Data security

Coding Qualitative Data: How Themes Get Made

Surveys and interviews are some of the best ways to conduct qualitative research. Researchers use these to establish rapport and manage the conversation with the participants. Yet, the research process does not end there. They will still have to sort and analyze everything to come up with logical conclusions.

In the absence of a numerical statistic, quantifying gathered information is almost impossible. Results are not definite without complex formulas and computations. For this reason, researchers have to maintain their credibility through coding. In this article, we will focus on the essence of coding qualitative research.

The Importance of Coding Qualitative Data

Coding plays a vital role in conducting qualitative research. You can code the data by labeling and organizing them to see common patterns and ideas.

In short, you can use words or phrases to assign codes and categorize your data. This process will help you come up with a more precise conclusion.

Below are some reasons why coding is a fundamental part of qualitative data analysis.

Coding Qualitative Research Makes Information Quantifiable

When analyzing qualitative data, you have to make the stakeholders believe in findings. You have to assure them of your output’s accuracy. It has to answer the question of whether it reflects the actual users’ behavior or needs and wants?

Coding qualitative data is as important as the numerical values in quantitative research. It can help you quantify and sort the messy scripts and responses in your open-ended surveys.

Codes can make your qualitative research more credible and appealing to your audience. With them, you can be confident about the truthfulness of your findings.

Coding Qualitative Research Creates Structure

While a structured interview determines appropriate questions, it does not ensure appropriate answers. Interviews and discussions don’t always turn out as expected. The flow of the conversation does not always run as planned. More often than not, it takes a surprising turn and gives way to more topics for exploration.

In short, these questions may address other aspects of the topic. Coding helps you organize the responses or scripts. You can pull them from the same code without going through the entire interview again.

A Brief Guide to Coding

Codes are words, phrases, or paragraphs that convey a similar meaning. They allow you to group scripts and responses in similar categories. You are free to choose codes and stick with them to maintain data consistency.

Familiar yourself with coding through the step-by-step guide below:

1. Identify Your Preferred Coding Method

You can code qualitative data by hand or by coding software. But, it’s important to choose first between deductive and inductive coding.

  • Deductive Coding

Deductive coding requires researchers to create and develop a predefined series of codes. You can do this before the actual data gathering. Codes are dependent on the identified questions and research framework. But, they can change as the analysis continues.

For example, you want to know why consumers dine in a specific restaurant. Your codes may include the price of the food, the quality of service, and the restaurant’s name. Once done, you will go through the data again and check if they are relevant to the codes you first created. They should reflect the structure of the data.

  • Inductive Coding

Researchers who know nothing or little about the topic always use inductive coding. They have to create codes from scratch since there are no preconceived ideas. In short, there are no predefined codes or codebooks. This method is best for exploratory research.

Both of these methods have advantages and disadvantages. But in reality, researchers often use them together depending on their objectives.

2. Initial Coding

This fast and easy process is also called the First Passing. You only have to check and familiarize yourself with the entire data. You may code sections with a broad code name. You don’t have to develop sophisticated ones since you may narrow them down in the next phase.

3. Line-by-Line Coding

This is when you have to analyze your data with a keen eye. From broad code names, you may start to narrow them down and work on more details. You may assign codes to everything, even if you will not take some of them into the final narrative. With that, you will have a more profound analysis as codes become more detailed.

4. Categorization

Your codes may remain broad and messy. For this reason, you have to group codes into similar categories and sub-categories. Move them around to find a structure that best fits your analysis. By sorting codes, consistent themes will emerge from your data and tell the story behind it.

5. Turn Themes into Final Narrative

Once they can reflect themes, you can take them into your final narrative. You can now tell the stories behind the information you have gathered. Hence, you can come up with credible findings.

Indeed, coding can be tiring at times. You will have to scrutinize your data and go through several time-consuming steps. Even so, it erases biases and assures the accuracy of your research. This increases your credibility in producing actionable findings.

A post by Kidal D. (5721 Posts)

Kidal D. is author at LeraBlog. The author's views are entirely their own and may not reflect the views and opinions of LeraBlog staff.