Throughout class it was hard to imagine how an interview could transform into data. How do field notes, observations and interviews come together to produce trustworthy and relevant outcomes? After participating in the simulated practice interviews, learning how to create a transcript, and code interviews I am starting to see the value of this process.
Before we started the practice interview, I had the perception that it would be very easy. I have conducted job interviews where I had several core questions and then changed up what I asked as we went. It is a normal part of my job to interview customers to determine learning gaps and what direction to take with their training. So, the qualitative research interview should be a breeze.
First, I played the interviewee, and my partner had a smooth flow from one question to the next. It was easy to talk and share my thoughts. Finally, it was my turn. My plan was to start with the first question, then adjust as the conversation went on. At first, I would be engaged in the responses and forget that I needed to compose a relative question to keep the conversation going. Eventually that did get easier.
One interesting find is my line of questions veered off greatly from the original topic. At first, I was unhappy with myself for not staying on point, but I realized what I veered off to was so much better. We identified a realistic challenge when implementing technology in the classroom. If I was a researcher this would help me position the value of my research.
Transcribing in Camtasia
I experimented with transcribing audio. As an Instructional Designer I use tools like Camtasia to develop training. I tested the audio to speech feature in Camtasia, using a computer mic to record an audio clip. Audio can be recorded right into Camtasia; however I used my preferred recording method of Audacity. In thinking about the audio recording the point is to get a good quality and a format that Camtasia can process. The quality of sound can influence accuracy of the transcription. The file was outputted as a wav, however mp4 should work nicely as well. A fresh project was opened in Camtasia, and the audio file was dropped into the timeline. To produce the transcript in Camtasia, right click on the audio file in the timeline and choose ‘Apply speech-to-text’ from the menu. This features is typically used to create captions in videos, so the captions box appeared next to the main video screen when the process finished. To finish the ‘Export Captions’ was selected, which allowed me to save the file to a local drive. The file that downloaded was .srt format, this was changed to .txt, when opened I could see the transcribed audio. I didn’t experiment with other formats other than a text document. I need to play with transcribing further, however this little test gave me a starting point for future tests.
The coding demonstration was very helpful, when we broke off to try it, we applied the same process that was demonstrated. Being partnered with a friend and like-minded person we worked through coding without conflict. One of us would make a suggestion, and the other person would either agree or make an alternative suggestion. With that said, it is easy to see how a research team could have conflicts. For one thing, personal bias could make coding a subjective process and affect research outcomes. We identified personal bias in our subjectivity statements, but after coding in class, this will be revisited.
Over the last two weeks I have gone from not understanding the qualitative interview process, or how this can be used as trustworthy data to experimentation and thinking about how I can apply what I have learned. It is kind of exciting to see this different (to me) method of data collection as a possible solution to my research.