Qualitative Data Analysis in NVivo

What is qualitative data?

• Data representing concepts, insights and ideas that are not (re)presented in numbers
• Used in qualitative research which is unstructured and focuses on the points of view of the participants
• Differs from quantitative data that are often structired and focus primarily on and are represented with numbers
• Qualitative data from interviews, focus groups, observations, web scraped content, images, maps etc.

Qualitative data analysis (QDA)

• This is the process of organizing, analyzing and interpreting qualitative research data to generate themes, patterns, insights or answer research questions.

Purpose of QDA

• Used when research is explorative in nature, and there are not many (or any) research already conducted in the area
• To uncover valuable insights and deeper meanings that may not otherwise be uncovered in quantitative data
• To suit disciplinary preferences and practices, as well as research and data collection types

Benefits of QDA

• Explores the ‘whys' and ‘hows’ of a research context for deeper understanding of participants' experiences
• Captures emotions and personal feelings which cannot be captured in numbers
• Explains patterns of knowledge, intent, and action being presented as data
• Identifies new areas of inquiry different from predetermined research questions
• Explores diverse viewpoints because it is user-centered
• Complements or helps to explain quantitative findings (in the case of mixed-methods research)

Challenges of QDA

• It could be time consuming and labour-intensive
• Findings may be subjective to the researcher’s interpretations
• It could be challenging to replicate the process
• Some proprietary QDA tools are expensive for individuals