Data collection and analysis in qualitative approach

Now let’s talk about document analysis. For documents, it can be accessed at a time convenient to the researcher and it is an unobtrusive source of information. It is often compiled and often transcribed already, so you don’t need to spend a lot of time doing the transcription. But some of the information may be protected and they cannot be accessed by the researcher. And sometimes it requires the researcher to search-out the information on how to find places. And sometimes it requires transcribing or optical scanning for computer entry, and that can take a lot of time. And sometimes materials may be incomplete. All the documents may not be authentic or accurate. After all, these documents originally, they are not for the research purpose.

So documents can be all sorts of documents. They can be public or private. For public documents, that can be anything from meeting minutes to newspapers; and private documents can be journals, diaries or letters. And there are more. So the researchers can develop a system to keep record of the documents. Apart from the above three often used approaches of a qualitative data collection, there are many other approaches available. Now here are only some examples, ethnography, grounded theory, case study, narratives research narratives research and so on and so forth.

Ethnography is a strategy of inquiry in which the researcher studies a target or an intact cultural group in a natural setting over a long period of time by collecting primarily observational and interview data. The research process is flexible and typically evolves contextually in response to the lived realities encountered in the field setting. Grounded theory is a strategy of inquiry in which the researcher derives a general and abstract theory of the process, action or interaction grounded in the views of participants. This process involves using multiple stages of data collection and refinement of inter-relationship or category of information.

Two primary characteristics of this design are the constant comparison of data with emerging categories and theoretical sampling of different groups to maximize the similarities and differences of information. Case studies are a strategy of inquiry in which the researcher explores in depth a program, event, activity, process of one or more individuals. Cases are bounded by time and activity, and researchers collect detailed information using a variety of data collection procedures over a sustained period of time. And narrative research is a strategy of inquiry in which the researcher studies the lives of individuals and asks one or more individuals to provide stories about their lives. This Information is then often retold or restored by the researcher into a narrative chronology.

In the end, the narrative combines views from the participant’s life with those of the researchers’ life in a collaborative creative. And there are many other types of data collecting approaches.

We have so far discussed the approaches for collecting qualitative data. The next question is how to analyze this data. This figure captures the main procedures and steps from bottom to the top. Altogether there are six steps from data preparation to interpreting the meaning of themes and descriptions. Let’s take a look at each step. The first step is to organize and prepare raw data for analysis.

Now this involves transcribing interviews,

optical scanning material, typing up your notes or sorting and arranging the data into different types, depending on the sources of information. The qualitative data can be anything from transcripts to voices, voices, videos and even pictures.

The next step is to read through all the data. First of all, you need to read all of them to obtain a general sense of the information and to reflect on its overall meaning. What general ideas are participants saying? What is the tone of the ideas? What is the impression of the overall depth, credibility and use of the information? Sometimes qualitative researchers write down notes in margins or start recording general thoughts about the data at this stage.

Now here I have an important question to ask: who should do the reading? Well, very importantly, yes, the researcher should be doing the reading, instead of hiring an assistant to process the data, which is different from quantitative studies. In quantitative studies, we often hire systems to run the data for you.

After you have got a holistic feeling about the data, now you can start coding. Coding is the process of organizing the material into chunks or segments of text before bringing meaning to information. It involves taking text data or pictures gathered during data collection, segmenting, sentences or images into categories, and labeling these categories with the term, often a term based on actual language of the participant, we call it NVivo term. I will show you an example in the next session.