Open-ended questions are ubiquitous in qualitative research; they allow respondents to express their thoughts without the confines of scales and answer lists. Open ends facilitate an understanding of details that could easily be overlooked through strictly closed-ended questioning by helping researchers understand not just ‘what’ but ‘why’
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.
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:
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.
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.
To learn more about the power of AI in coding check out this link describing My-Take’s new coding technology.
Taylor was a Community & Insights Manager at My-Take, focused on helping clients gain valuable information through online insight and advisory communities. She delivered actionable quantitative and qualitative feedback to key stakeholders to help drive internal decisions.