Skills Toolbox: Research
By Madeleine Peckham
While the
“real” world isn’t very good at sizing up humanities grads’ skills, most people
are aware that we have a lot of experience doing research. But what exactly
does “research” mean, and how can this academic task be translated into a
workplace skill?
Research
involves far more than leafing through books or doing online searches. Research
is a process.
Knowing how
to research is one of the most transferable skills you possess, and one of the
most valuable. Sure, you will probably never again be on JSTOR looking for
peer-reviewed articles critiquing Juergen Habermas’ characterization of the
18th-century “public sphere”– bummer? hardly– but every job that requires
analysis and decision-making requires research.
As I often
tell my undergrads, the first part of research is crafting a good question.
In a class, this is usually done for you by the professor. At work, it’s often
up to you. How you develop your question involves what information you have
available, what your time constraints are, and in what format you will be
presenting your results and conclusions. A good research project can be
seriously hampered by a bad starting question. As in academic research, it’s
very important to get a clear handle on what demands the project needs to
fulfill before you begin to execute it. Making brilliant conclusions tends not
to impress people if you weren’t addressing the question they wanted an answer
to.
Second, come
up with a data-gathering plan. In grad school, we call this
“methodology,” but in the real world, it’s often framed as a response to time
constraints. What is the most efficient way of collecting data will allow you
to maximize the amount of relevant information on your topic? When I worked at
a DC non-profit, I often had to compare pending legislation in several
different states. State legislatures used conflicting terminology and organized
their databases differently. It was imperative to come up with a plan so that I
didn’t have to waste valuable time viewing the thousands of database entries
that were irrelevant to my study.
Choose your
data wisely. As a
TA, I often read papers that I know were “researched” entirely from the first
hit on Google. Be sure to consider possible sample biases and be ready to
justify your choices of what you select. In the work sphere, this often
involves thinking about your sources of data– do they have political leanings?
What’s the funding source? Who’s doing the work? What other work have they
done?
And now the
fun part– analysis. Data, contrary to what a lot of
people think, doesn’t just speak for itself. It’s critical that you interpret
what you find, keeping in mind how it specifically relates to your research
question. Try to make your analysis as clear and concise as possible. The point
here is to help people understand what you found, not to wow them with how much
effort you put in.
Finally, draw meaningful
conclusions. In undergrad papers, most students assume this just means
restating what you’ve already presented. In a work situation, you will probably
be expected to explain how this will advance company goals, support related
projects, or offer an important new perspective. The key to this is to think
about why your research question originated in the first place. What was the point
of your study and what’s next?
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