How bad is the loss of NSF dissertation improvement grants?

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Last week, NSF announced they have stopped awarding DDIGs – the Doctoral Dissertation Improvement Grants in the divisions of Environmental Biology and Integrative Organismal Systems.

How bad is this decision? In the words of Jane Lubchenco:

Continue reading

Useful science communication resources

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Inspired by my own endeavours in science communication and an informal talk I gave to my department, I started to think about offering a course. There isn’t anything like that for PhD students so I went through a few easy hoops and got approval to give a short course on science communication. We finished up the meetings last week and I thought it might be useful to collect and share all the information in one place. Keep on reading if you’re interested in running your own version of such a course or if you are looking for information on topics in science communication. Continue reading

There are lots of opportunities for grad students to learn how to teach

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In my last post I complained that grad students don’t generally get taught how to teach in grad school, despite the fact that they are (arguably) there to be trained for a career that requires them to teach. Thanks very much to everyone who commented! As a result of both the comments and getting more information about TA training at my current university, I’ll now write about how there are in fact a lot of opportunities for grad students to learn how to teach. You just have to put a bit of effort into going out and finding them. Continue reading

Why aren’t grad students taught how to teach?

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The biology departments at the university I attended for my MSc and the one I just started at for my PhD both have courses for new grad students that are meant to be an introduction to the skills they will need to be successful in grad school and beyond. One is called “Basic skills for a career in science,” which is pretty self-explanatory. The other is called Professional Skills Development “Philosophy and methods” and is “intended to be a forum for students to enhance their current skills and understanding of how to do ‘good’ science and to discuss some issues that they will encounter as scientists.” One used to be optional and is now mandatory; the other used to be mandatory but is now optional. (updated)

The course I took included writing grants and abstracts, making scientific posters and presentations, effective data presentation, time management and advisor-advisee relations, the publication process, and ethics. The one I haven’t taken appears to cover somewhat similar topics. Neither mentions teaching, which I’m pretty sure is an essential skill for a career in science. Continue reading

Academic Hazing

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A recent conversation* on twitter made me think about academic customs. The conversation centered on PhD comprehensive exams (PhD candidacy in the US system that happens about halfway through the PhD) but applies to all gate keeping parts of a PhD (or Masters) program. These can vary a lot between countries, universities and even departments (I wrote about the defence a while back). But this conversation was basically about how these hoops/tests can drift towards a hazing function rather than a learning or career building function.

Let me just get my opinion out from the first. I don’t think hazing is useful, respectful or professional. Full stop.

But one of the things that struck me is the difference between true hazing and an experience that can feel like hazing or at least slightly ritualized torture but in hindsight really isn’t. I’m one of the lucky ones it seems in that my experience was more the latter. Continue reading

Thoughts on the PhD defence

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Last Friday there was a PhD defence in our department and Terry’s post about open defences in the USA got me thinking about the different cultures surrounding PhD defences. The first thing that came to mind is how different they can be, from country to country, university to university and even from department to department within universities.

A few axes in which defences can vary:

  • defence versus none
  • an open versus closed defence
  • external examiner(s) versus none
  • student presentation versus none
  • external examiner gives a presentation on  or not
  • official book printed prior to or after your defence
  • who makes the decision (a unbiased committee or one that has been involved throughout your PhD)

So, why so much variation?

Well clearly, some variation might come about from outside sources, such as the law. Much of the variation might simply arise from traditions of the university and culture (we’ve always done it this way…). But this got me thinking about the purpose of a PhD defence. In our teaching it is always better if we have defined goals and learning outcomes of the activities we do and a PhD at its core is fundamentally a learning process. Being a bit new to the other side of the equation, I don’t really have any idea about how much discussion is given to the purpose and expectations of the defence in departments. Are there clear objectives? What is the point? What does it all mean? These questions and many more may drive the form of the defence across universities. Clearly there could be a difference in the form of a defence where the main purpose is to evaluate the quality of the work versus where it is seen as a time point to gather your various projects into a cohesive story (and presumably the evaluation of the work has been done earlier, e.g. in the decision that you’re ready to defend). [Update: scroll down to the comments for a much more detailed examination of the purpose of a PhD defence by Paul Klawinski]

