Using Nvivo for qualitative data analysis Workshop 2 Sue Jones

Advantages of using software packages with qualitative data It allows you to quickly:  Code  Uncode  Recode  Structure the coding system  Restructure the coding system This facilitates:  Shaping, framing and generating of theory  A sense of being close to the data  Changing your mind and rethinking  Being speculative and creative

Disadvantages of using software packages with qualitative data  They are often far too sophisticated for the needs of qualitative researchers  They can turn qualitative data into quantitative data  They can force a hierarchy on the data  You can become closer to the codes than you are to the data

Help with Nvivo8 sourceHandler.ashx/RelatedDocument s/DocumentFile/289/NVivo8-Getting- Started-Guide.pdf sourceHandler.ashx/RelatedDocument s/DocumentFile/289/NVivo8-Getting- Started-Guide.pdf ocument/NVivo8/NVivo8-Introducing- NVivo.htm ocument/NVivo8/NVivo8-Introducing- NVivo.htm

Other packages  Atlas Ti  Transana  Qualrus  Computer Assisted Qualitative Data Analysis 

The coding process A point is reached where every new interview is captured within the existing codes and coding frame (saturation) Horizontal coding of themes reflected across the interviews Vertical coding to account for individual perspectives Write definitions for every code and every cluster of codes Identify and describe links and relationships between codes Finally consider all of this in the light of existing theory and literature

What does a definition look like? A crisis in masculine identity The interplay of gender and underachievement was frequently viewed from the ‘poor boys’ perspective. Boys are pictured as having been cast adrift. They lack direction and focus, they have no role models, and struggle with a feminised curriculum, they daydream and lack interest. They are faced with images of themselves that do not say, ’boys have problems’ but rather that ‘boys are the problem’. At the same time girls are seen to be achieving and to be successful, indeed to be everything that boys are not. Teacher AP says that ‘boys at the moment lack direction in society’. Teacher XY says that ‘as the mother of sons I think it’s harder for boys’ Teachers XY and P joke about the current role models for girls and boys and XY says that ‘there’ll be female role models that are sassy, pert, bright, achieving. But the male role models don’t seem to be like that ……. Who can you be?. David Beckham or Homor Simpson, what a choice’.’.

Pitfalls to avoid Too close a correspondence between the codes and the initial interview questions. º Question ‘ Why do some children underachieve? º Code ‘Causes of underachievement’. Creating codes but not thinking about links between codes Codes morphing and changing in emphasis through the analysis process and so no longer represent the data coded in initial interviews Pre determining codes Cherry picking quotes

Writing up the analysis Let the analysis drive the organisation of your data Determine the key codes or clusters (core categories) Describe them using the definitions Be faithful to the spread of opinion: the untypical as well as the typical Talk about the differences between interviewees using the vertical analysis Explain how you understand or have theorised the relationship between codes or clusters Discuss in the light of existing theory and literature

Its not rocket science its social science! Everyone hears and sees how you appear, few touch what you really are. Machiavelli