Title: Introduction to analysis
Course: EDPS0009: Researching Education and Society: Qualitative Methods 2020/2021 > Section: 6. Analysis

Data analysis is a systematic approach to making sense of and making meaning from data collected during the research process. In many published articles this stage of the research is presented along the lines of "we transcribed the data, we coded the transcripts and the following themes emerged". Unfortunately, this is a serious mis-representation of the process, which requires the researcher's active participation in order to interpret data, make sense of it and make meaning from it.

More recently, qualitative researchers have focussed on the important and active role the researcher plays in analysis, and there are now publications highlighting the active sense-making. e.g.:

- Atkinson, P. (2017). Thinking Ethnographically. Sage.
- Morgan, D. L. (2018). Themes, Theories, and Models. Qualitative Health Research, 28(3), 339-345.
- Saldaña, J., & Omasta, M. (2017). Qualitative Research: Analyzing Life. SAGE Publications.

In order for data analysis to be a systematic way of making sense of data, there obviously needs to be some kind of "system", which we follow. And this is where the different traditions of and approaches to data analysis come in.

There are many ways of how analysis can be carried out, here are some more popular and common examples:

For the purpose of this module, we will focus on Thematic Analysis, Discourse Analysis and Grounded Theory, whereby you will not be expected to apply Grounded Theory in your course work.