Data analysis

Abstract

Data analysis sometimes feels like the ‘dark art’ of research. It is often poorly understood, scantily taught and barely explained. Yet analysis is the beating heart of our work as researchers. This chapter outlines creative approaches to analysing data in education research. You will get most benefit from reading this if you already have a good grounding in when and how to use conventional methods of data analysis. If you lack confidence in this area, we would recommend consulting the relevant section(s) of a good methods text, such as Cohen, Manion and Morrison (2018, part 5), ideally before reading the rest of this chapter. Creative data analysis can refer to the analysis of data gathered using creative methods such as those covered in the previous two chapters. Alternatively, it can refer to creative methods of analysing data gathered using creative or conventional methods (or a combination of the two). This chapter focuses on the latter, as the former is more fully covered in the literature (for example, Rose, 2016; Lenette, 2019). The use of creative methods in analysing data makes no difference to good practice in research. Analytic work still needs to include meticulous preparation and coding of data, accurate description and representation and appropriate use of power in interpretation. Creative analytic work can be done by hand, using software or with a combination of methods. In this chapter we invite you to consider: the potential role of embodiment in data analysis; how to analyse visual data creatively; creative ways to analyse data using arts-based techniques; creative approaches to multi-modal data analysis; and the ethical aspects of analysing data.