Really great questions posed in class yesterday and on the 'tickets'! I'm going to attempt to respond to your questions, while inviting you all to share your insights as well.
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Why do I prefer Transana over InqScribe?
I use both. Transana is a tool I sometimes prefer when I'm considering engaging in analysis in a more systematic way when I'm transcribing. I work with fairly 'large' interactional data sets and it is often helpful for me to NOT construct a Jeffersonian transcribe for all 300 hours, for instance. Rather, I create 300 hours of verbatim transcripts and then go through and carefully select segments that I will come back to and apply the Jeffersonian process too. This means that I'm making some pretty significant analytical decisions and I want to systematically document these. I've found that Transana allows me to do this in a way that is convenient for me. I view InqScribe as a transcription tool -- not useful for supporting the type of analysis decisions I describe above. However, I have other work where I may be transcribing 15 life narrative interviews, which will later be thematically analyzed. I would use InqScribe. First, I typically (in this case) create a verbatim transcript and then move to work within a package like ATLAS or NVivo. However, more recently, I've started just doing that type of transcription within ATLAS. In this way, the bulk of my research process is occurring within one package. It's a balancing act -- one which requires creativity and flexibility.
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What about moving across two packages? (e.g., Transana --- ATLAS.ti)
Sometimes it is needed and actually serves to support the research process. There are certain projects that will call for you to move across packages. I'll send you all a chapter in which I describe my own use (and rationale for it) across two packages. Part of this move to work across packages is grounded in the need to 'manipulate' the package to do what I (as the analyst) need it to do.
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Are there packages that support PDFs for literature reviews?
I would recommend exploring NVivo and/or ATLAS.ti. Both of these packages support PDF files and are quite useful packages for systematic literature reviews.
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How much space (in a paper) should one give to discussing how digital tools are being used within the research process?
This is a challenging issue. There has been SO little discussion in the qualitative community around what should be shared and why. I would argue that we need to share more than we typically have shared. Why? The process becomes more transparent when we make explicit how we used particular tools. For instance, rather than stating, "I used ATLAS.ti throughout," it would be more helpful to say what features were used. Perhaps there is minimal space or reason for sharing the details of a given feature, but as a reader and evaluator of what I'm reading I want to know what features were used (e.g., coding, memoing, etc.). In general, we've tended to do a decent job talking about the tools that support data collection; however, when discussing reflexivity (did we maintain an audio diary or a blog, for instance) and data analysis, there has been far less explicit discussion. One of the critiques of qualitative research is that the analysis occurs in a 'black box.' This is a fair critique. However, it is up to us as qualitative researchers to make explicit to others what happened in this 'box,' as we maintain a commitment to make the process transparent. Transparency and rigor are very much linked (and I would suggest ethical practice is central to the process, as ethics is made evident through transparent reporting).
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