Methodology – Overview at qualitative and quantitative research methods pdf. Qualitative Data Analysis, Visit us now!
Although one important feature in ATLAS. Should it be an inductive approach, a deductive approach, or a mixture of both? According to the academic literature, it should be your research question that is guiding this decision. In theory this is and should be so. In practice, choices are often more pragmatic and not everyone is educated in the application of the whole range of methodologies that are out there. Furthermore, not everyone who has the need for analyzing qualitative data is conducting an academic research project that requires more thorough thinking regarding knowledge generation.
A simple analysis of themes and quick access to the data by themes is all that is needed. Given this definition, positivism, symbolic interactionism, phenomenology, hermeneutics, interpretivismor critical theory, are theoretical perspectives. Analysis methods derived from these various frameworks are statistical procedures, theme identification, constant comparison, document analysis, content analysis, or cognitive mapping. GT may also be classified as method, if understood and used as a series of procedures. An analysis of embodied lived experience before empirical data are collected via self-inspection and reflection of own experience. It can capture whatever is salient, the essence of what is in the section or it can be an evocative attribute.
Coding has become a popular method with the spread of Grounded Theory methodology. It is however also used as a method to structure and organize data outside the Grounded Theory framework. What can be derived from the above is that they are many different methods to analyze qualitative data and coding is only one of them. This is related to the variousphilosophical traditions and methodological frameworksbehind. The analysis of embodied lived experience for instance is rooted in phenomenology and phenomenologists forego coding of data all together. Researchers following the interpretivist paradigm where the above listed sequential analyses techniques belong to even perceive coding as an abhorrent incompatible act for data analysis.
And for them CAQDAS packages like ATLAS. What we will however see later, researchers from these traditions still use ATLAS. It helps them to manage, sort through and organize their data corpus. If you decide that coding is an appropriate method to approach the analysis of your data, there is still a lot to learn.
If you never cooked a meal before, being provided with all the pots and pans necessary and the ingredients like meat, vegetable, eggs, cheese, spices etc. Embarking on your first journey of analyzing data with the support of CAQDAS is very similar. Technically speaking, coding means to attach a label to a selected data segment. This is something you learn very quickly like operating a stove. But when is a code just a descriptive label, a category, a sub code, a dimension or a theoretical code? Software is not able to tell you or makes such decisions for you. The process of developing a good code system is already more than coding in the technical sense of just attaching a label to a data segment.
Furthermore, having coded the data is not the end of the analysis process. After coding, the data is prepared for further analysisand exploration. Frequently used tools are the code-cooccurence explorer and the codes-PD table for the purpose of cross-case comparisons. Results can be saved in various forms as a basis for new queries, for instance supporting researchers in identifying types and typologies in the data.
Thus, analysis is more than coding and still largely dependent on the person sitting in front of the computer using thesoftware tool. Let me end this section with a quote from the ATLAS. When Iasked Anselm Strauss back in 1996 to contribute a foreword to the manual of the first version of ATLAS. I was extremely happy heagreed.
In the next section an overview of various analysis approaches is provided. Your will find pointers whether CAQDAS is a useful choice and where researchers have used it for data organization and management only. References to studies that employed ATLAS. Action research consists of a family of research methodologies.