Research commonly includes various approaches to work with data and the choice of suitable strategy based on a study’s purpose. For qualitative information, coding is one of the most valuable ways to gather coincidences and make detailed observations. As qualitative data is unstructured and non-numerical, coding is utilized to identify concepts, tendencies, and general similarities in research (Belotto, 2018). The process includes the components’ discretion and labeling the items based on their characteristics (Belotto, 2018). Qualitative data coding example is the participants’ survey forms analysis that includes separating their responses by citizenship, gender, education, and other unstructured information.
Qualitative data coding can be applied for labeling or group information, and the outcomes might influence research differently depending on the selected strategy. The approach can be inductive and deductive, and both of the tactics include the essential coding process. Chandra and Shang (2019) state that “inductive coding refers to a data analysis process whereby the researcher reads and interprets raw textual data to develop concepts, themes or a process model through interpretations based on data” (p. 94). The deductive process works in reverse: it analyzes the information by applying the already existing set of codes to test a hypothesis (Azungah, 2018). Qualitative research can benefit from both coding approaches, as they deepen the analysis and become a foundation for further studies and new theories.
The distinguishing factors between inductive and deductive coding are based on how the process initiates. In the inductive approach, information is being analyzed to notice patterns and specific details to generate further research theories (Azungah, 2018). The deductive strategy is the opposite because the qualitative data is coded based on the existing hypothesis and should result in submitting or refuting a statement (Azungah, 2018). Indeed, the choice between the two types of coding depends on a theory’s existence to test or demand for developing one.
References
Azungah, T. (2018). Qualitative research: deductive and inductive approaches to data analysis. Qualitative Research Journal, 18(4), 383-400.
Belotto, M. J. (2018). Data analysis methods for qualitative research: Managing the challenges of coding, interrater reliability, and thematic analysis. Qualitative Report, 23(11), 2622-2633.
Chandra Y., Shang L. (2019) Inductive coding. In: Qualitative Research Using R: A Systematic Approach, 91-106. Springer, Singapore.