This was an odd experience for me, I had lost my voice so was not able to speak any contributions to the workshop…only type! This meant I had to be very succinct about what I said but also realised how long it takes me to type things out. It also made me reflect on how much I was able to actually contribute when only typing. Something to think about for future online sessions with students…

I found this session really useful. I hadn’t started any of my data analysis yet. I had the data in raw interview form but had not even transcribed it yet. It was really fun to try out different methodologies of analysis without the pressure of using your own data set,how they work in practice and question my understandings of them.

We started by practically looking at semiotic analysis- the study of signs and symbols and their use or interpretation.We looked at images associated with ideas of a researcher.

https://miro.com/app/board/o9J_luxM8D4=/

It was really interesting to see the groups assumptions on what a researcher should be/do. Mine have defiantly altered since undertaking this SIP. I come from an art and a science background so sometimes there is synergy but other times the different schools of thought do not align. The last time I carried out research it was science based. My science head is more rigid and facts based whereas my art head wants to explore experience. Hopefully my project will capture both and my two heads wont contradict each other or be counter productive!

Data poetry was an interesting exercise. I liked the limitations of only using words there and having to use the order of speech. It was amazing to see how different people’s interpretations/stances/takes on reading the same thing, and what they chose to illuminate or bring to attention. It really highlighted to me how the researcher is so pivotal in how data is analysed and presented back.

Searching for themes was another really useful exercise. It is an area of analysis which I had already identified as something I would probably do with my data.

We were asked to read something and analyse our

assumptions about the data and positioning

initial observations, responses, insights

reflect on assumptions

then code transcripts

This was interesting to me as it thew up some of the things I was thinking about with my analysis of my transcripts and how I might interpret things. It also gave me a good idea of how to approach thematic analysis in general.

I found the exercise of breaking everything down into 5 sentences very difficult! I know this is something I will struggle with- streamlining what I need to say about my project. I’m so invested and in the thick of it I worry about the balance of saying enough and getting the points across in a way that someone who is new to the project will grasp with ease.

After the session I knew I needed to research thematic analysis further. I listened to the talk by Braun and Clarke about their new book. It was very informative, but it did send me down a further thematic analysis rabbit hole about the nuances between different types of thematic analysis, how they are used and when to use them.

I found this page quite helpful in breaking it down

https://medium.com/usabilitygeek/thematic-analysis-in-hci-57edae583ca9

I will start by:

underlining, marking and highlighting important parts (coding)

see which important ideas recurr (temporary consrtucts)

elimination of temporary constructs that do not seem to be re-enforced in rest of data, however keep separate list as they may form counter examples

come up with second order constructs that make good fit with the data- then refine these—-these will become your themes and sub-themes.

It was advised we re-visit our aims, assumptions, beliefs and practices, to think about and critically revise them once we have analysed the data.