Reflections

Overall, this project was a large undertaking but luckily I was able to slowly but steadily chip away at it. I think the most important thing that can come from my work this summer is the creation of a workshop that can help to introduce others to coding DTRA. From my experiences I can help to create exercises and use tools that have helped me to understand coding.  For example, do you remember the Template I talked about in the last post? Well as a refresher, it is just the non-coded transcription pasted on an Excel worksheet in the first column followed by columns for D, T, R, and A. And if we are also coding for emerging elements then also columns for D’, T’, R’ and A’. That template can then be copied, pasted, and coded in another sheet of the same excel book and then compared to any other coded worksheet in the Excel workbook using a split-screen view. After I had done my coding, I was able to view both my coded sheet and the previously coded sheet using split-screen view. Then using scroll lock I was able to scroll down on both documents at the same time and compare the coding of each.  Using this method was extremely beneficial for me, and because getting to this method was a trial-and-error process, I would like to include it in the workshop to make it as efficient as possible.

However, the application of DTRA to a situation like this is still so new that we still aren’t sure what is the best way to measure DTRA data. Right now the coding I have done has been mainly concerned with the number of times that an element is measured as well as the number of existing elements that are uttered compared to that of emerging elements. But what about the pattern that the elements appear in? If we have tried to include potential elements should we also try to code for negative utterance (this is saying that a Domain, Task, Resource, or Activity is not present in the community. As you can see this is a multifaceted problem with a multitude of possible solutions. Professor Aday is currently working with Cathy Merritt, who is a part of SOMOS (Student Organization for Medical Outreach and Sustainability), to answer the next stage question: how will we use the DTRA data that we have coded and collected? Answering this question is vital to being able to figure out the best way to code transcriptions and to analyze the data.

This summer was so important because it allowed me to dive head first into the DTRA coding effort. It is a project I look forward to pondering through, frustrating over, and working on throughout my undergraduate career.