Coding research data
Coding is a method to interpret qualitative data. After an interview, a giant corpus of text can be unwieldy. To manage this, it is common for researchers to ‘code’ their responses so that they can get an overview (or a meta-view) of the responses. This overview can often (with many caveats) be converted to quantitative data. For example, counting the number of positive responses. Coding requires interpretation, and can be quite subjective, so it is important to have a clear protocol for coding. Once these data has been coded, they can be categorised and converted into themes and theories.
Example applications
In my doctoral thesis, I asked about 1,000 university students to visually graph an integral, given a known rate of change. The case study used carbon in the atmosphere as the context. Students were given a graph of the greenhouse gas emissions per year, and were asked to graph the the corresponding accumulation, and write a written description. The graphical results were coded into five categories, using a stencil that showed the upper and lower bounds of a category (correct, decrease, stabilise, increase, other). This coding scheme allowed for me to quantify the frequency of different answers.
Steps
There are many reasons to engage with a coding process, but once you have collected the data, a general approach should include:
- pre-coding - getting a sense of the data by looking for codable opportunities
- preliminary coding - developing the schema
-
code contrasting data - look for extreme cases (such as other researcher’s data) to see if your coding scheme holds up. It’s worthwhile discussing the schema
- decide on the lumping chunk-size - do you code everything, or just the key observations?
- finalise the code list - establish the rules for coding so that others can replicate your approach
Key concepts
- an overview of what coding is, in which situations it should be used, and the development of a
coding scheme
- example of a coding activity, that develops into the categorisation of codes
- advice to the student engineer on how to approach an activity that requires coding (such as interpreting an open-ended survey question)
Core resources
For a comprehensive guide on what coding is, how to undertake coding, and things to watch out for, see Salda 2012: