The technological innovations that have arisen from the global impacts brought by the Digital Era have changed the way industries and individuals operate on a daily basis. One of those changes is in the growth of the skill of coding. This skill is the beginning and ending of every computerized, digital task that occurs, from phone usage to internet data compilation.
Everything begins as a group of characters formatted as a code, and in the field of research, coding turns qualitative measures into numbers. This allows a program to compile data, and that data is then used to apply a judgmental scale rating on the researchers. Because of the importance of those numbers and how it affects reputation and article impact, researchers need to understand as quickly as possible how coding is related to their work.
What is Coding in Relation to Science?
Coding has a place in science in every field of research, but it is especially evident in qualitative findings. Using coding, researchers are able to analyze their data and break it down into new, unexplored results. Through this skill, qualitative text data is analyzed in multiple ways, then put back together in results that make sense in the context of the research in question.
Still, the idea of coding generates a lot of confusion, especially to early career researchers. Coding is, in part, a field that is navigated through self-taught measures as research is implemented. As data is collected, researchers make decisions as to how to use it in their research. Through trial and error and a miasma of different programs trudged through, scholars eventually learn how to use coding to best get their data from qualitative findings into quantitative numbers. Coding is necessary because text can be cumbersome and difficult to sift through until the information makes sense. Through coding, researchers are able to index the data into a map or tagged grouping that takes the reader straight to a relevant point. Coding is therefore used for things like indexing, labeling, and theory and understanding of ideas.
Redesigning Academic Articles to Enhance Coding
As you perform your research, you’ll come across times when coding is necessary. Redesigning how you record your data can help you to enhance coding as an integral, common aspect of your procedures, especially when you use coding software like NVivo or MaxQDA. Using software specifically designed to turn qualitative findings into numbers makes it a simple, seamless part of your research steps.
This software can be structured to help you to develop sets of codes in simple through complex scopes, arrange the data collected around a specific category, or layer it all together. If you have a specific question, the codes can sift through the data and find the data that will help you extrapolate the information obtained to determine your answer. You will only need to sort through and decide how much data is relevant to your topic. This requires significant determination of the right keywords to limit your search but also keep it wide enough to bring in a large enough net of information to help you see the bigger picture, if one exists.
The use of software does limit the researcher’s understanding of how to code, simplifying the process for them. This can be a problem in inhibiting the scholar’s ability to see a large-scale view of what the data is and what’s occurring in the breakdown of it. By learning coding itself, the researcher learns what they are capable of procuring and how to conceptualize what is possible.
Whether you want to learn the full aspect of how to code or use the skill to streamline your data, coding will be an essential part of turning your qualitative research into numerical numbers to show in your research.