DRS2012 Bangkok Proceedings Vol 4 - Design Research Society

2108 Conference Proceedings
Designing New Meanings: A Design Method for Eating Design
analysed the data from the users sample, and once finished, I have analysed the data
from the interpreters sample.
The analysis was conducted on the transcription of the discussion of each session from
both days. Each phase of the analysis was conducted on the following data items:
transcription of Day 1 (session 1 to 5) and transcription of Day 2 (session 1 to 5).
Familiarizing with the data. The recorded dialogues were transcribed by a company of
professional transcribers. Before starting the analysis the transcripts were checked back
against the original recordings for accuracy. Comparing the recording with the text was
useful to start familiarizing with the data.
Generating initial codes. In this phase initial codes were produced from the data. The
transcriptions were read and each extract considered of interest was coded organizing
the data into meaningful groups (Tuckett, 2005). Codes are features of the data that
appear interesting to the researcher, and refer to the row information that the researcher
assesses in a meaningful way regarding the phenomenon investigated (Boyatzis, 1998,
p. 63).
Searching for themes. For this phase Braun and Clarke (2006, pp. 89-90) instruct to
combine different codes into broader potential themes, and to essentially start analyzing
the codes trying to understand how different codes may combine to create overarching
themes. Nvivo allows to create a hierarchy of tree nodes, where main nodes contain subnodes.
When combining sub-nodes together under the same node, six main nodes that reflected
the six main topics of conversation were created: Companion, Others, Service, Food,
Environment, More. The last main node ‘More’, groups those nodes that did not
specifically refer to one of the other five topics, and that freely emerged from the
conversation.
Reviewing themes. In this phase Braun and Clarke (2006, pp. 91-92) propose two
different steps. In the first step the analyst should review all the data extracts for each
node and consider whether they are coherent to each other and to the node itself. In the
second step I read again the entire data set in order to consider individual nodes in
relation to the entire data set, and whether the final nodes reflect the data set as a whole.
Defining and naming themes. This final phase I consider being described more in detail
by Ritchie et al. (2003, pp. 237-244). They describe the three key steps being: detection,
categorization and classification. Throughout these steps the extract is interpreted on
different levels of abstraction creating in the end the final themes.
Themes
The result of the analysis of the two sets of data resulted in two different groups of
themes: a group of themes produced from the analysis of the users’ discussion, and a
group of themes produced form the analysis of the interpreters’ discussion.
THEMES FROM USERS SAMPLE THEMES FROM INTERPRETERS SAMPLE
People connections
Mirroring
Discovery/Curiosity
Observing/Curiosity
People connection
Mirroring
Discovery/Curiosity
Observing/Curiosity
Focus on food