Coding is the process of grouping together open-ended responses based on similar words, sentiments, or ideas. Coding enables researchers to quantify data obtained from open-ended questions and identify top themes.
The Different Types Of Coding
Researchers can utilize a variety of coding concepts to make sense of open-ended data. Coding concepts are the filters through which a researcher assigns codes.
Two common concepts include:
- In Vivo Coding: Uses direct words or phrases quoted from participants to create codes. These codes are rooted in the voice of the participant.
- Descriptive Coding: Uses the basic topic or summary of responses to create codes. These codes are rooted in top-level themes.
Other coding concepts include process coding (“-ing” words), versus coding (binary terms) and many, many more. Regardless of the concept used, it’s important to note that coding is subjective; codes will naturally vary based on the researcher’s interpretation of a response.
How Artificial Intelligence (AI) Will Impact Coding
Coding has historically been a manual process; humans read the data, create the codes, and combine responses to produce top themes. As artificial intelligence infiltrates more and more of the modern world, researchers may be left wondering - how will AI impact coding?
AI, in short, will speed up the coding process. It can read responses and apply codes in a fraction of the time taken by traditional methods. With the help of market researchers, AI will learn which words or phrases trigger each code and apply those learnings to future studies.
Written expression is complex, and as such there will always be a place for humans in the coding process. Humans will continue to captain code creation and steer code composition while AI accelerates the process.
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