Process 5-7: Analysis of data from fieldwork
To look at the data generated from our fieldwork and secondary case studies, we have followed six steps:
1 – Decide on filters to look at the data: These filters derived from our research questions and highlighted enablers and barriers to our theme.
2 – Colour coding: It allowed us to identify where each of the three filters could be found in the data. We have started this process together in one evening session but due to time constraints, our coding proceeded independently. Each one of us colour-coded in printed out transcripts, fieldnotes and case studies. After the coding was done we cut out each code in preparation for the next phase of our analysis.
3 – Creating clusters: For this, we have used our cut-out codes and applied the principles of Affinity Mapping to create groups of similar information, and revisit these groups as we progressed in the analysis towards the creation of final clusters.
We started the clustering process individually and followed it with group discussions to revisit our clusters and make adjustments. This allowed us to get familiar with other people’s codes. At times, to the same text passages, each of us assigned different codes, which was a useful way to become aware and discuss the overlaps between our data clusters.
4 – Naming the clusters: By naming the clusters we have also identified crossovers between our three data filters, highlighting the consistency to our body of data.
5 – Linking the cluster to key descriptors of our theme: Here, we connected our data to our initial theme. We have highlighted two key descriptors for ‘Being Yourself at Work’:
– Descriptor A: Being professional and caring at work;
– Descriptor B: Recognising that each young person needs different approaches to meet their needs fully and move forward.
6 – Choose key clusters to take to the ideation phase: This stage of the process allowed us to start sorting our interest areas to take to the ideation phase. Our prioritisation was made based on the team’s perception of what was relevant for our theme, and the team’s intrinsic motivation regarding the direction we wanted their project to take. We wanted to focus on developing ideas for Corporate Parents so that the young people could experience love, as shown in the results from the first round of research. Based on our analysis we chose the three clusters defined below: Mindset, Language, Personalising support for young people.
See in the image, the connections we have made between our data clusters, our three filters and the key descriptors of our theme.
Our next step was to define each cluster and choose one lens to take for ideation.