PREVIOUS: Gathering Evidence (Primary)
Introduction
After you have collected your primary data, it is natural to feel overwhelmed. Hopefully, you have a lot of results to sort through, organize, and analyze.
Transcribing Interviews
If you have recorded an interview, the next step is to transcribe all–or part–of the interview. Transcribing involves listening to the interview and writing down what was said. You may wish to skip over tangents, but don’t automatically do so. You might find they aren’t so tangential to your research after all!
It really helps to slow down the recording when you are transcribing. If you have a good amount to transcribe, you may want to look online for a free transcription program that does this. Transcribing takes a lot of time. Plan for about 15 minutes of recording to take an hour to transcribe.
A transcription looks like a script you might find for a play. You will have each participants name, pseudonym, or initial, to the side to show who says what. You may use ellipses (…) to indicate pauses. Don’t worry too much about proper punctuation, though. Transcribing will show you just how messy speaking can be. You’ll find that your participants don’t often speak in clear, neat sentences like you might find in their writing. That’s okay. You can cut out filler words like “uh,” but don’t worry about editing their language. Write down what was said.
Here’s an example of part of the transcript for the interview we watched under the Gathering Evidence section with Dr. William Betts.
KL: How does the campus counseling center differ from another kind of mental health care facility? It’s got to be a unique approach, right?
WB: It is and it isn’t. In many ways it’s a targeted group. If you think about community mental health, you have folks that are in their forties, fifties and sixties. We have fewer of those folks coming into the counseling center. The issues that students deal with are often pretty straightforward. I kind of talk about college as being a perfect storm of stress. You spend your whole high school years trying to get into the right college. You then get in. You leave everybody you know at home, all your friends, all your family, you move to a strange city where you don’t know how to get around, you move into a room that’s about the size of your bedroom at home
KL: With a stranger.
WB: With a complete stranger sometimes, right? And then we put you under a whole bunch of academic stress. And what you find is that that’s a lot for students to manage, so that is a very predictable set of concerns. Now, whether folks have anxiety because of that, or depression, that’s a little variable. But that’s probably the place where things are slightly different than community mental health is the fact that it is that, sort of, one population.
KL: So, the situational factors are more pressing with this particular clientele.
WB: Absolutely. And what I will tell you is that there is a really strong professional group of counseling centers across the country in universities, and so we work together, we gather data, we do research together to really target students’ needs. And that’s the really nice part about it is, is that we learn from each other and we’re able to address very similar issues amongst various campuses.
Coding Data
Whether you are working with transcripts of interviews or artifacts from an archival analysis, coding is a useful tool for analyzing your data. There are many methods of coding, but we will stick with something fairly basic for the purposes of ENG 104.
You may be used to a similar process from writing papers based on secondary sources. You may have looked at those sources for particular themes and marked those themes in some way. For example, you might have highlighted sources with several different colors that indicated different themes, or you may have had a short-hand “code” that you wrote in the margins of your sources to mark where those themes occurred. Coding primary data is very similar!
There are three types of coding you may use for ENG 104.
A Priori—Sometimes researchers look at qualitative data for particular themes or topics that they already know. They may generate a list of codes before looking at the data. This method is called a priori coding.
For example, in a study of what types of comments teachers leave on student papers, you might apply a list of the types of comments to the data such as: question, praise, negative comment, correction, statement. Let’s say I have collected a bunch of teacher comments, which are my primary artifacts for coding. I would then determine if the comment should be coded as a question or as another code on my list. This type of coding is helpful if you have a very focused study where you are trying to find out exact information.
Descriptive-–This simply means that you are summarizing the main point. For example, in an interview, you might find a few words that summarize the gist of a participant’s answer.
For example, Dr. Betts said in the interview: “You leave everybody you know at home, all your friends, all your family, you move to a strange city where you don’t know how to get around, you move into a room that’s about the size of your bedroom at home.” He’s talking here about the stress of adjusting to college, so you might write that in the margins of your transcript as a summary, even though he didn’t use those exact words. This type of coding may help you see how your data fits with other research. Perhaps you already found a secondary source about adjusting to living conditions in college settings.
In Vivo—You may want to go into your data with a completely open-mind. To do so, you may decide that your codes will emerge from the very words the participants said. This method is called in vivo coding.
For example, let’s take this quote from Dr. Betts: “And then we put you under a whole bunch of academic stress. And what you find is that that’s a lot for students to manage, so that is a very predictable set of concerns.” We might code it “academic stress” using his own language. Another code might be “predictable concerns.” Maybe you don’t personally agree that this type of stress is predictable, but the point is that this is the language the participant uses to characterize it. This method is valuable to break away from any pre-concieved notions you have about your topic and see what your participants are actually saying.
Research Memos & Notes
Writing memos is another great way to get your thoughts in order when you are working with qualitative data. If you are working collaboratively, memos are a great way to communicate with your research team. At any stage of the research process, it can be valuable to stop and reflect on what you are finding. You can write about your initial impressions after conducting an interview or about what you discovered when you did your coding. Reflect on what you are learning, what is surprising you about your data, and what you still have to learn.
Analyzing Quantitative Data
With a survey or other quantitative data, you will work to create graphs, charts, and tables based on your survey results and provide verbal descriptions of each of the visuals. But how do you know what to include? You can easily acquire pre-made charts with whatever online program you used to make and distribute your survey. But this may not be the best data to include.
If you collected demographic data, does it make a difference to your study? In order to find out, you can cross-tabulate your data or filter it by a certain demographic. Let’s say you followed up on the interview you did with Dr. Betts by conducting a survey about stress in college students. You might want to see whether or not the year of the student influenced the type of stress they experienced. You might hypothesize that first-year students experience more social stress around moving to college but that seniors experience more financial stress. However, if you just list how many freshman and how many seniors took your survey and how many overall students felt what type of stress, then you are missing a valuable chance to connect your data. Run the numbers and see if anything interesting comes up.
Qualtrics provides a helpful tutorial on using their survey software to analyze your results.
You may also have collected a few open-ended answers on your survey. In this case, you can go back to what you learned about coding qualitative data and apply that to those sections of your survey.
Summary
Whatever type of primary research you conducted, analyzing it is hard work. However, just like sorting through secondary sources is important to preparing you project, organizing and analyzing your primary data is key to do before you begin writing. You may have to return to the data while drafting, but you’ll have a great start on how to organize your project and what to include from your primary research before you start writing.
NEXT: Ethical Approach to Primary Research