Wasted time and misdirected analysis: The analysis lacks focus and the research reports on the wrong thing. No goals set for the analysis: The aims of the initial data collection are lost because researchers can easily become too absorbed in the detail. It can be hard to see which details are useful and which are superfluous.Īnalysis becomes a description of many details: The analysis simply becomes a regurgitation of what participants’ may have said or done, without any analytical thinking applied to it.Ĭontradicting data: Sometimes the data from different participants or even from the same participant contains contradictions that researchers have to make sense of.įindings are not definitive: Analysis is not definitive because participant feedback is conflicting, or, worse, viewpoints that don't fit with the researcher's belief are ignored.

Rich data: There are lots of detail within every sentence or paragraph. Superficial analysis: Analysis is often done very superficially, just skimming topics, focusing on only memorable events and quotes, and missing large sections of notes. Large quantity of data: Qualitative research results in long transcripts and extensive field notes that can be time-consuming to read you may have a hard time seeing patterns and remembering what’s important. The table below highlights some common challenges and resulting issues. Many researchers feel overwhelmed by qualitative data from exploratory research conducted in the early stages of a project.

emerges when related findings appear multiple times across participants or data sourcesĬhallenges with Analyzing Qualitative Data.

is a description of a belief, practice, need, or another phenomenon that is discovered from the data.

What Is a Thematic Analysis?ĭefinition: Thematic analysis is a systematic method of breaking down and organizing rich data from qualitative research by tagging individual observations and quotations with appropriate codes, to facilitate the discovery of significant themes.Īs the name implies, a thematic analysis involves finding themes.

Thematic analysis, which anyone can do, renders important aspects of qualitative data visible and makes uncovering themes easier. Qualitative behavioral data, such as observations about people’s behavior collected through contextual inquiry and other ethnographic approaches Qualitative attitudinal data, such as people’s thoughts, beliefs and self-reported needs obtained from user interviews, focus groups and even diary studies This research often produces a lot of qualitative data, which can include: In the discovery phase, exploratory research is often carried out. But how do you summarize a collection of qualitative observations? Summarizing a quantitative study is relatively clear: you scored 25% better than the competition, let’s say. Uncovering themes in qualitative data can be daunting and difficult.

How to use nvivo for thematic analysis