Working with networks stimulates a different kind of thinking and allows further explorations.
WHAT TO DO WITH YOUR DATA: Qualitative & Quantitative Research
Networks can also be used as a means of talking with others about a finding or about an idea to be developed. Before you reach the last step of the analysis, several networks will probably have been drawn, redrawn, deleted and created anew.
The aim is to integrate all the findings and to gain a coherent understanding of the phenomenon studied; or, if theory building was your aim, to visualize and to present a theoretical model. The starting point for your data analysis should be the methodology you have chosen.
Based on this, you need to ask yourself which function or tool in the software you need to use to advance your analysis. It is important that you always start with your research goals and do not let a software tool drive the analysis. Ask yourself step by step along the way what you want to achieve; think about which functions and tools in the software can help you to achieve it — this is the process of translating your methodology into executable steps in ATLAS.
The N-C-T method described below describes a generic approach to analysis. I recommend making it the core of your computer-assisted analysis, variated by and adapted to the chosen methodological approach. Noticing refers to the process of finding interesting things in the data when reading through transcripts, field notes, documents, reports, newspaper articles, etc.
In order to capture these, the researcher may write down notes, mark the segments or attach preliminary codes. Codes may be derived inductively or deductively. At this point, the level of a code does not play a role. Codes may be descriptive or already conceptual. The important point is to mark those things that are interesting in the data and to name them. Collecting : Reading further, you will very likely notice a few things which are similar to some you have noticed before.
They may even fit under the same code name. If a similar issue does not quite fit under the same heading as the first issue you noticed, you can simply rename the code to subsume the two. Even if the term is not yet the perfect code label, it does not matter. It will be easier over time when you continue to collect more similar data segments to think of a better and more fitting label.
Thinking about things: We need to think when noticing things, when coming up with good names for codes, or when developing categories and subcategories. We need to do some more thinking when it comes to finding patterns and relations in the data. How can we integrate the various aspects of the findings in order to develop a comprehensive picture of the phenomenon studied? Figure 2: The recursive process of noticing, collecting and thinking Friese, Figure 2 shows that noticing , collecting and thinking goes hand in hand and back and forth.
You will rework your codes and the code system several times, you may come to the realization that you need more data even in the second analysis phase.
If you query your data, you may still be adapting codings. With every cycle you go through, the changes will be smaller, and you will understand your data better, until you are satisfied with the insights you have gained. Overall, I can assure you — it is a rewarding process. Figure 3 summarizes the process of computer-assisted N-C-T analysis.
- Also from SAGE Publishing.
- Using Software in Qualitative Research;
- Moonshine nation: the art of creating cornbread in a bottle.
Figure 3: The process of computer-assisted qualitative data analysis Friese, Bodgan, Robert C. Boston, MA: Pearson Education. Bong, Sharon A. Debunking myths in qualitative data analysis. Bourdon, Sylvain , May. The integration of qualitative data analysis software in research strategies: Resistances and possibilities [30 paragraphs].
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Charmaz, Kathy Qualitative interviewing and grounded theory analysis, in Jaber F. Gubrium and James A. Thousand Oaks, CA: Sage. The new edition is extraordinarily authoritative and seriously useful, detailed yet unfailingly interesting. It confronts the reader firmly with the challenges and complexities of qualitative work and the power, mixed offerings and sometimes considerable limitations of existing software. It's so carefully written, and the authors' voices are so clear, that it encourages, steadily explains and assists. The authors' enthusiasm and unique experience and knowledge of the field shine through, so against all odds for such a technical work, this book is a bloody good read!
The project provides information, advice, training, and ongoing support in different software programs designed to facilitate qualitative and mixed-methods analysis. Christina also undertakes research, training, and consultancy via her consortium Qualitative Data Analysis Services Ltd.
Christina has trained thousands of researchers and students to use qualitative software since Du kanske gillar. Permanent Record Edward Snowden Inbunden. It is a great resource for qualitative research instructors and undergraduate and graduate students who want to gain skills in analyzing qualitative data or who plan to conduct a qualitative study. It is also useful for researchers and practitioners in the social and health sciences fields.see
A Step-by-Step Guide to Qualitative Data Coding
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