The Little Things

On the same day that I renewed the Pandora subscription I have for my lab, I read this blog post by Namnezia, where he argues that a lab espresso machine is one of the best investments a new PI can make in his/her lab. This got me wondering about the little things that I do to try to increase lab morale, and what I might want to add to the mix.

Some of the things I do:
1) Pay for a lab Pandora account: It’s not very expensive, and spending long hours in the lab pipetting Daphnia and washing glassware pretty much requires good music to keep from going insane. (Audiobooks work quite well, too – I listened to tons and tons of books while counting samples as a grad student – but they don’t work as well when there are multiple people listening.)

2) Celebrate lab birthdays: this is a tradition I’ve carried over from when I was an undergrad in Nelson Hairston, Jr’s lab at Cornell. When I first joined Nelson’s lab, one of the first questions I was asked was when my birthday was, since all lab birthdays were celebrated. That was a great way to signal that I was valued as a lab member, even as the new undergrad in the lab. I’ve carried on this tradition in my lab, and I think everyone enjoys it. I mean, who doesn’t like an excuse to eat cake?

3) Lab lunches: At Georgia Tech, we would have lab lunches every Friday. People could come or not as they wished – it was just an opportunity to get together and chat informally. I started this in part because of how much I loved the lunch room at the Kellogg Biological Station, where I was a grad student. Grad students, postdocs, and faculty would gather in one room to eat, and it was such a great way to interact with everyone. Here at Michigan, we haven’t started weekly lunches yet, in part because there is no good place to have them near my current lab space. But we’re moving to a new lab space soon, and that will have space for this sort of thing, so I’m hoping we’ll resurrect lab lunches this summer.

4) Lab outings/get togethers: This is something that I did much more of pre-kids. Sadly, my current lab members probably will read this and think – lab outings? Huh? But, pre-kids, we did things like go to Braves games (back when the lab was in Atlanta), I had people over to my house, etc. Now, I find it much harder to figure out how to make time for these things, but I probably should work on that more.

Those are the main things I can think of right now. It doesn’t seem like much, really, and I’d love to hear about other things that I could do to keep a happy lab. If you’re a PI, what do you do for your lab that you think works well? If you’re a student, postdoc, or tech: what would you appreciate your PI doing?

Education Components of CAREER Proposals (UPDATED!)

This post is aimed at people who are considering applying for a CAREER award from the US National Science Foundation. For those who aren’t familiar, these awards are aimed at pre-tenure faculty. The key ways they differ from regular grants are: 1. they are restricted to pre-tenure faculty, 2. they are for five years instead of three, and 3. they include both a research component (like typical grants) as well as an education component (which, to a first approximation, is sort of like a broader impacts section on steroids). I’m focusing on the education component here. I am writing this based on experience applying for one (which included reading the CAREER proposals that had been written by a lot of different people), talking with people who applied for them about what worked and didn’t work, reviewing CAREER proposals, and talking with others who’ve reviewed CAREER proposals about what generally works and doesn’t work. With a CAREER proposal, if you don’t do a good job with the science part and the education part, you won’t get funded. I’m hoping this post helps people as they work on the education component.

As with any proposal, it is immensely valuable to get examples from people who’ve applied. Clearly it’s good to read proposals that were successful, but it also helps to read ones that were not, especially if the person is willing to share reviews, too. Knowing what doesn’t work can be as important as knowing what does.

In my opinion, the following things are needed to have a compelling education component of a CAREER proposal:

1. Focus on a particular subset of educational activities. Don’t try to do all the possible broader impacts that NSF lists! Choose 1-2 areas that you particularly care about and focus in on those. In my case, I focused on topics related to underrepresented groups in science. I had several different activities, but they all centered on that theme.

2. Convince the reviewer that what you’re focusing on is important and that what you’re proposing to do to address that problem really will address it. Cite your methods/approaches in this section of the proposal the same way that you would the methods in the regular part of the proposal. For example, if you are proposing to develop hands-on activities for middle school kids to try to help them stay interesting in science, show (with citations) why hands-on activities are particularly valuable, and why it makes sense to focus on middle school kids.

3. Convince the reviewer that you can do the proposed work. Don’t just say that you will recruit minority students, or that you will set up a summer program focused on math-bio, or whatever. Prove you can do it. It’s the same as with the regular part of the proposal: preliminary results help convince the reviewers that you can pull it off. Yes, this means that you need to do some of the work ahead of time, before you know whether you will be funded. But, in my opinion, that is time well-invested, in part because it increases the odds that you will be funded. And, if you take my advice from point 1 above (about choosing something you particularly care about), hopefully you’ll find that you enjoy the time you invest in this.

