100,999 words of transcripts…

The draft prologue, abstract, Chapter 1: Introduction, Chapter 2: Literature Review, Chapter 3: Methods and Data, Chapter 4: Survey Findings as well as related appendices are now in “ok draft shape” and have been reviewed by my supervisors and colleagues who kindly read earlier drafts, sections and subsections. I am also updating my growing acknowledgement section and am continuing checking new research that is released so that it can inform my literature review if relevant.

I have found the ongoing dialogue around my research extremely valuable and it has also helped me to identify gaps or holes I should say in my own understanding and my personals struggle with theory… the methods chapter was particularly painful and I am sure it is not over yet. As I have all my data now from both cases, I am now focusing on the analysis of the main data collected through the phenomenographic interviews. All 22 of them and there are 100,999 words in total. I need to code all of it, every single phrase. You see, in phenomenography you code everything and while this seems to be a very inclusive qualitative research process, as all variations of experiences are getting voiced, it is also a very messy process I have found so far. I have currently doubts that what I am doing is leading me anywhere… However, yesterday, while finishing a presentation for a forthcoming talk (thank you Sue for looking at this) and looking back at earlier drafts and  preparatory work within the presentation, on the ipad, on phone and in a Word document, I can now see how the final presentation has emerged through synthesising all these thoughts I had. That presentation is now much more stable and I feel so much happier about it… still very nervous though…

Hopefully I will make good progress with the data analysis and reach a stage where I can just look at the data and how I organised it and it makes sense to me and others. I have a long way to go until then…


trying to… (source)

My challenge is that I am not just familiarising myself with the methodology and applying it but also with the data analysis tool. This is NVivo and while I am making some progress and can do the very basics, I still struggle. Not giving up. I will keep going and hopefully discover some useful shortcuts along the way and make progress with the analysis too.


image source here

Looking at the first attempts to analyse the data, I notice a change in my approach. Maybe this is a result of a short conversation I had yesterday with a colleague. While until yesterday, I had themes and categories. I decided this morning to delete all themes and go with categories at this stage which I can later group together into themes. I hope I am doing the right thing… There are around 30 categories (not categories of description yet!!!) at the moment… far too many, I think. The plan is to get all the transcripts coded by the end of the weekend. Yes, I have work to do ;). Reading the transcripts all together and doing the coding, however, really helps me get into the data. I just wish I could do this until I am done. Doing a bit and then nothing for days, is hard. I have found that I need a lot of time getting back into it after a break… and working in the evening when my brain is dead doesn’t seem to be productive either. Anyway.

Some observations from today so far based on the transcripts: One of participants’ key motivation to participate seems to be to use new technologies and get ideas how to enhance their practices. They could of course do this on their own without joining an (open) course. However, what they also say is that they are keen to connect with others and especially from other countries and cultures. This seemed to be more important that just connecting with colleagues in other disciplines or institutions. They recognise that they have limited time and that the motivation of those working for credits might be increased, but are keen to be involved and get loads out of the interactions with others, especially when learning in small groups. Learning within a group was their choice. They also valued the support by facilitators. Coming together as group members was speeded up by organising synchronous get-togethers via Google hangout where they could see each other. This really helped them get to know each other and seems to increase commitment to the group. But not all could make. It is interesting what some say that they established much closer relationship when working in these small groups (but not surprising) and others who didn’t join a group note that they recognise that they would have that opportunity if they had joined a group. However, not everybody wanted to join a group and some found the resources really useful and the related activities and the community based conversations. The literature was useful for many but not all engaged with it. Some suggested to use them more in the groups. While for some creating a product as a result of the collaborative learning process was seen as valuable, others said that this didn’t really work and would prefer to support each other in a different way. The short activity-based videos and other activities are mentioned a lot also by a participant who had learning difficulties. This is something to think about when designing activities and making resources available in alternative formats. Feedback also featured in the transcripts I read through and while there were positive comments regarding these, some mentioned that they felt a bit superficial at times.

While the courses were developed and/or offered with universities from other countries, the course language was English. Participants whose native language was English seem to be aware of and sensitive to the challenges this might cause non-English native speaking participants. The interviews do confirm that some of the international participants had real confidence issues with using English in the courses and this in some cases hindered some aspects of their participation. It was fascinating to find out what participants said about other participants. Empathy features in their descriptions of their experiences as well as that they were annoyed by specific behaviour.

Back to some more coding now…




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