We are all aware of the benefits of team working – more thoughts and ideas, a chance for smaller thoughts to grow and develop into big ideas with the help contributions from others. But what does this look like in practice, and how is it acted out in the workplace? It requires mutual recognition of every team player’s opinion being as valuable as the idea you are bringing to the table. The best work is produced through many thoughtful stages of corrections, making changes each time in an attempt to add quality. At first it may seem time consuming and it may feel like there’s a lot of unnecessary shuttling taking place (going forwards and backwards refining different parts of the same idea) but the effort is definitely apparent in the end product. These processes are core to collaborative writing and I think doing so is a good way to achieve exceptional results.
So, during the Departmental Conference, I particularly enjoyed the seminar by a representative of the James Lind Alliance, an organisation that I was previously unaware of. In a way they have been taking a niche approach and have turned the tables around when considering the formulation of research areas and topics. Continue reading
On the 15th November I attended the first of a two part course on the qualitative analysis aid software NVivo9. I hadn’t used the software before and I thought that it would be worth finding out how it could help me to organise my data for analysis. After conducting some more interviews, I was looking for a tool that could facilitate the analysis of my interview transcripts. On first glance, the ‘dashboard’ didn’t appear to be quite as confusing as I thought it would be, with elements such as the Ribbon toolbar reminding me of parts of Microsoft Office:
By the end of the day, I had learned the basics on how to code data (or assign category labels to texts that with enable similar comments by interviewees to be grouped together) using ‘Nodes’ on a ficticious dataset, and how to query the dataset (asking the software to display certain data based on specific characteristics chosen by the user). As is the case with most computer software, it is only as useful the user makes it and NVivo9 is simply a tool to help you with your anaylsis – it will not do any analysing for you!
I’m now in the process of applying the same techniques to my own interview data ahead of the next session so that I have real data to work with during the training.
I spent this week reading through research protocol and sifting through other relevant documentation to get gain an understand of project. Note-making (on paper, not a pc!) seems to work best for me as a way of engaging with text over long periods of reading. I like to use flow/diagrams that show the development of my understandings of the content, with questions and quotations on the diagram periphery. The questions are useful to feedback to my line manager.
Below is a link to one of my diagrams: