QDAS

I have NVivo, and am very happy with using it. It's a tool, and I'd no more worry about using it than about using a pencil or a spreadsheet. It has its limitations, but because it allows me to keep track of a mass of data, it saves me time and allows powerful analysis, keeping everything in one place.

Finding training on how to analysis qualitative data is more difficult than learning how to use software. There are training courses on QDAS that tell you what it does, but Gregorio tells you how to use it and how to do qualitative analysis - there's a difference.

---

Qualitative Research Design for Software Users Silvana Di Gregorio (Author), Judith Davidson (Author) 2009 978-0335225217 at Amazon

Saving time with Nvivo

Qualitative data analysis software can save time (Silverman) is my answer to Minh's assertion here that Word is so good. He writes some provocative blogs, worth reading.

I use NVivo 8 to store, search and retrieve interview text from 30 transcripts. After transcribing I code it against:

1. general codes - process, structure, climate, facts, queries (see Checkland). For a query, I create linked annotations as to what the query is about and how I might follow it up.
2. Metaphors, stories and anecdotes or words that strike me. For example, in one case study, participants used the word 'gel'. IN another type of organisation, people, more than once referred to "skin in the game". The shard use of the terms may indicate the culture.
3. the theoretical framework for engagement, covering aspects of communication and knowledge-ability: mutuality, negotiation of meaning, environment, expertise, contribution, participation and adaptation.

Having coded, I use the NVivo query function. I'll search for a code to draw together all the text that I'd coded under facets of engagement. For a particular case study, I query all the relevant transcripts and documents and emails, copy and pate them into a Word document and then draw on them as reminders and examples as I write the analysis.

Another query I use is text query - I've heard a particular phrase - "Who said it?" I ask myself and search all the files to find it.

I use memos to create:

• a to do list
• a coding journal
• thoughts on each case
• thoughts one each code
• key issues that arise

To develop theoretical aspects, I link from a source file to one of the memos, though I'm not very sure yet of the technicalities. I think cross linking will become more important as I move into cross case analysis. Then Nvivo should be of help in developing the theoretical aspects of my study.

Matrix queries then will be the next facility to experiment with to see what patterns I can find with certain attributes.

---

CHECKLAND, P. (1981) Systems thinking, systems practice.
SILVERMAN, D. (2005) Doing qualitative research : A practical handbook, London ; Thousand Oaks, Calif., Sage Publications.

Qualitative data analysis

I was talking with a fellow OUBS post grad about qualitative data analysis (QDAS). As she hadn't been using Nvivo, but Decision Explorer, she wanted to know if Nvivo would be more useful to her. We talked about its linking mechanisms, annotations and memos - those are what make NVivo really useful for me.

I demonstrated some of the ways I now work after doing that Silvana di Gregorio workshop.

• time stamp (Cntl shift T) - useful for journal
  
• memo for a coding journal
• right hand view instead of bottom view (view>detail view> right)
  
• Alt-F1 to remove / show left hand column
• creating and reading annotations
  

We received a manual at the workshop, which is very useful reference. Do the course to get the manual too. Silvana di Gregorio also writes books on QDAS as well as giving workshops.

The linking mechanisms are what make NVivo really useful for me. I annotate as I transcribe, or listen the first time to a transcription, or whenever. I use memos to link to collections of notes on facets of engagement, so I'm linking what I find in the cases with what I've found in the literature. This will help my later analysis as I write up the case studies for the dissertation.

Technology I use for research

Research uses technology:

• Microsoft Office (though I could use Open Office - it's Microsoft available on campus). I use Word for writing, reports, chapters and Excel for my plans.
• Phone - not Skype though
  
• Blogging software - this, and I have tried the OU's Assistive Publishing System (APS) to create an internal web site.
  
• NVivo for qualitative analysis
• SPSS for statistical analysis, though not much since I completed the Master in Research Methods.
• Virtual Private Network(VPN) - very useful for accessing my files on the server at the OU when I'm working at home
• microfiche - once for a PhD thesis that the library got hold of for me.
• Digital recording software - for recording data and playing it back
• Digital photography software - used to edit photographs for the poster I created for the competition.
  

Nvivo updated

I'm following Silvana di Gregorio's advice on anonymising my data in the analysis files so I shall soon be able to share the data with my supervisors, which will be interesting. I wonder if they'll look as closely at such electronic files as they do my writing.

I've also worked out how to attach memos to transcripts, but done so too enthusiastically as I hadn't realised where the links should be to annotations. Now I can annotate transcripts so each particular point that I want to comment on is linked to the particular annotation. It's really useful because as you read a transcript, ideas come to mind, ideas that may not require coding, but just thinking about and perhaps talking about with someone eventually, something to follow up later.

The other useful thing I've learned is to create an analysis journal under memos, with the time stamp against what I've done (cntrol shift T). This is useful to remind me how far I've got in anonymising, and what codes I might want to look at in future (like code against history or pre-conditions).