4. Take advantage of existing infrastructure at your university. Lots of places have units devoted to helping with teaching and outreach activities.  Maybe they already have an existing camp in place that you can work with. Maybe they can provide you with references related to pedagogy. Maybe they can help you design ways to assess whether your approach is working. Whatever it is, take advantage of these resources. At Georgia Tech, I established my own links with a camp at Piedmont Park (located in Midtown Atlanta near Georgia Tech), and I also took advantage of the help from CEISMC, which is Georgia Tech’s Center for Education Integrating Science, Mathematics, and Computing; they helped me add in realistic assessment tools.

5. Include a means of assessing the success of your education component. For example, if you are going to design an educational activity for K-12 students, you should assess whether that activity is an effective means of achieving your educational goals. In my case, as I said above, I relied on help from educational experts (from CEISMC) for developing those assessments.

6. Similar to a regular proposal, if someone’s help is essential to the success of the education component, get a letter from them. In my case, I included letters from the person who runs the camp at Piedmont Park, a letter from someone at CEISMC who could help me with assessments, and a letter from a colleague at Spelman College who helped me recruit Spelman students to work in my lab.

7. Devote funds to the education component: Another way to show that you are serious about the education component is to include funds in your budget to support it. There are lots of things you could budget funds for: supporting students and/or K-12 teachers, buying supplies for classrooms or camps, etc.

Of course, all of the above is just my opinion on what makes for a compelling education component of a CAREER proposal. If you disagree (or agree), please let me know in the comments!

UPDATE: In the comments, Ethan White pointed out something very important that I forgot to include in this post. It’s so important, that I will make it point 8:

8. The research and teaching components should be integrated with one another. Having a great education component that is totally unrelated to the research component will be seen as a major weakness. Reviewers will want to see synergy between the components (and are asked to consider that when reviewing CAREER proposals.)

Prioritizing manuscripts, and having data go unpublished for lack of time

A few recent things have gotten me thinking about how I (and others) prioritize working on manuscripts. First and foremost, I have a new baby who is not yet in daycare. My husband and I trade off watching him, and I need to be really efficient and make sure that I work smart during the chunks of time that I get to work. (By the way, one thing I’ve discovered is that I should schedule Skype meetings for times when I am watching the baby, as it’s relatively easy to keep him happy by bouncing on a yoga ball while Skyping. Yoga balls and Skype are apparently important components of work-life balance for me.) In short, prioritizing tasks on my to do list is even more important right now than it normally is. Second, there has been renewed chatter on twitter related to whether some data are not worth publishing because they are not of sufficient interest (which, for some people, apparently is if they can’t aim for Nature, Science, or PNAS). DrugMonkey has been heavily involved in these discussions, and wrote this blog post in response to one of those discussions. His first point is “never let data go unpublished for lack of impact.” That seems reasonable. But it made me wonder how much I and others let data go unpublished for lack of time. And, if that is happening, is it a sign that I (or we) should change how we approach things?

To explain a bit more: every PI that I know – and many postdocs and grad students – has generated more data than they have been able to publish. This means that decisions are being made about which projects to write up and which ones not to. As a grad student and postdoc, when deciding which things to write up first, I generally focused on the studies that I thought were the most interesting. I certainly thought it was important to have publications in top journals (and by “top” I mean journals such as Ecology, AmNat, and Evolution), and so whether a manuscript had a shot at one of those journals did influence my thinking on where to place it on my priority list. At the same time, if I manuscript didn’t have a shot at a top journal, I still hoped to get it published at some point (possibly by collecting additional data, or by aiming for a lower impact journal). I just didn’t prioritize it as highly.

Now, as a faculty member, my lab generates even more data, and I have even more responsibilities (especially teaching and service). How do I prioritize manuscripts now? At this point, it is based on who is the lead author. If it is a grad student or a postdoc, that manuscript moves to the top of the priority list. (This recent post by BabyAttachMode suggests not all PIs prioritize this way.) Within that group of high priority manuscripts, it’s more or less first come, first served. In the past year or so, working on those manuscripts has basically taken up all of the time I have available for working on manuscripts. The unintended side effect of this is that manuscripts that do not include students or postdocs as coauthors are currently languishing near the bottom of my manuscript to do list, and it makes me wonder if/when I will get back to them. In this case, results are going unpublished due to lack of time. I really wish this wasn’t the case, but I’m not sure of what to do about it.

