Job (Re)Search: Part Five – Results, Analysis, Discussion

Phew! We’re almost there—I can see the light at the end of the tunnel. We’ve almost covered the whole research process in this series, and with this article we’ll be putting the finishing touches on the career exploration/research metaphor.

Last week, I wrote about data collection, emphasizing the process as one of action. The corresponding relationship to career exploration was obvious, as action is the key to forward motion in both domains. With that in mind, let’s talk about what comes next: analysis and discussion of results.

If data collection is all about action, then analysis is about calculation (in either a mathematical or a logical sense) and discussion is about imagination. Once researchers obtain their study’s results, they must apply a strategically chosen method of analysis to those results in order to make them meaningful—otherwise they’re just a bunch of numbers (in quantitative research) or words (in qualitative research). Whether through statistical tests or any variety of qualitative content analysis techniques, data begin to take the shape of meaningful results.

Of course, we don’t run t-tests or ANOVAs after we’ve undergone a similar data collection process in our career exploration efforts. It’s still advisable, however, to reflect on the actions you’ve taken, and how the information you’ve gathered—about you, about the world, about different people and work environments—might be meaningful. Without this reflection, all those actions you’ve taken are only partially beneficial to you. They’re still opening up new opportunities and keeping you engaged, but they’re not helping you to learn, and career exploration—like life itself—is all about continuous learning.

Science doesn’t stand still; it’s always evolving as new research is produced, reviewed and disseminated. We’ll never get to the point where we can say, “Aha! We’ve figured out science. No further research is necessary.” That might seem hyperbolic, but think about how you treat your career development—is it possible that you’re expecting to just “figure it out” one day? If so, I hate to do it, but it’s my responsibility to let you know that’s never going to happen. In my mind, it’s as preposterous an assumption as the one about figuring out science.

Every piece of research changes things, even the ones that discover nothing new. In fact, those are some of the most important studies, because they often help to confirm that a previous finding is indeed reliable. The message I’m hoping to impart today is that every experience changes you, even the ones that don’t tell you anything new about yourself. It’s up to you, however, to analyze the data in order to conclude how you’ve changed.

Once the analysis is done, researchers move on to a discussion of their results. Discussion, in this sense, doesn’t mean hanging out at a coffee shop for a friendly chat. Rather, it is an in-depth examination of the implications of that particular piece of research. It is asking questions about why the results came out the way they did, and what those results mean in the context of already existing research findings. It is coming up with theories in order to explain the results, imagining as many implications of the research as possible, and identifying where more research can to be done. It is where researchers’ imaginations run free, and curiosity is the order of the day.

Isn’t it great to be curious? To imagine what life would be like 5 or 10 years from now, when you’re well on your way down a career path? If you’ve identified a few directions that you’re curious about getting into, now’s the time to write your career exploration’s discussion chapter. Why those careers, and not others? What theories do you have about how those careers might be a good fit for you? What have other people’s paths been who’ve ended up in those careers looked like, and how might yours be similar or different? If you were to go on this path, how might that impact other areas of your life?

Results. Analysis. Discussion. Pretty rad, right?

Miss the last 4 entries in this series? Part 1, part 2, part 3, part 4.

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