cause-effect graph that facilitates the analysis of controversial issues and fosters comparative analyzes.
However, when selecting software for qualitative research and deciding on the analytic approach a researcher is going to take they should be wary of the common misconceptions that learners have about software for qualitative research: that it will do the analysis for them and that they will learn about qualitative data analysis by learning the software.