Data analysis

Data analysis

1. two categories:

   • Qualitative
     • Information from:
       • Journal/diary entries, interviews, classroom recording of interactions, observation notes
     • Tools
       • Categorising
         • Coding de data
           • Inductive coding
             • Scan the data "perspectives of people in terms of opinions and views"
           • Deductive coding
             • Develops categories based on literature/theoretical knowledge
           • Steps
             • 1. Gather together all the data
               • 2. Read the data in order to geat a good feel for what is there
                 • 3. Give a lable to the main idea or theme
                   • 4. Develop a number of different labels for the ideas
                     • 5. Make a list of the initial categories
                       • 6. Check again and see whether you can group them more into sub categories that all related to the main category label.
                         • Until identified all ideas that cluster together
                         • 7. Make a note on your category list of where the sub-categories fit in.
                           • 8. Show the categories to a collegue and share suggestions.
       • Analysing
         • Richard's steps:
           • 1. Providing a general characterisation
             • Getting a general sense of the kind of interaction you are listening to and giving it a description
           • 2. Identifiying grossly apparent features
             • It is best to hold back on interpretations at this point if you can and focus on the obvious.
           • 3.Focusing in on structural elements
             • Begin to examinate the finer details of how the interations are structured and describe noticiable features
           • 4.Developing a description
             • When steps 1-3 are completed. Giving an objective picture of the interaction related to what we have seen in the data.

2. Think about...

   • Reflecting and doing the action is essential in ACTION AND REFLECTION "AR"
     • Ongoing reflection is satisfying and makes the research worthwhile
     • AR reducing information to find explanations and patterns
       • Extract the key meanings and messages
       • centre attention on what data tells

3. It is dynamic, cyclical, and recursive

   • Steps in order to get an overall framework in the analysis
     • 1.Assembling your data
       • Collect all the data, review questions, start going though your data
     • 2.Coding the data
       • Identify which data sources you can code qualitative
     • 3.Comparing the data
       • Compare categories or patterns, develop tables, charts, set of quotes
     • 4.Building meanings and interpretations
       • Think deeply, look for more abstract, identify connections, refine personal theories
     • 5.Reporting the outcomes
       • Story of your research