It’s Week 4 already for my research students, and summer research is in full swing. My students have spent much of their time so far working on some data collection and data analysis tasks, and had their first opportunities to do some technical writing (which will be good practice for the conference paper they will write at the end of the summer). They’ve learned a few new programming languages (Java, Perl) and modified code written by others (and not very well commented). They’ve hit a lot of dead ends and experienced a lot of “huh, that’s odd” moments with the data.
In short, they’ve had a pretty full research experience already!
As a research mentor, I’m facing a couple of key challenges at this point in the summer:
- Helping my students to become more self-sufficient, while still encouraging them to ask questions
- Carving out time to get my own work done, while still being an effective mentor to my students
The first challenge is particularly tricky when working with students who are not familiar with the whole “doing research” drill. Doing research means that we’re working with questions without answers, essentially working at the edge of our knowledge of a field. Students are used to problems that have “correct” solutions, and are used to having someone to turn to (a professor, a classmate, the almighty Wikipedia) for that answer. Students new to research will sometimes become paralyzed with the unknown, and instead of trying something will either do nothing, or will ask questions too often (confirm everything before trying, for instance).
My responsibility is to get them to try out ideas before asking me questions—in essence, getting them to trust their instincts, and to develop a research instinct in the first place. So, for instance, when a student comes to me and says “the program doesn’t work and we don’t know why”, instead of running down to the lab, I’ll ask if they’ve isolated the problem to a particular section of the code. If they’ve isolated the problem, I’ll give them a few things to try—or, better yet, I’ll ask them “what do you think you should try next?” By not rushing to bail them out, and by forcing them to confront their demons, they become more willing and able to do the initial legwork on their own, and end up coming to me with more interesting questions because they’ve already answered some of them on their own.
The flip side is knowing when to spend the time walking them through the answer. This afternoon, for instance, I decided to sit down with one of my students and walk her through a particularly tricky section of code which had to be modified. Sure, I could have said “here is the API, figure it out yourself”, but I sensed that both of us would be more productive if I put in the face time with her. And it turned out to be the correct thing, because we discovered the code in question is quite inefficient, and put fixing the code on our to-do list.
This leads, though, to the second challenge: working with 4 students, I am less in control of my schedule than I’d like, because I never know when I’m going to have to spend the afternoon in the lab with them, or when a technical problem they can’t fix is going to crop up. I am queen of the daily to-do list, but lately much more is not getting done and migrating from daily list to daily list. I need to carve out some time that I know I won’t be interrupted so that I can work on the bigger/more intellectually challenging tasks, and balance those with the smaller, more deadline-driven tasks. I’m also experimenting with putting specific blocks of time on my calendar for specific tasks—we’ll see if that works better this week. I think I also have to be a bit more realistic about what can get done in a week, and be satisfied with that.
The challenge in the comming weeks, for me and my students, is maintaining momentum and morale, as the project intensifies and the problems get harder. Hopefully we’ve laid a solid enough foundation in these first few weeks to maintain both.