![]() ![]() ![]() If you are analyzing survey responses for people's preferences for shopping in brick-and-mortar stores and shopping online, you might think about marking each survey response as either "prefers shopping in-person" or "prefers shopping online." Once you have applied the relevant codes to each survey response, you can compare the frequencies of both codes to determine where the population as a whole stands on the subject.Īmong other things, codes can be analyzed by their frequency or their connection to other codes (which ATLAS.ti calls co-occurrence). Think of a simple example to illustrate the importance of analyzing codes. On the other hand, a reader can examine a fully coded project and get a sense of the main points of the data by looking at the margin of the document. Without codes, another reader would need to read all of the text to determine a particular meaning that the researcher has already interpreted. Taking a look at the example above, a set of three paragraphs is represented by one code, which is displayed in green in the right margin. Understanding what codes are supposed to do, a researcher then looks at the data line-by-line and develops a codebook by identifying data segments that can be represented by words or short phrases. While a strictly numerical understanding of qualitative research may overlook the finer aspects of social phenomena, researchers ultimately benefit from an analysis of the frequency of codes, combinations of codes, and patterns of codes that can contribute to theory generation. Naturally, if such visualizations rely on tables and figures like bar charts and diagrams to convey meaning, researchers need to find ways to "count" the data along established data points, which is a role that coding can fulfill. Moreover, such narratives might be too lengthy to grasp when the objective is to reach a consensus on valuable insights.Īs a result, researchers in all fields tend to rely on data visualizations to illustrate their data analysis. When presenting qualitative research to an audience, a narrative summary of the data alone lacks the analytical process that is inherent to establishing research rigor. The use of codes has a purpose beyond simply establishing a convenient means to draw meaning from the data. Coding allows a reader to get to the information they are looking for to facilitate the analysis process. Now, with two ways to organize the data in front of you, you can look at all of the ingredients sections of all the recipes belonging to a cuisine to get a sense of the items that are commonly used for such recipes.Īs illustrated in this example, one reason someone might apply sticky notes to a recipe is to help the reader save time in getting the desired information from that text, which is essentially the goal of qualitative coding. Now, suppose you have different colors of sticky notes, where each color denotes a particular cuisine (e.g., Italian, Chinese, vegetarian). Imagine applying a couple of sticky notes to a collection of recipes, marking each section with short labels like "ingredients," "directions," and "advice." Afterward, someone can page through those recipes and easily locate the section they are looking for thanks to those sticky notes. What is a code?Ī code in the context of qualitative data analysis is a summary of a larger segment of text. Coding provides a way to make the meaning of the data clear to you and to your research audience. Qualitative coding is a necessary process before researchers can engage in the qualitative data analysis process. Unlike quantitative data, unstructured data for qualitative research requires not only reorganization but a reflection on what the data means in the first place. Until this process, raw data in qualitative research is essentially meaningless data, at least from the viewpoint of empirically generating knowledge. In qualitative research, one of the goals prior to data analysis is to identify what information is important, find that information, and sort that information in a way that makes it easy for you to come to a decision. The information that go into choosing the "best" hotel can be located in various and separate places (e.g., travel websites, blogs, personal conversations) and scattered among information that may not be relevant to you. Suppose you need to determine the most important aspects for deciding what hotel to stay in when you go on vacation. Qualitative research tends to work with unstructured data that is either unorganized or organized in a way that is not useful to your research inquiry. ![]()
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