When I started writing this post I realised that I don’t have strong opinions about how a PhD defence ‘should’ be. It seems to me that there are lots of different and equally good ways of awarding PhDs. What constitutes ‘good’ will likely vary a lot based on how the entire program is formulated. But seeing different traditions now in Sweden has opened my eyes to some of the benefits of doing things differently. And thinking more seriously about PhD defences has gotten me thinking about the broader potential impacts of the event beyond being able to call yourself Dr. afterwards.

First maybe I should lay out my own experience on the table so that my biases are in the open. I have a degree from the USA and so my defence went something like this: I handed in my dissertation to the committee that I had throughout my PhD a few weeks before the day, I gave a seminar (50 mins) on my research to the department and answered questions, then I went into a room with my committee and talked with them. They sent me out of the room and talked about who knows what while I waited (the time went on forever…). Then they brought me back and congratulated me (hooray!). I think I might have been told that an open defence was illegal somewhere in the planning but honestly with juggling a baby, an international move and finishing up, that time is a bit hazy for me….

What I liked about the process that I went through is that it gave me a defined goal to work towards for ‘finishing’ writing. In my department you only print bound copies of your dissertation after the defence. That means there is still more to do and you need to incorporate changes that your committee suggests. But the seminar gave me a chance to communicate with my department and let them know what I had managed to do in my time there. So although it was a little stressful, I appreciated having a defence rather than not. I think I benefited from doing mine. It was the first full length seminar on my work, for example. And getting through your defence is definitely something to celebrate.

I’m not sure what it would have been like to have an open defence. The ones I’ve been to so far here in Sweden are much more focused on the details of the papers included in the dissertation. To be honest, I didn’t really feel like I was defending anything in my ‘defence’. In fact, my yearly committee meetings were always much harder and challenging than my defence and that wasn’t a bad thing. It made sure that my progress was going in the best possible direct rather than challenging details after it was too late to change them. So my committee and I talked very little about my dissertation but they focused more on big picture ideas. It was a really a great conversation that got me thinking about my place in science and how I could contribute. I think I’m still learning that but it was a wonderful broadening conversation. I was definitely asked some challenging questions in that closed-door portion of the defence, but I wasn’t actually defending my specific papers as I’ve seen more recently. Even in my former department, I think what constitutes the defence varies a lot between students but I appreciated the form mine took.

One thing I think I might have missed out on with an internal defence with my committee is that I didn’t get a chance to have an in depth conversation about my work with someone from the outside. Watching the defences here in Sweden, I am beginning to appreciate how valuable that can be. I know of a number of people who ended up doing a post-doc with their external reviewer. It seems like a great way to meet and interact with a leader in your field and also gives them a chance to get to know you. I also know of another example of a paper that came out of discussions during the defence. Generally the process seems like a great way to connect with someone and in our department the external examiner also gives a presentation about your work to put it in a broader context. In a way, this gets them to be an advocate of the student and really get to know their work. So even if future collaborations aren’t an outcome, you’ve had someone new think deeply and carefully about your work. However, if I had an external examiner for my own defence, I don’t think I would have had the same kind of interesting conversation as I did. It could have been just as good but likely pretty different.

So overall, I can see benefits to different PhD defence styles but unfortunately you can’t do everything…

What are the traditions at your department? Are there active discussions about what could be broader outcomes of the process of the PhD defence (besides a point where you can pass/fail a student)? And please share more extended outcomes of the PhD defence process! I’m sure I’ve only scratched the surface in this post.