This means that some of the data we’ve collected – some of the things we now know based on work done in my lab – are not available generally, which is wasteful. Is this inevitable? Does it mean that everyone who currently has a file drawer of data (or, more likely, folders on their computer containing unpublished data) should take some sort of hiatus from doing science until they’ve cleared the backlog? I don’t think that’s likely to happen, but I don’t know what the right answer is.

So, readers, my questions for you: How do you decide which manuscripts to work on first? Has that changed over time? How much data do you have sitting around waiting to be published? Do you think that amount is likely to decrease at any point? How big a problem do you think the file drawer effect is?

Related posts:
How do you decide authorship order? (by Jeremy)
How to decide where to submit your paper? (also by Jeremy)

Sexual Harassment and Rape in Field Sciences

Kate Clancy and others are doing very important work to bring the problem of sexual harassment and rape while doing fieldwork to people’s attention. The link above gives Clancy’s summary of the work, and this one at ScienceInsider gives another summary. Clancy and colleagues have surveyed bioanthropologists, and, according to Clancy’s blog post, found

59% of our sample reported [sexual harassment], with women having a three times greater risk than men. 19% of our sample reported sexual assault, but while women did again have greater numbers, the male sample size in this group (n = 1) was too small to test this statistically.

Equally disturbing is this quote from Clancy’s post:

For both harassment and assault, we found most of the perpetrators were individuals superior in the hierarchy than the victims– so for instance, a faculty member harassing a graduate student.

Kate’s post is excellent, eye-opening, and disturbing. I think it is something all ecologists should read.

The survey is now open to other disciplines. “Ecology” is not specifically listed, but options include “Biology”, “Zoology”, and “other”. You can find the survey here.

Hopefully this work will open up discussions of the problem of sexual harassment and rape – and ways to address the problem – to fields beyond bioanthropology, including ecology.

How often do you travel?

Something I’ve been thinking a lot about lately is how much work-related travel I feel okay with, and this has me wondering about the work-related travel of Dynamic Ecology’s readers. This is surely influenced by lots of factors, including career stage, family responsibilities, and enjoyment of travel.

For me, I traveled fairly little as a grad student. I went to one meeting per year, for the most part (sometimes two). I went on the job market as a postdoc, and so did a lot more traveling then. As a new faculty member (before I had kids), I still went to 1-2 meetings per year, and then usually did a couple of seminar trips on top of that. Over time, the number of seminar/talk invitations has increased, and I generally say yes, because I find it enjoyable to visit other departments, meet with people, etc. And, to be honest, sometimes I say yes even if I feel a little overwhelmed with travel, because I’m pre-tenure. But my tenure dossier goes in this summer and I now have two kids, so I know that I need to cut back some on travel. I’ve agreed to three work-related trips for the summer and two for the fall already. That’s a lot!

Right now, I’m trying to decide what is the right level of travel for me at this career and life stage, and I’m wondering what others do. Currently, I think I might start aiming for one trip per semester (including summer), which would mean 3 trips per year.

So, my questions for you:
1. How much work-related travel do you do?
2. What is your career stage?
3. Do you have children or other major family responsibilities (e.g., care of a parent or sibling)?
4. If you answered “yes” to 3, has that influenced how much you travel?
5. What do you think is your ideal level of travel?
Please answer in the comments!

Where’s Meg? (and REU opportunity)

Just a quick post: I recently had a baby, hence my blogging hiatus. We’re doing well – but taking care of a newborn and dealing with lab stuff means no time left over for blogging. Hopefully I’ll be back before too long!

One of the other things I’m working on right now is finding an REU for this summer. The exact project is flexible depending on the research interests of the student, but will focus on host-parasite interactions, using Daphnia as a model host. Check out this webpage for more information.

Women in Ecology and Ecolog Discussions (Updated!)

