![]() ![]() This iterative process is especially important when coding inductively and/or in teams as it will build efficiency by minimizing the maintenance of codes that are unnecessary, redundant, and overly specific/idiosyncratic and help inform the building of a manageable and effective code system. Doing so will help you decide which preliminary codes deserve to be in your codebook, which preliminary codes can collapse into one overarching code, and so on. When you begin coding, code a portion of your data, such as an interview, and pause the process to assess the codes you have developed and/or applied. Do this thoughtfully and thoroughly enough, however, and you may be rewarded with a code system that stabilize as you develop enough codes to capture all the important content you find in your qualitative data to address your questions.This is the messy and wonderful world of qualitative research methods as it can be tricky to map the ‘academic’ concepts we have in our heads to the very real-world data we collect. However, people in natural ways use their own rich and varied language in how they communicate with us during our research. Remember, it is easy to come up with nice dictionary definitions for the codes we think we will be using. This is a simple example of the kinds of questions we should be asking as we develop guidelines for how our codes are defined and the criteria we will use to decide if they are to be applied or not.Ī rule book, or code book, should evolve as themes develop and we then keep testing and modifying the rules as we explore if the codes will be useful for all the kinds of data we collect from our participants. What if others say they sometimes do these activities at home and sometimes they do them in a temple? What if we see this in the reports of the first three of our participants, but none of the other 50 people talk at all about religious rituals engaged in at home? įor example, say we come up with a code called ‘religiosity’ and define its use to ‘tag the stuff people tell us about religious rituals they engage in at home each day.’ But what if some people say they only do these activities 5 days a week? until we have something that everyone on our team can consistently apply to the data in our project and capture something meaningful across our research data that speaks to our research questions!. Code viability is then developed through an iterative process of hypothesis generation, hypothesis testing, modification, reconsidering, re-testing.This is also referred to as inductive coding. ' in Vivo' or'Emic'-codes are more emergent in nature as they are inspired by what is found directly in the data and help us see and understand things we did not anticipate. ![]() This is also referred to as deductive coding.
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