Hand Coding Versus Qualitative Data Analysis Software

Hand Coding Versus Qualitative Data Analysis Software

When comparing hand-coding to qualitative research analysis (QDA) software, my first reaction is that QDA is more labour-intensive than hand-coding. Many researchers still hand-code on paper, while others have switched to using a QDA software application. I see the value and richness of data analysis utilizing qualitative data analysis software. Still, before conducting additional research and learning about QDA, I chose to code by hand manually. I couldn’t afford the time it would take to learn the software. Rubin and Rubin (2012) use QDA software to improve the efficiency of project analysis and evaluation. I will continue to contribute insights about QDA software, such as MAXDA2020 and NVivo, based on my experiences with these programs and hand-coding.

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Hand-coding necessitates the creation of functional and directional codes by hand. Pen, paper, note cards, a hard copy of the transcripts, and the artifacts or documents to be coded are the only items required for this coding method (Meyer & Avery, 2008). Outside of a more familiar program like Excel or Word, they, too, necessitate the “relearning” of a new step-by-step approach. Hand-coding on paper is an excellent approach to examining data if the data sets are limited and allows the researcher to code data without spending time or money on obtaining a software tool. When compared to utilizing a software program, one downside of hand-coding is that it does not allow the coder to see the full breadth and depth of what might arise from their data sets. When selecting a coding approach, one should also examine the sufficiency of less detail. Furthermore, hand-coding is time-consuming because it takes longer to identify and locate coded data. It may be difficult for some to organize and sort page by page, looking for the position of the code.

Computer-Aided Qualitative Data Analysis Software (CAQDAS) such as Atlas. Ti, In Vivo, Transana, and NVivo are required for QDA software for coding. QDA software includes tools to aid qualitative research, such as recursive abstraction, grounded theory methodology, discourse analysis, content analysis, transcription analysis, coding, text interpretation, and so on (Predictive Analysis Today, 2016b). After researching and reviewing various coding tools, I have concluded that QDA software applications will and can provide greater flexibility in coding any data size. However, I’m not sure if your data collection is small enough. Should one spend effort and money on QDA software? Coding is popular because practically any fundamental notion, event, or concept may be coded as respondents express it immediately inside each data line. Suppose a researcher wants to get the most out of their given data for their dissertation, thesis, or any project in comparison; QDA software can help. In that case, fantastic results and conclusions can be generated from the data set(s) (Smith & Firth, 2011).

I have learned from investigating various QDA software that it is a valuable and essential tool for all academics, but especially for those working on large-scale datasets where hand-coding would be impracticable. Furthermore, electronic coding can save time when writing peer-reviewed literature by allowing the researcher to organize codes, conduct queries, and more readily code frequencies (Predictive Analysis Today, 2016b) and study correlations between different attributes.

In light of the pros and downsides, this author believes that QDA software is neither easy to understand nor simple to learn. Learning how to write and set up the project at hand is critical to maximizing the ability to retrieve and query data (Patton, 2015). Though feasible and attainable, this might be a complicated procedure. Depending on the size of the data set in my study, I’m unsure if I’ll utilize a QDA application or start hand coding. For richer results, I will most likely use electronic coding.

Everything I’m considering for my upcoming capstone is based on what I’ve learned in my coursework. My capstone begins in less than a month, and I’m feeling reasonably prepared, which I consider a win. It has been challenging to assimilate content and connect the dots at times, which I believe is due to online learning and the time provided for working on all tasks, including everyday life. This course has been unique with the addition of journaling and the workshop rather than the discussion board. Critical comments have dramatically improved my knowledge; thank you. Building on the criticism, I could exit week nine with a “nice, thanks” – after two lessons in a row and numerous defeats, I clicked my heels. Thank you very much. Prof. Hein

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References

Meyer, D. Z., & Avery, L. M. (2008). Excel as a Qualitative Data Analysis Tool. Field Methods, 21(1), 91–112. doi:10.1177/1525822×08323985

Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice: the definitive text of qualitative inquiry frameworks and options. Thousand Oaks, CA: SAGE Publications, Inc.

Predictive Analysis Today. (2016b). Top 21 free qualitative data analysis software. Retrieved from http://www. Predictiveanalyticstoday.com/top-free-qualitative-data-analysis- software/

Smith, J., & Firth, J. (2011). Qualitative data analysis: the framework approach. Nurse Researcher, 18(2), 52–62. doi:10.7748/nr2011.01.18.2.52.c8284

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3- to 5-page  describing considerations for choosing to use QDA software. Include  the following:

Summarize your experience with coding using Excel or Word. Identify what worked well, where you struggled, and how the coding process evolved.

Hand Coding Versus Qualitative Data Analysis Software

Summarize your research on your two choices by comparing and contrasting features. Describe why you chose these two versus the others and what you are considering for your capstone, given your experience in this course.