More Nvivo

We covered today:

• relationships
• hyperlinks
• models
• find
• queries

I've created a journal and I've restructured my database to catalogue my cases as cases. I'm all analysed out. My head is like an overfull sponge that needs some of its water wringing out before it can absorb any more.

Qualitative analysis & NVivo

We have a two day work shop on NVivo, and not how to use, but why to use it. It's proving very useful and interesting, and would have saved me three days of coding back in January if I'd known then what I learned today.

Next time I get a case study, my process will be:

• Transcribe - delegate
• Add time stamps
• Style. e.g. different styles for interviewer, interviewee, and questions related to my framework. Then autocode.
  
• Font - use a big font that's easy to read on a screen
• Anonymise so I can share with supervisors (will they want to look?)
• Import to NVivo
• Code

Coding will include importing as cases, which I couldn't get my head round earlier - I hope I can now. I will import cases, assign attributes and perhaps analyse relationships using the relationship node.

Nvivo coding

I was messing around on an Nvivo training course today and imported a photo as a practice. This is a rather boring photo of an office, not one I'd thought to use. But Nvivo has this little window for a description so I thought I'd fill it in. As I wrote I realised what else the photo showed me:

Notice the programme plan on the wall of this meeting room. This was a boundary object.

This is a week for finding boundary objects. The Nvivo project will include a code for boundary objects.

NVivo course

Have just attended first half day of Nvivo course. It's a big piece of software that takes time and space on your computer. No wonder when I first tried it, it was so slow. But the software might allow more efficient analysis of data.

Despite efficient software the thinking work is still essential, what codes to use, and then how to write it up. Supervisors yesterday were asking if I'd given a fair account of the first two case studies - well yes - but only in that it is my account and only on the data that I picked out as important. And I didn't use Nvivo on the data - that's yet to be done.

There's another day of training next week and some homework to do. The course has helped because now I understand what the nodes are about.

Isn't second year busy compared to first?! Cases to collect, transcription, courses, conferences, papers to write and the literature still to search!

NVivo difficulties

I'm trying to find out how to use this NVivo to record and code my thoughts on the literature review. It should be a good tool. After all, a literature review is a qualitative analysis, isn't it? But I can't work out the best way to use externals, create memos, link to the Word documents I already have written for reviews.

And there isn't an NVivo course till September, which is one I can't go on because it's the day after the BAM conference. So I have to wait longer to get the training, and carry on self-training - no problem because I've taught myself lots of technical programs for years.

Qualitative analysis

I've just realised that I could use NVivo, could have been using NVivo, to extract and analyse data from my literature review.

Why did no-one point that out before?

• Because supervisors don't need to know much about software and aren't going to point their students at it.
• Because there isn't training in using software, but training that is either about the product (e.g. Word, NVivo, Endnote) or about the process, and not how to integrate the two.

The best integration the OU has provided in the last two years was through the Professional Academic Communication in English sessions (PACE) when one of the lecturers explained how she'd used Endnote to keep notes and print them off or insert them in Word.

Here are slides that discuss the training issue, from the 2006 ESRC research methods festival. And here's a paper from Silvana di Gregorio on using NVivo to analyse literature for the review. And here's a discussion on qualitative data analysis.

Data analysis & using NVivo

Third year student, Linda Wilks, presented on the role of habitus in festivals. That was interesting but of greater relevance and use to us students was her explanation of how she analysed her qualitative data. Here's what:

Recording the interviews

• Assess background noise
• Put your recorder on something soft

One of my colleagues had problems transcribing an important word when the interviewee spoke as he put his coffee mug down.

Transcription

• Use a foot pedal
  
• Contract some of it out but expect to have to check it thoroughly yourself too. Cost is £11 per hour of their time.
• Takes approx 7 hours to do 45 minutes

I thought this useful & practical. But it got more useful because she talked about organising the data to make it manageable by:

1. Designing a data classification system
• Based on research theory
• Related to interview questions
• Be prepared to modify it
• Transfer into NVivo under ‘tree nodes’
  


2. Import your transcripts into NVivo
• Highlight sections of the transcript and drag into the appropriate tree node


3. Export the tree node contents
• Make sure you tell NVivo to include the folder and hierarchical name
  

She gave us a screen dump of NVivo with nodes and folders and hierarchies. She explained with examples of sources and numbers of references in the nodes, and an analysed transcript.

• To get an idea of the important areas, assess how many references a node has.
• Print out tree nodes for analysis.

For the second level of analysis, she used Fairclough's critical discourse analysis and justified the use in relation to her work.

She had a check list to scribble on her texts, for example what styles, types of statement, intertextuality and transferred the notes to a spreadsheet.

The final step is to write up findings, without reference to theory at this stage and no language that precludes conclusions.

What I've noted above is all Linda's work, and if you want to know the detail you should contact her. I'm going to get NVivo and practise on my MRes data, and I'm going to look up Fairclough.