This was going to be a Friday links contribution, but I got a little carried away, so now it’s a whole post on its own. It is inspired by the newest round of discussions about women in ecology that have been occurring on the Ecolog listserv. For whatever reason, Ecolog seems to periodically feel the need to tackle the question of whether women are qualified to do ecology. For example, last spring, there was a long, disheartening (to me, and I know to others as well) discussion that started when a graduate student asked, quite reasonably, for recommendations for carriers to use with her baby when doing field work. Some people replied with their suggestions, but others replied with admonitions against bringing an infant into the field. One of my favorite replies came from  Lis Castillo Nelis, who pointed out (correctly, in my opinion), that, if a colleague over 50 had asked for gear recommendations, people would not have replied with warnings about the potential for heart attacks in the field; she then suggested that perhaps we should also assume that the original poster is an intelligent adult who has already evaluated the risks and benefits, and, being a competent adult, had come to the conclusion that bringing her baby into the field was the right decision. The discussion quickly devolved into one related to women and parents in ecology; the full threads can be found here, here, and here. Some of the most troubling replies, in my opinion, came from Clara B Jones, and were summarized and countered in this post on work-life “balance” from Prof-Like Substance.

With that as background, when I was skimming through the “topics of the day” list in the ecolog daily digest while eating my oatmeal a few days ago, it caught my attention that there were several posts with the heading “Gender issues”. These had spun off from a thread on “A Graduate Student’s Guide to Necessary Skills for Landing a Job”; unfortunately, that thread isn’t grouping nicely in the archives, so you’ll have to go here and then scroll down. Once again, Clara B Jones plays a key role in this thread. Just as important, though, is the way the discussion evolved from there. This newest round of discussions of women in science have led to great posts from Prof-Like Substance and Jacquelyn Gill. Both of them tackle a key point: how/whether to respond when statements like this are made.

How have I responded? Last spring, I wrote the original poster off list to say that I was dismayed at the turn the discussion had taken and that it is indeed possible to have an academic career in ecology with children and to be happy while doing so. I also took the discussion over to twitter; I’m pretty sure that’s how PLS originally found out about it. But I didn’t engage on Ecolog. I imagine it would be a very frustrating experience. But that thread was definitely in my mind when Jeremy approached me about writing for this blog, and when I agreed despite knowing that I would be insanely busy this year (with, among other things, a move to a new university, teaching a giant course, new baby on the way, and submitting my tenure dossier this summer). This is a topic I hope to cover more in the future (when I magically get more time – that will happen, right?!) For this round on ecolog, I once again haven’t replied to the list, but once again brought it to twitter. And now I’m writing this post.

But there is another way that I “reply”, in a sense: I try to do good science. I haven’t been as active with the blog recently in part because we are trying to get a bunch of papers out the door, to get new experiments going, and, in general, to do good science (along with departmental service, some guest lectures and seminars, etc.) It’s not a direct reply, of course, but I do think it’s a reply of sorts. As a postdoc, when I first started reading data about bias against women in science [pdf] (that we – including women – have), rates of women with children getting tenure (as compared to men with children or to women who do not have children), etc., I found it totally depressing. And at first I was pretty bummed about it. But then I decided to be a bad scientist and ignore the data. Instead, I focused on women I knew who had children and did good, interesting science. Keeping those women in mind was very encouraging to me.

I now receive emails from grad students and postdocs indicating that, for them, I am now a person that they look to as an example that one can have a tenure-track career with children. This also comes up quite often when I give seminars – especially this semester when I am very obviously pregnant. It’s a little scary – and definitely humbling – to me that some people view me as a role model for this sort of thing, but I can also very much understand how they feel (in terms of needing to have particular people in mind to use as examples that it can be done). Unfortunately, when they ask what the magical secret is to having children and a tenure track career, I feel stumped. I know that, for me, having a partner who fully shares parenting and household responsibilities is essential. And I also know that, while I may look like I have achieved the mythical work-life balance from the outside, that’s only if you take some sort of long term average. Certainly last fall was very much skewed towards work (which, again, was only possible because my husband took on extra responsibilities at home); once I have baby #2, things will skew towards life for a bit. So, I agree with PLS that, really, work-life balance means not dropping the same ball too many times in a row (or, I would add, not dropping a particular ball at an especially crucial stage).

So, to finally get on to those links I had in mind: I wanted to link to PLS’s and Jacquelyn’s posts, as I already did above. I also wanted to:

1. remind people that we ALL have biases. One reply to ecolog indicated that Clara B Jones couldn’t be sexist because she’s a woman. The data – including in this recent paper – show that women are biased against women in science, just as men are. As I’ve posted on here before, I have found Project Implicit a really interesting tool towards beginning to evaluate and think about the biases that we all have.
UPDATE: In the comments, Karen Lips pointed to this video of a talk by newly elected AAAS president and Yale astrophysicist Meg Urry. I haven’t had a chance to watch it yet, but Karen reports that it is full of data and case studies on the ways we all show subtle biases. Sounds very interesting!

