Types of data analysis
The means by which you analyse your data are largely determined by the nature of your research question, the approach and paradigm within which your research operates, the methods used, and consequently the type of data elicited. In turn, the language and terms you use in both conducting and reporting your data analysis should reflect these.
The list below includes some of the more commonly used means of qualitative data analysis in educational research – although this is by no means exhaustive. It is also important to point out that each of the terms given below generally encompass a range of possible methods or options and there can be overlap between them. In all cases, further reading is essential to ensure that the process of data analysis is valid, transparent and appropriately systematic, and we have provided below (as well as in our further resources and tools and resources for qualitative data analysis sections) some recommendations for this.
If your research is likely to involve quantitative analysis, we recommend the books listed below.
Types of qualitative data analysis
- Thematic analysis
- Coding and/or content analysis
- Concept map analysis
- Discourse or narrative analysis
- Grouded theory
- Phenomenological analysis or interpretative phenomenological analysis (IPA)
Further reading and resources
As a starting point for most of these, we would recommend the relevant chapter from Part 5 of Cohen, Manion and Morrison (2018), Research Methods in Education. You may also find the following helpful:
For qualitative approaches
Savin-Baden, M. & Howell Major, C. (2013) Data analysis. In Qualitative Research: The essential guide to theory and practice. (Abingdon, Routledge, pp. 434-450).
For quantitative approaches
Bors, D. (2018) Data analysis for the social sciences (Sage, London).