NVIVO Chapter 4 Working With Data

1. NVIVO Chapter 4Working With Data

2. Overview • Discover strategies for seeing and naming concepts and categories in your data • Read, reflect, link and store ideas • Use annotations, memos and nodes • Begin to visualize ideas or patterns of events

3. Goals for Working With Data • Get a “rounded perspective” on your data • Strive to develop working concepts • Why is this important? • Where will the ideas take me? • May reflect in how you name nodes or write memos • Lay the foundation for key themes • Identify patterns in the data

4. Gain a Perspective on the Text • Reading and Thinking • Using Memos • Using Tables • Annotating (The Comments Field?) • Marking and Linking • Hyperlinks (Things You Can’t Download or Include) • “See Also Links” (Text) • Great table on pg 65 of Bazeley

5. Building Knowledge of the Data: Coding • Raw data reflect “the undigested complexity of reality” (Patton, 2002) • Codes are a way of classifying and tagging text (or indexing it) for later retrieval • Connects data to ideas, and the ideas back to the data (facilitates data retention, not data reduction) • Codes also form the initial patterns of association and help identify relevant concepts and linkages

6. Approaches to Coding • Splitters: maximize differences between text passages looking for fine-grained themes • Lumpers: minimize differences between passages looking for overarching themes • “Have a bet each way”: A little of each

7. For the Lumpers • Broad-brush/bucket coding: Allows for text sorting and coding from within the program • Get the broad view • Identify relevant text • “Park” the text you don’t want to think about yet… • Identify sequences • Complete preliminary analysis • Sort answers according to the questions • Code the backdrop for the main issues

8. For the Splitters • Coding detail • Uses the software to merge nodes or create tree nodes • Detailed, slow exploration of the text • Line-by-line coding • Reading between the lines • Break open the text • This “microanalysis” creates an awareness of the richness of the available data • Focuses your efforts on the text, not on preconceived notions; helps to identify patterns

9. Fracturing or Slicing Data • Multiple nodes can be used to code a passage of text • Resolves the data into its constituent components • Ask: • What conditions might relate to an initial code? • What interactions might exist? • What strategies or consequences can be related? • All about opening up the data (use memos to capture) • Use descriptions or properties to enable coding queries • Helps to avoid repetitive nodes Look at each passage for what action is occurring, and who or what is the source of that action…

10. Strategies for ID’ing and Naming Codes • Issues with your text: • Something is happening in a particular setting at a particular time • Particular groups or people are involved, with their own beliefs or background • Consequences arise from these issues • Dealing with this in NVIVO • Code each “component” separately—use multiple codes for the same passage of text • Store concepts, codes, components, or categories in a Node

11. Seeing As… • Need to avoid being sidetracked • Look at your data: • Identify what’s interesting…highlight that passage • Ask why it’s interesting (can the code come from this?) • Why am I interested in this passage? Does it lead to a concept or a node? • Memo the process

12. A Priori Coding • Some come to coding with a list of concepts in mind • Extensive literature review • Prior experience • Strong theoretical background • Having this list can be beneficial, especially in a time crunch; however, it can also confine the text

13. In Vivo Coding • Using the actual words from the text/source to determine a code • The actual expressions of the participants • Look for local terms • Use the language of the participants to label the concepts • Can be done directly in NVIVO

14. Repetitions/Regularities • Anything that’s important will come up again • People repeat ideas that have significance for them

15. Ask Questions to Develop Codes • Who, what, when, why, how, how much, what if, what for, with what results… • What actions or interactions are occurring? • What strategies are being applied? • Under what conditions? • With what consequences? These all can help develop codes…

16. Compare and Contrast • Compare two segments of text • How are they similar? How are they different? • Do these differences or similarities construe a dimension worth exploring, or a variable running through the narrative?

17. Record Narrative Structure and Mechanisms • Watch how things are said… • How is the response structured? • Things to watch for: • Transitions/turning points • Inconsistencies, silences, omissions • Use of metaphors and analogies • Repetitive phrases • Although there is “narrative analysis”, doing these steps can help clarify the data and lead to possible codes

18. Storing Codes in Nodes • Nodes: points at which concepts could branch out into sub-concepts or dimensions • NVIVO nodes only refer to the source document, they don’t replicate the data • The source remains intact • Information about the source is always maintained • Always possible to view the passage in its original context • Passages can be coded in multiple nodes without losing data integrity

19. Nodes • Free Nodes • Parent Nodes • Trees • Stores coding • Sometimes used for organizational purposes

20. Other Thoughts on Coding in NVIVO • Adding coding: It’s always possible to go back and add more • Automating coding: The software will do this based on a number of source parameters • Text headings • Standard questions • Heading levels