Analysis of qualitative data requires intensive reading of the transcripts, field reports, diaries, journals, and other documents. It is a continuous and to-and-fro process. What changes do you, as a qualitative researcher, face during data analysis and how do you overcome those challenges?
Multi-pronged challenges such as Poor interview questions asked (which does not bring out the relevant responses), unrelated questions and responses thereof, Circular and repetitive answers, shallow responses (a few words), too little questions/too many questions. Too many respondents rather than a few key respondents. This leads to too much volume/data overload.
I use Nvivo which assists in finding key words / patterns and trimming out unnecessary data.
Hi, You can read the my papers on the qualitative study to follow the process. The only way to overcome challenges is to refer Quality journal and follow the process.
Regards,
I did hear someone else talk about this issue and they mentioned a study they had done prior to the covid pandemic. But because of the delay, interruptions caused, they were advised by their supervisor to re-do the analysis as answers may have changed due to the pandemic. I disagreed, as I think the previous answers are still important for others to read. I don't know much about this area myself.
I have not yet reached this stage of my research, but for me Sachin Sukuna's answer hit the nail on the head, so to speak.
I have recently been experimenting with artificial intelligence for the interview of qualitative data via ChatGPT, and I am very impressed with the results. In particular, I started by re-analyzing data from two of my previous studies, and I was surprised by how rapidly the program produced the main concepts from those studies.
Just asking a few general questions produced the important key dimensions, and asking follow-up questions gave more detailed information about each of those dimensions. Of course, the program cannot literally "interpret" the results for you, but it certainly could replace a laborious coding process as a tool for locating the core content that you need to interpret.
Like any other approach to qualitative analysis, it does require familiarity with your data (you can't just throw anything at it), but beyond that, the program has a strong potential for being an alternative to existing techniques for the initial stages of working with qualitative data.
Dear David L Morgan . Would you please share the ChatGPT link you used?
Thanks
I have worked with both ChatPDF and ChatDoc, both of which you can find via a Google search. They both use ChatGPT 3.5 In addition, I tested out the askyourpdf extension for ChatGPT 4 through the Chrome browser, but found it to perform less well than the first two -- difficult to install, no link to quotations. no improvement in what was located or how the responses were written, etc.
The biggest challenge in qualitative analysis is gathering the required information from various sources and extracting the relevant data based on the study variables. I use READ approach i.e., ready the materials, extract the data, analyse the data and distil the findings. Document analysis has a systematic procedure to collect the qualitative data. I use weft software , Atlas ti.6 for handling text documents.
For reading, its a time consuming. For that, having a clarity in theoretical framework and conceptual framework helps to focus better in all documents. Tracing the required text will get easy.
In qualitative analysis you have not option to, just see many different types of documents. I preferred journals and field reports. But the must important is to be clear what you looking for.
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