Natural history is important, but not perceived as an academic job skill

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This post is a reflection on a thoughtful post by Jeremy Fox, over on Dynamic Ecology. It encouraged me (and a lot of others, as you see in the comments) to think critically about the laments about the supposed decline of natural history.

I aim to contextualize the core notion of that post. This isn’t a quote, but here in my own words is the gestalt lesson that I took away:

We don’t need to fuss about the decline of natural history, because maybe it’s not even on the decline. Maybe it’s not actually undervalued. Maybe it really is a big part of contemporary ecology after all.

Boy howdy, do I agree with that. And also disagree with that. It depends on what we mean by “value” and “big part.” I think the conversation gets a lot simpler once we agree about the fundamental relationship between natural history and ecology. As the operational definition of the relationship used in the Dynamic Ecology post isn’t workable, I’ll posit a different one.

As a disclaimer, let me explain that I’m not an expert natural historian. Anybody who has been in the field with me is woefully aware of this fact. I know my own critters, but I’m merely okay when it comes to flora and fauna overall. I have been called an entomologist, but if you show me a beetle, there’s a nonzero probability that I won’t be able to tell you its family. There are plenty of birds in my own backyard that I can’t name. Now, with that out of the way:

Let’s make no mistake: natural history is, truly, on the decline. The general public knows less, and cares less, about nature than a few decades ago. Kids are spending more time indoors and are less prone to watch, collect, handle, and learn about plants and creatures. Literacy about nature and biodiversity has declined in concert with a broader decline in scientific literacy in the United States. This is a complex phenomenon, but it’s clear that the youth of today’s America are less engaged in natural history than yesterday’s America.

On the other hand, people love and appreciate natural history as much as they always have. Kids go nuts for any kind of live insect put in front of them, especially when it was just found in their own play area. Adults devour crappy nature documentaries, too. There’s no doubt that people are interested in natural history. They’re just not engaged in it. Just because people like it doesn’t mean that they are doing it or are well informed. That’s enough about natural history and public engagement, now let’s focus on ecologists.

I honestly don’t know if interest in natural history has waned among ecologists. I don’t have enough information to speculate. But this point is moot, because the personal interests of ecologists don’t necessarily have a great bearing on what they publish, and how students are trained.

Natural history is the foundation of ecology. Natural history is the set of facts upon which ecology builds. Ecology is the search to find mechanisms driving the patterns that we observe with natural history. Without natural history, there is no such thing as ecology, just as there is no such thing as a spoken language without words. In the same vein, I once made the following analogy: natural history : ecology :: taxonomy : evolution. The study of evolution depends on a reliable understanding of what our species are on the planet, and how they are related to one another. You really can’t study the evolution of any real-world organism in earnest without having reliable alpha taxonomy. Natural history is important to ecologists in the same way that alpha taxonomy is for evolutionary biologists.

Just as research on evolution in real organisms requires a real understanding of their taxonomy and phylogeny, research in real-world ecology requires a real-world understanding of natural history. (Some taxonomists are often as dejected as advocates for natural history: Taxonomy is on the decline. There is so much unclassified and misclassified biodiversity, but there’s no little funding and even fewer jobs to do the required work. If we are going to make progress in the field of evolutionary biology, then we need to have detailed reconstructions of evolutionary history as a foundation.)

Of course natural history isn’t dead, because if it were, then ecology would not exist. We’d have no facts upon which to base any theories. Natural history isn’t in conflict with ecology, because natural history is the fundamental operational unit of ecology. Natural history comprises the individual bricks of LEGO pieces that ecologists use to build LEGO models.

The germane question is not to ask if natural history is alive or dead. The question is: Is natural history being used to its full potential? Is it valued not just as a product, but as an inherent part of the process of doing ecological research?

LEGO Master Builders know every single individual building element that the company makes. When they are charged with designing a new model, they understand the natural history of LEGO so well that their model is the best model it can be. Likewise, ecologists that know the most about nature are the ones that can build models that best describe how nature works. An ecologist that doesn’t know the pieces that make up nature will have a model that doesn’t look like what it is supposed to represent.

