Unisexual Ambystoma

Unisexual Ambystoma

Friday, February 28, 2014

Scenes from the OSU Museum of Biological Diversity Open House

Earlier this month, I was happy to again participate in the Ohio State Museum of Biological Diversity Open House, our department's biggest outreach event. We had more than 2,200 visitors from all parts of Ohio and elsewhere. This year, Matt Holding and I teamed with two fantastic undergraduates who work in our lab (Meghan Parsley and Paul Hudson) to go even bigger than we did last year. Since this year's theme was all about how scientists use technology to discover and classify biodiversity, we put together a booth that showed visitors how our lab uses technology across all aspects of our science, from catching animals to analyzing their DNA.

We had an absolute blast at this event. Apparently, so did a whole bunch of other people!

Here are some photos I took frantically between showing salamanders to (big and little) kids:

And here are some photos of our booth, some of our materials, and some of the great visitors we met!


At the end of the tables, we had a few animals on display that showcased some ways that DNA can reveal biological differences between organisms. Included among these animals was the eastern glass lizard that we brought back from Florida last year, and I was astounded at the number of kids that could immediately identify it! The little "flip quizzes" at the end of the booth sparked a lot of discussions with both adults and children.


This is a great event and I highly recommend it if you are a local. All the faculty, staff, and students are so excited to meet the citizens of Ohio and share their passion. For more pictures and information, I'd recommend the Museum of Biological Diversity Facebook page here.

Monday, February 17, 2014

Who Works 80 Hours a Week in Academia?

Part of being a graduate student is working hard. Whispers of disappearing faculty positions and decreases in funding percentages are heard at most social gatherings. You have to be in the lab 80 hours per week to stay at the front. Right? In this really good blog post, Dr. Meghan Duffy (follow her on twitter here!) presents her argument for why the myth of the 80 hours/week = success equation is pretty silly. 

When I read Dr. Duffy's post a few weeks ago, I had already been intensely thinking about the way I work for about a month. After reaching doctoral candidate status in the fall, I realized that I had a lot of irons in the fire. I also realized I had no real grip on how I spent my time. I knew I was working and I knew I felt like I was working hard, but I needed some more information about my habits. Ya know, data.

So how does a PhD student spend their time? Well, I've been diligently logging all of my work hours since January 14th. I'm no Steven Wolfram, but I put this app on my phone and set up six categories of my work: 
  • General Work: a catch-all for emailing, running small errands, generally finding journal articles, etc.
  • Meetings: anytime I was sitting in a meeting for the lab, the department, or other research activities went here
  • Thesis Research: any activity related to thesis research
  • Other Research: any research, including educational research, that doesn't directly apply to the ol' thesis
  • Outreach Activities: this included both things outside of the university (giving a public talk, preparing materials for outreach events, etc.) and things within our lab (running undergraduate lab meetings)
  • Teaching: any time spend preparing for teaching or preparing for teaching
There is definitely a lot of subjectivity involved when placing actions in one of these categories, but this is what I rolled with for better or worse. Bottom line: whenever I was really working (not surfing the internet) on one of these categories, I was "clocked-in".

How much am I working?
As of downloading the data on Sunday, I've averaged 45 hours/week of real work. I'm working an average of 6.43 hours per day (including weekends). If I look at when I'm working, I start my Monday-Friday work days on average at 9:04 am and head home at 6:40 pm on average. 

Here is a boxplot of the start times of different activities:

This makes pretty good sense compared to my general thoughts about my schedule. I usually have meetings during the morning or midday, handle little things and email first thing in the morning, and often use larger blocks of time in the afternoon for research in the lab or at my computer. I generally go to the gym early in the morning and take time for lunch with other grad students. 

What am I working on?
Since I am not teaching this semester and am being paid through a research assitantship, the data shows that I am (thankfully) working mostly on research projects. The teaching category isn't presented here for the same reason. 

Category: Duration (% of total across 33 days)
General Work: 47.46 hours (22.4% of total)
Meetings: 23.67 hours (11.2% of total)
Thesis Research: 81.28 hours (38.3% of total)
Other Research: 14.76 hours (7.0% of total)
Outreach Activities: 44.99 hours (21.2% of total)

Here is a bar chart showing how I spend each work day on different activities:

I love this view because it primarily demonstrates what I think is so great about being a graduate student: few days are ever the same. Sometimes I can spend the day devoted to a single project and some days I run from place to place doing very different things. For example, on January 30th I spent the whole morning getting some things in the lab organized, had a committee meeting late-morning, ate lunch with the departmental seminar speaker, went to the seminar in the afternoon, worked in the lab for the rest of the day, and then drove to Crawford County in the evening to give a public talk for the Parks District. The following Thursday I spend the majority of the day at my computer writing. Different days produce very different paces and styles of work.

Other observations:
I don't work that much on the weekends. I use the weekends as re-charge time and predominantly spend them with my wife and friends or working on hobbies. I think this is a good use of my time so that's what I do.

Some days are long days and some days are short days. Fridays are generally short days while Mondays/Thursdays are generally long days away from home. I'm not a robot that can work long hours day after day, so long days are usually followed by less work the next day. I can see the sense in this, but definitely see room for improvement. 

How efficient am I?
I wish I had better data to answer this question. Since I didn't log the amount of time I was "trying" to work, it is hard for me to know how many of those hours I was actually working on one of the above categories. 

One thing I was interested in is how long I spend doing each activity. For example, I am extremely fatigued by reading journal articles for more than an hour, but I feel like I can infinitely chip away at a seemingly endless "small things to do list".

Here is another boxplot showing the duration of each activity:

So, generally, I spend an average of about an hour on any given activity, but the duration is awfully variable. The extreme outliers shown here can be explained by the Museum of Biological Diversity Open House (Outreach) and the Ohio Biodiversity Conservation Partnership annual meeting (Meetings). 

But have these been a productive few weeks? I think so. I believe that I spent each of those ~45 hours to get things done. But my whole point here is to quantify what the daily life of a scientist is actually like without the posturing or the caricatures of overworked grad students pulling out their hair.

Haha, yep, there I am.

Besides the obvious benefit of having sweet, sweet data to play with, logging these hours had an entirely unpredicted psychological outcome. It turns out that taking the time to click on my phone and think "Ok, what am I actually going to do right now" is a great exercise in focusing my mind.

I'm now going to click "end outreach activity" and go watch Downton Abbey. See ya.