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Qualitative data analysis necessitates some ingenuity in structuring a large amount of raw data, which can be challenging for educational researchers. I agree with Kiley on the essentiality of qualitative data organization, as organized data reduces confusion and enhances data collection. It is integral for a researcher to develop a clear qualitative data organization system at the outset (Wolff et al., 2019). I agree that using practical and straightforward naming approaches such as the project name, date, version number, or even experiment type assists the researcher in managing and organizing it. Systematic naming facilitates easier retrieval, lessening the massive qualitative data burden.
Furthermore, the file description technique allows the researcher to learn more about the file firsthand. It also aids in preserving information such as when the data was obtained, where the data was collected, and the meaning of abbreviations in the data, which aids in eliminating future confusion. The naming conventions for the original data files and subsequent analysis should be documented in a data dictionary file, including dates, locations, defining individual or group characteristics, interviewer characteristics, and other distinguishing aspects (Wolff et al., 2019). A clear organizing system helps facilitate data analysis.
Qualitative data is unstructured and has more depth which makes its analysis difficult. Researchers need the ingenuity to structure a large amount of raw data as organized data reduces confusion and enhances data collection. The first approach involves using practical and straightforward naming approaches when managing their data. Secondly, they should utilize the file description technique to preserve information detailing the collected data’s location, date, and meaning to avoid confusion and foster understanding. Adopting the two approaches eliminates future confusion in addition to easing data retrieval.
Reference
Wolff, B., Mahoney, F., Lohiniva, A. L., & Corkum, M. (2019). Collecting and analyzing qualitative data. The CDC Field Epidemiology Manual; Oxford University Press: Oxford, UK; New York, NY, USA, 213-228.
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