Setting the Scene:
You are a postgraduate student, and you have some data for your thesis. Maybe you started to read about ‘Data Analysis’ but are realising data are messy, complex and sticky. Maybe you even started your ‘analysis’ but dug down into a rabbit hole that has left you dazed and confused. Or, you have done some ‘writing up’ and need feedback on your analysis! If any of these scenarios sound familiar, this ‘mini-course’ may be for you.
What:
The purpose of this ‘mini-course’ is to work with doctoral students on analysing their qualitative data. We provide readings, tasks, feedback and guidance on how to analyse data and write up your results.
Who:
We’ll bring together 20 postgraduate students and their qualitative data for exciting collaboration. We are two faculty members at the University of Strathclyde. We have expertise in qualitative analysis, lots of enthusiasm for research design, and we want to share this joy with you!
How:
The mini-course meets on two Fridays and one Saturday – with morning and afternoon sessions (2.5 hours each). We’ll teach about, engage with and conduct qualitative data analysis. We’ll use course readings, in-class activities, homework tasks and provide guiding feedback.
Why:
We know the doctoral process can be lonely. We also know there are few opportunities to learn how to conduct qualitative data analysis. We aim to develop an interdisciplinary culture that works to do qualitative analysis, using a collaborative approach with guidance from peers and mentors.
Please note: All participants must be doctoral students who have collected data from their thesis.
Session 1: Friday 06 May, 10am-4pm (in person, University of Strathclyde)
Curiosity and Expanding Inquiries
- Modes of thinking analytically about data
- How to move beyond data in order to focus with data
Organising Data and ‘Glows’ in Data
- Preparing the data in order to think critically
- Reading data as the first form of analysing data
Session 2: Saturday 14 May, 10am-4pm (in person, University of Strathclyde)
(De)Coding and (De)Categorizing Data
- The techniques of ‘tagging’ data to make sense of what’s happening
- How to (un)tag data in order to move forward with your arguments
Diagramming and Unpacking Glows
- Mapping and making connections between data, literature and theory
- Unpacking the meaning behind connections to develop stories
Session 3: Friday 20 May, 10am-4pm (in person, University of Strathclyde)
Writing and (non)representation
- How to write up data ethically to (re-)present our findings
- Ways in which we make our work public
Reflexivity
- Making our work significant whilst remaining humble