1/ To follow up on yesterday's small q/Big Q thread here are the things I'm making a note of to emphasise in this year's qually res methods teaching to help students avoid appearing to be confused about their Q when they come to write their dissertation/thesis. First is research
https://twitter.com/drvicclarke/status/1444258228439764993
2/ questions - we see a lot of qual questions that are thinly disgused quant questions (how does A relate to B) in ethics apps. I'm going to give students egs of qually research questions - including the typology from Successful Qualitative Research: uk.sagepub.com/en-gb/eur/succ…
3/ & emphasise that qual questions are typically at the initial stages open & exploratory - we can't measures relationships between variables in any concrete way... & we need to centre participants' sense making (in res w/ people!) - so not impact of X but *perceptions* of impact
4/ Researcher "bias" or even influence - these for me are firmly in the small q camp. Biased knowledge/objective knowledge are a small q binary. In Big Q where we recognise knowledge production as inherently subjective - bias (=distortion of objective K) stops making sense...
5/ I will be encouraging students to centre notions of researcher subjectivity & reflexivity & start from the notion that they have inherently "influenced" their research - the question is how not whether. Noting the "small" size of the sample - small in relation to what? This
6/ suggests a lurking quant sensibility. Ditto in the classic evaluation that the small sample lacks generalisability. The problem here is the implicit conceptualisation of generalisability as statistical generalisability. There are Big Q alternatives: tandfonline.com/doi/abs/10.108…
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