Yes, the best ecological model is the one that is the most parsimonious: an overly complex model is not generalizable. You don’t need to know the natural history of every organism to identify underlying patterns and mechanisms in nature. However, a familiarity with nature to know what can be generalized, and what cannot be generalized, is central to doing good ecology. And that ability is directly tied to knowing nature itself. You can’t think about how generalizable a model is without having an understanding of the organisms and system to which the model could potentially apply.

I made an observation a few months back, that graduate school is no longer designed to train excellent scientists, but instead is built to train students how to publish papers. That was a little simplistic, of course. Let me refine that a bit with this Venn diagram: 

nathistvenndiagram

What’s driving the push to train grad students how to publish? It doesn’t take rocket science to look at the evolutionary arms race for the limited number of academic positions. A record of multiple fancy publications is typically required to get what most graduate advisors regard to be a “good” academic job. If you don’t have those pubs, and you want an academic job, it’s for naught. So graduate programs succeed when students emerge with as their own miniature publication factory.

In terms of career success, it doesn’t really matter what’s in the papers. What matters is the selectivity of the journal that publishes those papers, and how many of them exist. It’s telling that many job search committees ask for a CV, but not for reprints. What matters isn’t what you’ve published, but how much you have and where you’ve published.

So it only makes sense that natural history gets pushed to the side in graduate school. Developing natural history talent is time-intensive, involving long hours in the field, lots of reading in a broad variety of subjects. Foremost, becoming a talented natural historian requires a deliberate focus on information outside your study system. A natural historian knows a lot of stuff about a lot of things. I can tell you a lot about the natural history of litter-nesting ants in the rainforest, but that doesn’t qualify me as a natural historian. Becoming a natural historian requires a deliberate focus on learning about things that are, at first appearance, merely incidental to the topic of one’s dissertation.

Ecology graduate students have many skills to learn, and lots to get done very quickly, if they feel that they’ll be prepared to fend for themselves upon graduation. Who has time for natural history? It’s obvious that ecology grad students love natural history. It’s often the main motivator for going to grad school in the first place. And it’s also just as obvious that many grad students feel a deep need to finish their dissertations with ripe and juicy CVs, and feel that they can’t pause to learn natural history. This is only natural given the structure of the job environment.

Last month I had a bunch of interactions that helped me consider the role of natural history in the profession of ecology. These happened while I was fortunate enough to serve as guest faculty on a graduate field course in tropical biology. This “Fundamentals Course,” run by the Organization for Tropical Studies throughout many sites in in Costa Rica, has been considered to be a historic breeding ground for pioneering ecologists. Graduate students apply for slots in the course, which is a traveling road show throughout many biomes.

I was a grad student on the course, um, almost 20 years ago. I spent a lot of my time playing around with ants, but I also learned about all kinds of plant families, birds, herps, bats, non-ant insects, and a full mess of field methods. And soils, too. I was introduced to many classic coevolved systems, I learned how orchid bees respond to baits, how to mistnet, and I saw firsthand just how idiosyncratic leafcutter ants are in food selection. I came upon a sloth in the middle of its regular, but infrequent, pooping session at the base of a tree. I saw massive flocks of scarlet macaws, and how frog distress calls can bring in the predators of their predators. I also learned a ton about experimental design by running so many experiments with a bunch of brilliant colleagues and mentors, and a lot about communicating by presenting and writing. And I was introduced to new approaches to statistics. And that’s just the start of it the stuff I learned.

I essentially spent a whole summer of grad school on this course. Clearly, it was a transformative experience for me, because now I’m a tropical biologist and nearly all of my work happens at one of the sites that we visited on the course. Not everybody on the course became a tropical biologist, but it’s impossible to avoid learning a ton about nature if you take the course.

