First and foremost Humanists describe what is and only in a second step answer why it is that way. Qualitative Data Analysis and many similar research techniques often follow a simple scheme: creating categories/variables/topics, applying them to text and then analysing meaningful groups by qualitative and quantitative comparison. By this, we easily fall into the “Positivist Pitfall” of only describing, instead of explaining our data. However, we must strive to create meaningful interpretations that can be disputed or even be proven wrong.
On the surface MAXQDA and ATLAS.ti seem almost identical. Yet when we look under the hood, we see strong differences: one follows the logic of a relational data base and sorts everything into neat categories and the other operates like a graph data base that links different entities to form a large network. The implicit potentials and constrains of each (and any) software commonly drive our research because we too often follow the road that we already know best.
If we want to quantify the results of our coding in QDA, we have to think about two aspects first: scope and quantity. The scope forces us to consider what length our text segments should have (words, sentence, paragraph), whereas the quantity indicates what we are allowed to do with these segments later in analysis (numerical, boolean, non-numerical analysis). To quantify codes properly, this must be taken into consideration long before we complete our coding. Continue reading Scope & Quantity: Defining Codes for Proper Quantification
No, it’s not. Granted, QDA-software is far from methodologically neutral and strongly influences the way we design our research. However, it is not a method in itself and we always need some external “building plan”(a method) to guide us. Continue reading Is (MAX)QDA actually a method?