Question: How will you go about making sense of your data?
Once I have all of my data collected, I will need to start going through and organizing it to arrive at my findings. “Data is the information you collect as part of your research study” (Lichtman, 2013). According to Lichtman (2013), as you go through your data, you want to look for key concepts: “Key concepts are derived from the data through a process of coding, sifting, sorting, and identifying themes.” By following a process of coding and looking for themes, you can begin to make sense of your data.
By constructing your categories or themes, a researcher can begin to see patterns and these will begin to frame the study’s findings (Merriam & Tisdell, 2009). So how do you go about finding your themes or concepts? Lichtman (2013) lists three Cs of analysis, from Coding to Categorizing to Concepts, and suggests following six steps to go through that process:
Step 1. Initial coding. Going from responses to summary ideas of the responses
Step 2. Revisiting initial coding
Step 3. Developing an initial list of categories
Step 4. Modifying initial list based on additional rereading
Step 5. Revisiting your categories and subcategories
Step 6. Moving from categories to concepts
The concepts you come up with in Step 6 will turn into your research findings.
Penn (2012) lists 5 different ways a researcher can look at a pile of data in order to make sense of it. Asking these questions helps to give the researcher more insights into what the data is trying to say:
Question 1: Can it be grouped?
Clustering it together in logical groupings can sometimes be helpful for generating insight.
Question 2: Can it be split?
If your data is not yielding any obvious answers at first glance, perhaps it can be split up into smaller pieces, e.g., by smaller pieces of time or smaller subject.
Question 3: Can it be converted into rates? Rates can show trends that absolute data obscures.
Question 4: Can it be charted?
Most people simply can’t visualize data in their heads without assistance, so charts can be used to lay it out in some kind of visual form.
Question 5: Is it related?
Given two sets of data, are they related? If so, what is the strength and nature of that relationship? (Penn, 2012)
I think if I follow these suggestions when organizing my data, I will be able to pull out themes and make sense of what the data is telling me. I would then look back at my research questions and see if my data answers those questions. If it doesn’t, then I would look at the data I have and ask myself why it doesn’t answer my questions. It could be that it does, but I haven’t organized it correctly.
My study isn’t too complicated, so I think if I follow the above steps to organize and summarize my data, it will answer my research questions, and I will then be able to write up my findings in some way that makes sense.
Lichtman, M. (2013). Making Meaning From Your Data. Retrieved October 27, 2015, from http://www.sagepub.com/sites/default/files/upm-binaries/45660_12.pdf
Merriam, S., & Tisdell, E. (2009). Qualitative research: A guide to design and implementation. San Francisco: Jossey-Bass.
Penn, C. (2012). 5 ways to make sense of data – Christopher S. Penn Blog. Retrieved October 28, 2015, from http://www.christopherspenn.com/2012/09/5-ways-to-make-sense-of-data/