This final reflection for the 2019 fall internship covers what has been learned from this experience – what I have gained as a writer, soon-to-be-graduate, researcher, and what skill sets, competencies, and experiences were gained – its challenges and successes. Though interestingly, the internship entailed rather a little composition – leaning towards more methodology and technology research, along with data management. Although, this did allow me to leverage my previous professional and academic experience which provided valuable insight into the potential professional applications that my education through the University of Alaska Anchorage provides.

Fortunately, Dr. Stone focused my work on the technological aspects of the research – the design of the corpus, how to structure it, what software best leverages the data, and prepares it for rationalist research. This entailed the composition of a guide which detailed the corpus structure, how it was created, the folder/file hierarchy, and naming scheme of the documents composing the corpus; additionally, a research memo was written up to detail the boons and restrictions of upgrading an ATLAS.ti license to the latest release version. The coding process was new to me, previous courses have had an only cursory explanation (save for Dr. Jenkins Research and Methodology’s course) regarding the inner working of corpus analysis.

While these documents are simple in their purpose, they required time to understand the scope of the different software suites used in the research; however, while research functionality was an import aspect of determining the usefulness of a software, I paid specific emphasis to software usability through the user interface – something quantitative corpus methods and software packages such as within the R statistical language lacked. Qualitative analysis suites such as ATLAS.ti and MaxQDA which leverage categorical context codes leveraged both qualitative and quantitative approaches – sating both the rationalist and the empiricist researcher.

These required the research of corpus methodologies and of the software used to conduct it; Corpus design seemed varied across corpus subdisciplines and were largely determined by whether the origin of the discipline was of empiricism or rationalism and whether the discipline focused on the qualitative or quantitative aspects of language; unfortunately, I realized this variance in design after the initial creation of the corpus and concordance reports and  as I read deeper into the methodologies of corpus research over the semester, I realized that the initial construction of the ‘concordance’ was flawed. In no manner did the ‘Central document’ which tabulated the excerpts from the corpus server as a concordance – candidly, it was a bastardization. These setbacks would repeat in several forms – new context words that were initially overlooked would be found in the larger contexts of excerpts – these keywords would be added to the terms list which would then generate additional excerpts that would need to be highlighted and prepped for coding. This frustratingly would consume precious work hours. Dr. Stone was understanding – “Welcome to research”; I suppose this is the case when undertaking an unfamiliar methodology – as a researcher I can read the theory of the method until I am blue in the face, but it is not until I attempt to apply these methodologies where I discover the gaps and presumptions in my knowledge.

Nevertheless, I am thankful for the competencies I gained during this internship. Through the papers requested, the nearly weekly check-up meetings conducted by Dr. Stone, I became more comfortable in participating, discussing, and evaluating/comparing research methods to how Dr. Stone wanted to approach her research; additionally, I found my pace in meeting quality and time deadlines – avoiding the large bursts of productivity leading to fatigue and burnout.