11: Three Ways That Qualitative Analysis Software Will Save Your Qualitative Research Study
Qualitative research is essential for describing the rich experiences of your participants. Unlike quantitative research, qualitative research focuses on the quality and rich description of personal experiences and perceptions rather than focusing on the quantity of such perspectives as measured through a survey.
Due to the process of capturing unique perspectives through interviews, a focus on categorizing and coding text from transcripts and documents is important. One challenge to coding a significant amount of text manually is securing a method to effectively code and assign text to specific categories which can be easily accessed later. The good news? Qualitative analysis software packages such as NVivo, Atlas.ti, and Dedoose help qualitative researchers address common pitfalls and obstacles. Here are three ways that qualitative analysis software will save your next qualitative research study.
1. Code and Store Text for Easy Access
Feel free to ditch the process of manually highlighting your transcripts to note potential themes. Instead, qualitative analysis software offers highlighting tools that automatically stores highlighted text under specific categories or codes. Once you’ve coded all your transcripts, simply click on the selected category or code to locate all the assigned text.
2. Identify Possible Within-Group Differences Through Matrix Coding
Matrix coding allows the researcher to analyze demographic data alongside interview transcripts by assigning specific attributes (e.g., gender, race and ethnicity, age, socioeconomic status) to a single transcript. This tool will allow you to see whether there are coding differences between your female and male participants, young and old participants, etc. Maximize this tool by using graphs to visualize any coding differences among groups.
3. Explore Query Options to Identify Additional Findings
In addition to the coding tool, most qualitative analysis software packages also include other query options that supplement your findings. Complete your discussion of the results with a word cloud (a visual representation of the most common words in your data set) or a word tree (a visual representation of the context surrounding specific words and phrases).
Navigating new software can be scary, but it can also save you a lot of time and effort on your next project. Don’t be afraid to seek help through experienced researchers, workshops and trainings, and online resources such as YouTube tutorials. Good luck!
