Qualitative coding

Coding is a way of indexing or categorizing the text in order to establish a framework of thematic ideas about it | Gibbs (2007).

In qualitative research, coding is “how you define what the data you are analysing are about” (Gibbs, 2007). Coding is a process of identifying a passage in the text or other data items (photograph, image), searching and identifying concepts and finding relations between them. Therefore, coding is not just labeling; it is linking of data to the research idea and back to other data...

The codes which are applied enable you to organise data so you can examine and analyse them in a structured way, e.g. by examining relationships between codes.

Approaches to coding qualitative data

A basic division between coding approaches is concept-driven coding versus data-driven coding (or open coding). You may approach the data with a developed system of codes and look for concepts/ideas in the text (concept-driven approach) or you can look for ideas/concepts in the text without a preceding conceptualisation and let the text speak for itself (data-driven coding). Investigators can either use a predetermined coding scheme or review the initial responses or observations to construct a coding scheme based on major categories that emerge.

Both methods require initial and thorough readings of your data and writing down which patterns or themes you notice. A researcher usually identifies several passages of the text that share the same code, i.e. an expression for a shared concept.

An example

A code in a qualitative inquiry is most often a word or short phrase. In the table below an example (Saldaña, 2013) is given.

	Raw data	Preliminary codes	Final code
	The closer I get to “retirement age” the faster I want it to happen. I’m not even 55 yet and I would give anything to retire now. But there’s a mortgage to pay off and still a lot more to sock away in savings before I can even think of it. I keep playing the lottery, though, in hopes of dreams of early winning those millions. No retirement luck yet.	* retirement age* financial obligations dreams of early retirement	RETIREMENT ANXIETY

Expert tips

Any researcher who wishes to become proficient at doing qualitative analysis must learn to code well and easily. The excellence of the research rests in large part on the excellence of the coding | Strauss (1987).

Tip 1: Document the meaning of codes

The meaning of codes must be documented in a separate file. Make short descriptions of the meaning of each code. It is helpful to you and also to other researchers who will have access to your data/analysis. What you need to know about your codes (Gibbs 2007):

the label or name of the code
who coded it (name of the researcher/coder)
the date when the coding was done/changed
definition of the code; a description of the concept it refers to
information about the relationship of the code to other codes you are working with during the analysis.

Tip 2: Prevent coder variance

Coding textual information is a complicated cognitive process and the coder is necessarily a significant influence on the coding process. For each study coding procedures must be carefully planned and a specific coding design and guidelines must be established. Coders must undertake a training, where they are instructed about the specific coding design and coding rules. A part of coding procedures is concerned with reviewing the quality of the coding process. According to Gibbs (2007) several techniques to control coder reliability exist:

Checking the transcription
An independent researcher goes through coded texts and considers the degree to which coders differed from each other.
Checking for definitional drift in coding
If you code a large dataset the data at the beginning may be coded slightly different than material coded later. Check the the whole dataset for the definitional drift. Have good notes with descriptions of individual codes.
Working in a team
If there are multiple people working in a team, individual members can check each other´s coding.

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