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Teacher Ed Honours: Research Design
Transcript of Teacher Ed Honours: Research Design
Feeding or watering qualitative research
Findings and claims
Good qualitative research needs to have a solid trunk.
Height = going beyond what we already know - making your contribution. For an honours project this can be relatively modest: don't build a trunk that is too tall and thin! Plan something you can make 'thick'...
Thickness and sturdiness come from the relevance of your methods to your question(s), and the quality of the evidence (data) you generate
Qualitative research design
Step back and remember to answer the question: so what?
How does your tree look compared to those around it (other studies in your field) - why should be even bother looking at this, let alone tasting the fruit (listening to your conclusions?)
In your study you will find some things out about the case or empirical context you have studied. You make CLAIMS based on the DATA, about that CASE.
You won't be able to present all possible claims:
focus on those that are most interesting, say something new, and are best supported by your evidence
You have to move beyond your claims (about what you studied) to make conclusions about something of wider interest.
Make it apetising and easy to digest!
(University of Technology, Sydney)
Do a 'neighbourhood' analysis - what research gets closest to yours? what is in your wider area?
Just like you check whether a plant is wilting or drowning...
You've got to keep checking your research is 'plumb' - that the assumptions, questions, design, theories, and methods all line up
- See Chenail R J (1997) Keeping things plumb in qualitative research. The Qualitative Report 3(3)
Why here and not there?
Why this topic and not another one?
Why should I or anyone else care?
Strategy / general approach
Case study (multiple / single; Stake vs Yin)
.... leads to questions of sampling...
Samples matter (differently) in qual research!
Who do you talk to / observe?
How are they selected? Who is left out? What does this mean for your claims and conclusions?
What is your relationship to participants and how/why does this matter?
Would more mean better?
Samples can be large/small, but also homogeneous / diverse, random / targeted...
Whose involvement best helps answer your RQs?
What you have to resource (feed) your qualitative study also depends on:
Practicalities (time, money, geography)
Compromise is not a dirty word. Reflecting on the implications of decisions / limitations is the way forward.
Questionnaire? Interviews? Observations? Documents? Visual?
Before you get into the nitty gritty of how you do these, you've got to ask how they line up (are plumb with) your RQs
What does each give you evidence of?
INTERVIEWS/SURVEYS = what people say when you ask them X
OBSERVATION = what you notice and note when present at X
DOCUMENTS = what X (authors) wrote at a particular time
VISUALS = how X chose to represent Y (maybe an interview could tell you why, what it means)
What evidence do you need to answer your RQs?
This is about how you actually generate (not collect) your data
SURVEY DESIGN: open/closed questions
INTERVIEW: (un)structured? what does your relationship with participants mean now? (age, gender, power etc)
OBSERVATION: how does your presence affect the action? Does it matter? What do you notice? What are you looking for?
VISUALS: who creates images? How (SPD vs PE)
Is there not an AESTHETIC quality in doing this well? Is there not artistry as well as rigour?
Don't forget all aspects of design are shaped by practical & ethical considerations, as well as research questions, and your personal preferences / affinities
How tall is tall enough?
When do you have enough data?
SATURATION - stop learning / noticing new things
But you may not get there, especially in an honours project
So practicalities, ethics, time limits etc are okay as reasons to stop!
Analysis takes our data and reaches out over the terrain in which our tree is planted...
It has to stay 'plumb' - address your research questions, and have a firm basis in your evidence.
Parsimony rules! Balance between simplicity and power of insight
Seeking AN not THE interpretation of particular data
Strategy, Sampling, Methods, Techniques