Last month I tried to explain how I spend my teaching time both inside and outside the classroom. So what about the other 60% of my time: 40% for research and 20% for service. What do those mean? Let’s tackle the research part this month.

I’m an observational astrophysicist, which means that my research consists of using observational data to figure out how the universe works. But this doesn’t mean that I spend my nights at a telescope glued to the eyepiece. I use data from telescopes on the ground (CFHT, Gemini,  JCMT, and others) and in space (Hubble, Spitzer, Chandra) to try and answer specific questions about how stars in nearby galaxies are born, live and die. So, broadly, my research might go something like this.

1. Think of an interesting question and find out if it’s already answered. This usualy involves a lot of reading, mostly through the Astrophysics Data Service.
2. If not answered, figure out what data might be needed to answer it. If already answered, go back to step 1.
3. Figure out whether the data already exist. This can involve a lot of web-searching at online archives of telescope data. Someday there will be one-stop-shopping for such (the “Virtual Observatory”) but not yet.
4. If the data already exist, great: download them and get to work. If not: figure out what telescope could generate the necessary data, write a compelling proposal for telescope time, and design (& perhaps perform) the observations. [The previous sentence summarizes what can be months of work and will perhaps be the subject of a future post.] Sometimes it turns out that it’s not feasible to get the necessary data, in which case go back to step 1.
5. Once data are in hand, “reduce” them. The idea is to go from numbers in some kind of digital image to physical measurements, for example luminosity of an object in Watts. This step is what grad students spend a lot of their time on.
6. Finally, figure out the meaning of the physical measurements. Often this is done by comparing to simulations or other theoretical models — do the models and data agree? If not, is there a plausible reason why?
7. Share the results of the research: write a journal paper, give a conference talk or seminar, present a poster. More often than not, I do all three for a given piece of research (sometimes at different stages in the work).
8. Hopefully the research has suggested new questions to explore: return to step 1.

Many of these steps are done in collaboration with other people (see recent post by John de Bruyn) — one person doesn’t usually have the required technical expertise to do everything. (And see also this paper on the decline of the single-author paper in astronomy.) Almost all of these steps are done while sitting in front of a computer, but that computer can be nearly anywhere in the world. I know people who reduce the data from observing runs on their airplane flights home. Or write their papers in telescope control rooms. I’m usually too tired to do either.

You’ll also notice that there’s a lot of “back to step 1” in the list above. That’s the nature of research: 2 steps forward, 3 steps back, a couple of sideways steps. Eventually we get somewhere, but it’s not always where we expected. But that’s why it’s fun.

Now, if you will excuse me, I have an observing proposal to write.

If you have not heard of Carl Wieman, his bio is on http://cwsei.ubc.ca/.  In 2009, he has given various talks on scientific approach in science education.  Many of you who are in tuned with science education would no doubt know of his work.

I found that he had transcribed his talk into five written parts here: http://www.science20.com/carl_wieman/why_not_try_scientific_approach_science_education

While you may not agree with his proposed solutions, I would like to quote two points here that I find particularly good that may pique your interests:

1. “puzzle of my graduate students—why their first 17 years of education seemed so ineffective, while a few years of doing research turned graduate students into expert physicists”
2. “… novices see the content of physics instruction as isolated pieces of information— handed down by an authority and disconnected from the world around them — that they can only learn by memorization.  To the novice, scientific problem-solving is just matching the pattern of the problem to certain memorized recipes.
   Experts—i.e., physicists—see physics as a coherent structure of concepts that describe nature and that have been established by experiment. Expert problem-solving involves employing systematic, concept-based, and widely applicable strategies.”

I would love to hear what your thoughts are on Wieman’s insights or if you have ideas of how best to turn novices into experts.