1/11 Qualitative data analysis
We are now going to focus on qualitative data analysis. Let's start with simple definitions and explanations:
In contrast to quantitative data, qualitative data does not simply count things, but is a way of recording people's attitudes, feelings and behaviours in greater depth.
Qualitative data analysis is:
- Often based on grounded theory practices (link to explanation of grounded theory)
- Answers the 'why?' questions
- Pays greater attention to individual cases
Sources of qualitative data analysis
We can gather qualitative data in a variety of ways, for example:
- Questionnaires/Surveys: a series of questions and other prompts for the purpose of gathering information from respondents..
- Interviews: a conversation between two or more people (the interviewer and the interviewee) where questions are asked by the interviewer to obtain information from the interviewee.
- Focus Groups: a group of people are asked about their attitude towards a product, service, concept, advertisement, idea, or packaging.
- Observation: a group or single participants are manipulated by the researcher, for example, asked to perform a specific task or action. Observations are then made of their user behaviour, user processes, workflows etc, either in a controlled situation (e.g. lab based) or in a real-world situation (e.g. the workplace).
- Discourse Analysis: a general term for a number of approaches to analyzing written, spoken or signed language use.
Why we do qualitative data analysis
- Looks further than precise numerical evidence
- Looks for categories such as events, descriptions, comments, behaviour
- An inductive process - developing theories from the data you have gathered
- Coding of categories and sub-categories identified
- Compares codes, looking for consistencies, differences, patterns etc
- Looks for new and emerging categories.