This sort of work NEEDS software – there’s a prevailing view that this either can’t be done (you can only work with numbers) or that it will only quantify data and somehow corrupt it and make it non-qualitative. This requires using tools to help automate the classification, sorting and sampling of that unstructured data in order to be able to engage with interpretations. But that s small fry – the biggie is looking at the module evaluation data for all modules for all years (~130,000 comments!) Next steps include analysing the PRES and PTES survey comments. I’m working on a project to analyse the NSS (National Student Survey) qualitative textual for Lancaster University (around 7000 comments). Analysis techniques have not been developed that would allow researchers to take advantage of this fact. Qualitative analysis has not really come to terms with the fact that enormous amounts of qualitative data are now available in electronic form. They have used their new computerized analysis possibilities to do more detailed analysis of the same (small) amount of data. Qualitative analysts have mostly reacted to their new-found wealth of data by ignoring it. The signal characteristic that distinguishes online from offline data collection is the enormous amount of data available online…. A quick post here but one that seeks to place the rather polemic and borderline-ranty previous post about realising the potential of CAQDAS tools into an applied rather than abstract context.
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