2. remind people that we still have problems with women leaving science and academia. This is not simply an issue of demography that will work itself out as current grad students move on to academic positions. This post by Curt Rice focuses on why women leave academia, and why universities should be worried.

3. point to some biology- and ecology-specific data. For example, there is this preprint of a new paper in BioScience that focuses on reasons why women leave the biological sciences (especially as compared to medicine, where women are retained as physicians). There is also this interesting way of looking at data on gender & publications, where you can zoom in to look at Ecology & Evolution. If you do that, you will see that women are quite underrepresented as first- and last-authors on papers.

So, to conclude: Do I think the comments of a few posters on ecolog represent all ecologists? Of course not. But it does serve as a reminder that there are still real problems to tackle related to women in science in general and in ecology in particular. There are no easy solutions, of course, but hopefully making sure that the issues remain in the spotlight will help remind people that there is a problem, and that we need to work towards a solution.

Thoughts on Applying to Grad School (for prospective students and their mentors)

This year, I’m serving on my department’s Graduate Admissions Committee. So far, this has involved going through 105 applications (which, not surprisingly, takes a really long time) and meeting with the full committee to discuss each of the applicants, deciding whether to invite them for interviews.

What I’m writing here is aimed both at people who are applying to graduate school in ecology and evolutionary biology AND at the people who mentor those students (which includes grad students, postdocs, techs, and faculty – or, in other words, most of the readers of this blog). Others have recently written on this topic (Joan Strassmann and Joshua Drew spring to mind); I am intentionally not re-reading their posts before writing this, to try to keep this more limited to my impressions. (Also, I’m on a plane without wifi access right now.) I am writing this with a prospective student in mind as a reader, but, again, I think the information should be useful to people who mentor undergraduates (grad students, postdocs, faculty, etc.); this may well be a case where many students don’t know what they don’t know, and their mentors can help them learn more about the process.

Something that should be done well before considering applying to graduate school is to get relevant research experience. I can’t stress the importance of research experience enough. The most impressive applications came from students who had in-depth research experience. Students who had no research experience were not competitive. A few thoughts related to this:

1. Jeremy has extolled the virtues of attending a small college if you want to go on to a career in research. I agree that there are benefits, but there are also drawbacks. (Sorry, Jeremy.) One of them is that research opportunities might be more limited in a student’s area of interest. Another is that, for some smaller schools (but definitely not all), it can be harder for me (as someone reading through a ton of these applications) to interpret the letters. If a student from a small regional school with which I am not familiar has a letter writer who says s/he is in the top 5% of students s/he has mentored, that information is not particularly useful to me, since I don’t know much (or anything) about the student body at that school.

2. I found it particularly impressive if the applicant had gone to another institution to get research experience. I should add that I didn’t do this as an undergrad, in part because I was somewhat late in coming to this whole ecology and evolution thing. But a letter from someone outside a student’s home institution looks really good (in part, that person seems less biased).

3. Getting extensive research experience is good, but bouncing around to new labs every 4 months for a few years is not a good strategy. You don’t want to look like you are unfocused or can’t stick with a project.

4. Getting research experience in a field as close to the one an applicant wants to focus on for grad school is especially important. If nothing else, it shows us that you have some idea of what you are getting into.

Other things that applicants need to work on over the long term:

5. Obviously you want to do well in your classes. Straight A’s are definitely not essential. One C in Calc II isn’t going to kill your application. But a lot of C’s in science courses can be a problem.

6. Take relevant courses. Some applicants had very few E&E courses. That could be okay if they had made up for that in another way. But we do need to know that students will be able to TA courses in ecology and evolution. First year grad students already have a ton to do, even without needing to learn a lot of introductory ecology and evolutionary biology.

7. GREs: some people care about them. I don’t. I apparently was fully convinced by the workshop I attended on evaluating graduate applications, where they showed us data indicating that GREs correlate strongly with being a white male from a relatively advantaged background. They also showed data suggesting that GRE scores aren’t very predictive of success in grad school. One of the few things that GRE scores to predict (albeit weakly) is time to degree – but there the correlation is positive. Some people pay a lot of attention to GRE scores. Others mainly look to see that they aren’t bad. So, you definitely want to do your best on your GREs (which you were going to do anyway), but don’t let weak GRE scores keep you from applying to grad school.

