Computer Aided Analysis of Qualitative Data Social Research Methods

Outline Introduction Computer-aided qualitative data analysis Grounded theory Principles and techniques of data coding Advantages and limitations to computer-aided qualitative data analysis Conclusion

Computer-aided qualitative data analysis Computer software for qualitative data analysis (Nvivo, ATLAS/ti, ETHNOGRAPH, NUD*ist) software packages: ‘tools to mechanize tasks of ordering and archiving texts… for “data administration” and archiving rather than tools for “data analysis”’ (Kelle 2000: 285) Kelle, U (2000), Computer-assisted analysis: coding and indexing, in M. Bauer and G. Gaskell (eds) Qualitative Researching with Text, Image and Sound. London: Sage, pp. 282-298.

Computer-aided qualitative data analysis and grounded theory Computer-aided qualitative data analysis is often connected to the grounded theory approach (Strauss and Corbin): Theoretical foundation Principle of coding Comparison techniques BUT computer software for qualitative data can also be used with other forms of analysis Computer-aided analysis and grounded theory share many of the same advantages and limitations

Grounded Theory: origins Introduced by Glaser and Strauss (The Discovery of Grounded Theory, 1967): Opposed to the testing of old theories (anti-Grand Theory and anti-positivist) Exploratory, constant comparative method Often used in qualitative and ethnographic studies Generates theory inductively through analysis of empirical data Limited role for pre-existing theory Tends to generate middle-range theory

Grounded Theory: “[It] is not really a specific method or technique. Rather, it is a style of doing qualitative analysis that includes a number of distinct features, such as the theoretical sampling, and certain methodological guidelines, such as the making of constant comparisons and the use of coding paradigm, to ensure conceptual development and density” (Strauss 1987: 5)

Theory generalisation: the method of constant comparison Theoretical sampling data collection is controlled by the emerging theory Stages of analysis Coding into categories comparison of coded incidents ideas about properties of categories Integration of categories and their properties interaction of properties interaction of different categories Theoretical saturation no new properties or categories appear and no new interactions occur Writing the (substantive) theory chapter headings – categories and interactions section headings – properties illustrative examples – coded data *see Seale 1999, pp. 96-97

(Strauss and Corbin 1998, pp. 101, 110) Key terms Phenomena – central ideas in the data represented as concepts Concepts – the building blocks of theory Categories – concepts that stand for phenomena Properties – characteristics of a categories, the delineation of which defines and gives it meaning Subcategories – concepts that pertain to a category, giving it further clarification and specification Memos – the researcher’s record of analysis, thoughts, interpretations, questions, and directions of further data collection (Strauss and Corbin 1998, pp. 101, 110)

Coding data: Strauss and Corbin 1998 Further development of the grounded theory approach in the 1970-90s. Strauss and Corbin: three ways of coding data: Open coding Axial coding Selective coding

Open coding “naming and categorising phenomena through close examination of data” broader or more comprehensive and more abstract labels insightful labels “borrowed” concepts “in vivo” codes (catchy terms) (see Strauss & Corbin 1998, p. 115)

Further elaboration of Open Coding (through constant comparison): Axial Coding “microanalysis” of a single category, exploring its conditions, contexts, action/interaction and consequences Selective Coding emergence of theory selection of a single ‘core category’ (all other categories have a subsidiary role)

Criticisms of Grounded Theory Inductive vs. deductive? presence of theory before data collection and testing theory in the course of research (e.g. research question, researcher’s training, etc) Data dependency High risk of superficial strategies Critique from postmodernism the narrow analytic strategy – heavy reliance on coding standardized and mechanistic procedures fragmented and decontextualized data single, exclusive interpretation of data (researcher’s control over data and analysis) non-reflexive approach (relational nature of the qualitative research is not acknowledged)

Advantages of computer-aided qualitative data analysis Efficient, save time, assist the management of larger samples, good for research teams Can make the research process more systematic and explicit, which makes it seem more valid or trustworthy Can enhance the researcher’s creativity, by allowing more time to experiment and play with the data (Kelle 2000, pp. 293-294)

Limitations of computer-aided qualitative data analysis Can become overwhelmed by larger samples and the wider volume of data that the software can technically manage. Larger samples and more software tools/functions does not necessarily make the research more valid. Could potentially alienate researchers from their data and impose methodological approaches (ie. grounded theory) which overemphasise coding and neglect other forms of textual analysis. (Kelle 2000, p. 294)

Conclusion Computer aided qualitative data analysis shares many advantages and disadvantages with grounded theory. BUT these software packages are primary tools to assist with qualitative research and can also help facilitate different forms and methods of qualitative analysis. Helpful to think about two different modes of coding (Kelle 2000, p. 295): referential, as signposts to certain text passages (open, inductive and interpretive) factual (more deductive and related to classic content analysis)