L10 Data analysis, reporting, and discussion Flashcards
What is data reduction?
A series of small steps you take to convey the key messages found in your research. Going from data to results.
- What data do you have?
- Research perspective (conceptual framework)
- What are your deliverables?
What makes a great results section?
- Conveys a clear message (data = redacted)
and simultaneously - Is transparent about how you reached your results (results are linked to data)
What should you remember when making a great results section?
- Smart grouping is the basis for all analyses
- Data analysis starts during data collection
- Taking field notes during and directly after the interview
- The right member check
- Coding the data: find the right balance
- Data analysis does not end with open-axial-selective coding
- Re-iterate your results section
What are the steps in the coding process?
- Iterative coding
- Integration of core categories into theory
- Find a storyline around core categories
- Validate relationships between categories against
data - Re-iterate
What is a member check?
A technique used by researchers to help improve the accuracy, credibility, validity, and internal validity of a
study
- Not a summary
- Based on the preliminary analysis of your interview
- Integrate your interpretation, based on your field notes
- Ideally you would integrate quotes and tell them in which context you intend to use it
How do you start your analysis?
Data analysis is not summarising
- First set of data (e.g. 3 interviews): cluster and categorize
- Find relations between categories (hierrchy, matrix, causal): possibly develop new hypothesis
- Collect new data based on hypothesis
When coding data, what balance do you need to find?
The balance between:
- Label everything (but how to decide on what is important?) –> only code what helps you in answering your research question
- Label on a too abstract level (jump to conclusions) –> don’t forget to look at what the respondent is actually saying
What are two starting points for data analysis?
- Procedures: coding, indexing, categorizing
- Creativity: interpreting, exploring relations
How do you re-iterate your results section?
- Write three pages of results
- How to structure your results section in order to answer your RQs?
- Elaborate one section (about 3 pages long)
- Let someone check and focus on transparency and clarity
What is the discussion, and what’s in it?
= What your data shows
–> How has the field’s knowledge been changed by the addition of this new data?
- Where you speculate while avoiding rambling, guessing, or making logical leaps beyond what is reasonably supported for your data
- -> Balance between knowledge claims and creativity
Reversed funnel structure
- Key messages
- Why are they interesting and how can they be explained?
- What should we do next?
- Limitations
- Conclusion
How can you come up with elaborations in your discussion?
Compare and contrast technique
- Draw up a table describing where your work is simialr to others and where it differs. Use each of these points as a prompt to write a short paragraph on why.
The null hypothesis technique
- Write down why the results mean nothing. Sometimes forcing yourself to argue the reverse position can highlight the relationships or ideas worth exploring.
Organize an audience
- Explain the results to a friend and record yourself. Many people find talking an easier way to get ideas out. Alternatively write them in an email to someone.
Re-read the notes from your first introduction
- Sometimes those references that were just off-point for your introduction fit perfectly in your discussion
What do you write in the first paragraph of the discussion?
- You rephrase the objective and the key messages
- There should be 2-4 key messages in your report
What do you write in the next 2-4 paragraphs of the discussion?
What makes your key message interesting
- Per key message, relate your findings to the issue you raised in the introduction
- Note similarities, differences, or trends. Compare with previous findings.
- Defend your answers if necessary, by explaining both why your answer is satisfactory and why others are not.
How can your key message be explained?
- Set up a dialogue between results and theories
- Try to interpret unexpected findings in terms of method, conflicting theories, or a structured hypothesis
- Discuss and evaluate conflicting explanations of the results
- Discuss unexpected findings
What do you write in your implications for practice and policy section?
What are the practical implications of your results?
- What should policy makers / practitioners / doctors / patients / entrepeneurs do different?
What are the academic implications of your results?
- What additions / confirmations / explanations / refinements can you provide to current theory or methodological practice?
What do your write in your limitations and future research section?
Explain the limitations of the work: what is left out or yet to do?
- Do not describe flaws in your study design
- Demaracte your study findings. What can we learn from this and what can we not? Up to what point are your results valid?
What should other studies do to broaden the scope of our knowledge?