Focusing now on things that can be done right around when you apply:

8. In most ecology and evolutionary biology programs that I know of (including the one at UMich), you need to line up a prospective advisor BEFORE arriving. In many other fields, there is a culture of students doing rotations in their first year or two before choosing a lab. Rotations are NOT generally done in ecology and evolution (though, of course, there are always exceptions). This means it’s really important to contact a prospective advisor before applying. If there is no prospective advisor for a student, s/he is not admitted. It certainly wasn’t a fatal flaw if someone hadn’t contacted a prospective advisor ahead of time, but it definitely looks better if you do, and will make it so that the prospective advisor can more meaningfully comment on your application.

9. Say who you want to work with in your research statement, and say why you want to work with him/her/them. If you identify multiple people, they should be people who work on a similar area. It looked very strange if an applicant identified, for example, me and a plant systematist. If you don’t specify a particular person, the right person may not look at your application. We try to figure out who might be good potential mentors based on the research statement, but sometimes it’s pretty hard to tell.

10. Be specific in your research statement. I don’t expect you to have your dissertation all mapped out, but you should give a clear idea of what you want to work on and why. We also looked for a match between the level of research experience and the depth of the statement – applicants who had a masters (or who were finishing up their masters) were expected to have a more sophisticated statement.

11. You need to do more in your research statement than simply catalog what you have worked on to date. The most compelling research statements gave clear descriptions of previous research projects – ones that indicated that they really understood what they were doing and why – and then when on to say what they wanted to work on in grad school and why they wanted to do it.

12. Regarding letters of recommendation:
a) get them from science faculty – do NOT ask grad students or postdocs for letters, don’t ask your French professor, and definitely do not ask the person who runs the camp where you work in the summer.

b) if you’ve done science research with someone, definitely ask them. If you do not have a letter from someone like your REU mentor, that will be a big red flag (especially if you have a letter from your French professor instead). In rare cases, a person has so much research experience that there are more people who can write letters than there are letters that need to be written. In that case, go with whoever you think will write the strongest letter.

Having said all of the above, I will add that there was no single way to get on the invite list. Some people who had less-than-stellar undergrad GPAs got invitations based on having done really in depth research and having strong letters from their mentors. Some applicants had been doing research non-stop since high school, others came to it later, and still others had gone off to do something else (e.g., teaching) for a few years before applying to grad school.

I’m looking forward to meeting the people we’ve invited – it will be interesting to meet these people in person, after spending so much time going through their applications!

Why I Use Clickers, Part 2

Earlier, I talked about my use of clickers in Intro Bio (and previous courses). That post focused on reasons to use clickers (with some links to articles related to the underlying pedagogy) and on the reasons I find clickers useful.

Now that the semester is over, I can still say that I’m very glad that I used clickers. I plan on expanding my use of them the next time I teach Intro Bio. As expected based on the mid-semester survey we did of students, comments from students on the end-of-semester evaluations indicated they had liked this aspect of the course and felt like clickers helped them learn.

Let’s assume that some of you are now considering using clickers. What to do now? My first suggestion is to talk with colleagues at your school who are using them and/or with people at your school’s center for teaching. At UMich, that is the Center for Research on Learning and Teaching. They are more than happy to help faculty figure out how to use clickers. As was discussed some in the comments on the original post, my impression is that most schools have a particular type of clicker that they are set up to use. This is good for the students, since it means that they don’t need to buy lots of different clickers for their different classes. And it’s good for faculty, because it means you don’t need to be a pioneer and figure everything out on your own. At Georgia Tech, I got the clicker set up from their version of CRLT (which is called CEISMC), and then a colleague gave me a quick run through on how to set it up and use it in class. At UMich, I contacted CRLT and they told me about a training session they had the next week. I went, got a clicker, learned how to use it (it was a different system than I’d used at Georgia Tech), and was off and running. It was not nearly as big a deal to implement as I thought it would be.

Another major point that I didn’t properly address in my original post – but that is a big one to consider – is whether and how to tie clicker participation/performance with the course grade. There are various options, including:

1. Having clicker usage be totally voluntary (that is, no points tied with clicker use). This is what I did this past semester in Intro Bio. The main incentive for students to use clickers is because it helps them learn and keeps them engaged. A major disadvantage of this, though, is that, even if students know that clickers help with learning, sometimes that isn’t as motivating as knowing that your grade is affected by something. I feel certain that attendance would have been higher if clicker participation directly affected student grades; and, since I think there is value to attending class, increased attendance would be a good thing, in my opinion.

2. Incorporate clickers into the grading scheme, but just based on participation (that is, not based on whether they get a question right or not). This is what I did when I used clickers in my Ecology course at Georgia Tech. Students find this very motivating – attendance was a lot higher in the semester when I used this approach than it was in previous semesters. A disadvantage of this approach is that you have to do more to manage the clickers. There will always be a student who accidentally took her roommate’s clicker, or whose clicker battery died that morning, or whatever. When that happens, they will come to you. I tried to avoid having this be a major issue by making it so that they got full clicker credit if they answered a certain percentage of the clicker questions – say, 90%. Then they could have a few days where they forgot their clicker, the battery died, or whatever, and it wouldn’t affect their grade. I think that reduced their stress a lot.

3. Incorporate clickers into the grading scheme, with a subset of points awarded simply for participating, but full credit given only if they correctly answer the question. An advantage of this is that it makes it the most likely that students are fully engaged and trying their best on the questions. A downside is that it increases the stress level associated with the clickers. It also might change the type of question you want to ask. If credit is just linked with participation, it’s okay to use clickers to help students realize what they don’t know, and to ask really hard questions that almost no one gets correct. But if they are graded, students will get grumpy in a hurry if the questions are too hard.

4. Use clickers to give in class quizzes or exams, with no points for participation. I’ve only done this a couple of times, and only in my Ecology class at Georgia Tech (where, for the most part, I followed model 2 above). In this case, it was easy to do because the clicker system at GT allowed students to enter numerical answers, too, so I could have them do problems and enter their answers. But this is something I used pretty sparingly.

One major potential issue with 2-4 is the issue of cheating. When I first sat in a class to observe how clickers worked, I sat in the back row. The student sitting next to me apparently didn’t realize I was a faculty member, and pulled out three clickers. He proceeded to answer each question on all three clickers. Clearly that is not the goal of clickers! (And, yes, the student was completely shocked when I identified myself as a faculty member at the end of the class and took the clickers from him so that we could figure out whose they were and deal with it properly.)

One thing I did to try to discourage that behavior is to occasionally give a written pop quiz in class after I gave a clicker question, where they had to hand it in in person to me or a TA at the end of class. I told students I would do this at the beginning of the semester, so it’s not like I was being super sneaky. My hope was that it would help keep honest students honest. It appeared to work, because the semester I did that, I never had a student who had answered a clicker question but wasn’t there to turn in an exam. Clearly this approach isn’t perfect, and it won’t work in every type of class, but it was one way to try to combat the problem. If readers have other thoughts on how to deal with this problem, I would love to hear about them in the comments.

That rounds out my thoughts on clickers for now. Overall, I remain supportive of their use, and, as I said at the beginning, I plan on continuing to use them in lecture classes in the future.

Are any of you using clickers for the first time this semester? If so, how is it going?

The study that almost made me quit grad school

This is the second “story behind the paper” post from me. In the first, I focused on the paper that Ecology rejected that later won the Mercer award from ESA. In this one, I will focus on another study that involved a lot of angst at one point but that has a happy ending.

To set the scene: I was a third year graduate student. I had spent most of my first two years thinking that I was going to focus on hybridization for my dissertation. But it wasn’t proving to be that interesting, and, after learning more about parasites, I decided to switch to working on them. The summer before my third year of grad school and the fall of my third year were going to be my first big field season working on parasites. I planned a study where I would look, among other things, for effects of parasites on population dynamics. The plan was for me to do really intensive sampling of the population dynamics in a set of 6 lakes. My plan involved sampling each of the six lakes every 3 days (at least in the summer, when temperatures were warm and dynamics fast). On top of that, I was doing a larger survey of a set of 18 lakes, collecting data on selective fish predation, and monitoring habitat use via day/night Schindler series. A critical thing is that parasites cannot reliably be detected in Daphnia after preservation, so all samples (even the ones collected at 1 AM) needed to be counted live.

My original plan was to try to focus on Metschnikowia, a yeast parasite that we knew was in some of our lakes. While Metschnikowia has been a central focus of my research in the past 10 years, that first year happened to be a really bad year for Metschnikowia, with very low infection prevalences. But it didn’t matter, because there were tons and tons of bright red Daphnia, and I knew that A) there is a parasite, Spirobacillus cienkowskii, that turns Daphnia bright red, and B) Daphnia dentifera, my focal species, doesn’t produce hemoglobin (there is a paper somewhere that says this, though at this point I can’t remember which it is). So, red Daphnia must be sick Daphnia. And they were everywhere!

Except, it was more interesting than that. They weren’t truly everywhere: when I used a Schindler trap to collect samples at 1 meter intervals throughout the water column, I could see that the red Daphnia weren’t migrating vertically. Differential habitat use associated with infection – this was neat! Pretty much all the D. dentifera were deep during the day; at night, the red ones mostly stayed deep, while the clear ones migrated to the surface waters. I started forming lots of hypotheses: maybe the parasite was manipulating host behavior, perhaps to avoid fish predation? Maybe it was just that Daphnia that stayed deep were exposed to parasites in the sediments more – that is, maybe it was not that sick Daphnia don’t migrate, but that Daphnia that don’t migrate are more likely to get sick. I was trying to figure out how to test as many of these possibilities as possible, while doing all of the above work, too. And I was doing lots of day/night Schindler series to document the pattern really well.

One other thing I decided was important to do was to get data on the fitness impacts of infection. To do that, I set up flasks of red D. dentifera and control flasks of clear ones, so that I could see just how virulent this parasite was. I checked my flasks daily. For days. Then weeks. At some point, it seemed odd that none of the infected ones had died. I decided to pull them out of their flasks to see what was going on. They were all perfectly clear and healthy looking. Seeing them under the scope, realizing they were healthy, it became immediately apparent what was going on. They had never been infected. They were producing hemoglobin, despite the report that D. dentifera does not make hemoglobin. That explained why there was such a clear pattern of “infection” in the field – red animals were deep, because only animals living in the deep, poorly oxygenated habitat need to make hemoglobin.

I was devastated. I had spent the previous months exhausting myself and really excited about all the data I was generating for my thesis on parasitism. . . only to find out that I had almost no data on parasites. I did have a little data – there were several samples where it had seemed like there were two types of red things (in the end, these were truly infected animals and hemoglobin-producing animals) and I had counted those separately. But, really, I had very little data, and by this point I was most of the way through the field season in my third year of school.

I remember very clearly just leaving the lab and going to sit by Gull Lake. That morning, before I figured out what was going on, I had seen that Mike Lynch had posted an ad to evoldir, looking for a lab manager. I thought, “Well, that’s it. I’m in my third year, and I have no data. I’ll just quit school now and go and be Mike’s tech. That wouldn’t be so bad.” And, for a few days, that was my plan.

Fortunately, Alan Tessier, my advisor, happened to be visiting during this time. (He was a rotating program director at NSF at the time.) He did a good job of talking me off the proverbial ledge, helping me focus on the data that I did have that was useful, and helping me come up with a plan to salvage the field season. (In the end, it was salvaged. If it had taken me a few more weeks to figure out what was going on, it probably wouldn’t have been salvageable.)

It took a few months, but at some point I started to get curious about the data I had accidentally collected on hemoglobin production. I mean, it had been clear that there was a really strong pattern there in terms of habitat use. After playing around with the data for a bit, it became clear that there was something really neat going on: hemoglobin production was a marker for habitat use, and showed that there was intraspecific variation in habitat use in D. dentifera. Most strikingly, taking advantage of hemoglobin as a marker of habitat use, I could see that there was a clear negative relationship between the density of deep-living D. dentifera and their main competitor, D. pulicaria, which also occupies the deep part of lakes. That pattern was obscured if you just looked at overall D. dentifera density and D. pulicaria density. At some point, we started getting pretty excited about the data, and jokingly started to refer to it as Thesis 2. There were times when Thesis 2 seemed more promising than Thesis 1 (on parasitism).

It took me a long time to get around to writing it up, but, in the end, the hemoglobin study was published in Freshwater Biology. And, I’m proud of it. It’s a case where I did not have #overlyhonestmethods, and so it isn’t clear from reading the paper that it was an accidental study. But I find myself frequently telling the story behind this paper when I meet with grad students, because I think it’s important to recognize that things do not always go as planned, and that it’s possible to recover from what seem, at the time, to be pretty major setbacks.

Now that I’m back in the Midwest, it would be possible to follow up on this story. I hope we do. I think there’s a lot of potential to use this system to study the community consequences of intraspecific variation. But this time, we will study hemoglobin production and habitat use intentionally.