The course isn’t that different nowadays. One of the more noticeable things, however, is that fewer grad students are interested, or available, to take the course. I talked to a number of PhD students who wanted to take the course but their advisors steered them away from it because it would take valuable time away from the dissertation. I also talked to an equivalent number of PhD students who really wanted a broad introduction to tropical ecology but were too self-motivated to work on their thesis to make sure that they had a at least few papers out before graduating.

In the past, students would be encouraged to take the course as a part of their training to become an excellent ecologist. Now, students are being dissuaded because it would get in the way of their training to become a successful ecologist.

There was one clear change in the curriculum this year: natural history is no longer included. This wasn’t a surprise, because even though students love natural history, this is no longer an effective draw for the course. When I asked the coordinator why natural history was dropped from the Fundamentals Course, the answer I got had even less varnish than I expected: “Because natural history doesn’t help students get jobs.” And if it doesn’t help them get a job, then they can’t spend too much time doing it in grad school.

Of course we need to prepare grad students for the broad variety of paths they may choose. However, does this mean that something should be pulled from the curriculum because it doesn’t provide a specific transferable job skill? Is the entire purpose of earning a Ph.D. to arm our students for the job market. Is there any room for doing things that make better scientists that are not necessarily valued on the job market?

Are we creating doctors of philosophy, or are we creating highly specialized publication machines?

There are some of grad students (and graduate advisors) who are bucking the trend, and are not shying away from the kind of long-term field experiences that used to be the staple of ecological dissertations. One such person is Kelsey Reider, who among other things is working on frogs that develop in melting Andean glaciers. By no means is she tanking her career by spending years in the field doing research and learning about the natural history of her system. She will emerge from the experience as an even more talented natural historian who, I believe, will have better context and understanding for applying ecological theory to the natural world. Ecology is about patterns, processes and mechanisms in the natural world, right?

Considering that “natural history” is only used as an epithet during the manuscript review process, is natural history valued by the scientific community at all?  Most definitely it is! But keep in mind that this value doesn’t matter when it comes to academic employment, funding, high impact journals, career advancement, or graduate training.

People really like and appreciate experts in natural history. Unfortunately, that value isn’t in the currency that is important to the career of an ecologist. And it’d be silly to focus away from your career while you’re in grad school.

But, as Jeremy pointed out in his piece, many of the brilliant ecologists who he knows are also superb natural historians. I suggest that this is not mere coincidence. Perhaps graduate advisors can best serve their students by making sure that their graduate careers include the opportunity for serious training in natural history. It is unwise to focus exclusively on the production of a mountain of pubs that can be sold to high-impact journals.

We should focus on producing the most brilliant, innovative, and broad-minded ecologists, who also publish well. I humbly suggest that this entails a high degree of competency in natural history.

Does being a “Jack-of-all-Trades” impede or facilitate an early-stage academic career?

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This is a guest post by Andrea Kirkwood. She is an Assistant Professor in the Faculty of Science at UOIT, and you can follow on twitter at @KirkwoodLab

Jack-of-all-Trades, Master of Nothing

Recently a topic near and dear to my heart came up on Twitter. Allison Barner (@algaebarnacle) was live-tweeting from the Western Society of Naturalists meeting, and posted the following tweet:

This tweet caught my attention, because it touched on an issue that caused some anxiety for me as I completed my doctoral degree. At the time, I thought my graduate school training was too broad, straddling several disciplines (ecology, phycology and microbiology) across very different systems (lakes vs. wastewater lagoons). Some may view this is a strength, bringing to mind the classical view of what a Doctor of Philosophy should be. Yet at the time I was completing my Ph.D. (circa 2002), I suspected that my skill-set was viewed as old-fashioned, and was being supplanted by the next-wave of sexy techniques. I also felt like I knew a little about a lot of things, but an expert in nothing. Sound familiar? I attempted to rectify this by choosing to do my first post-doc in a lab where I could learn a sexy technique (i.e., applying molecular methods in phylogeny and diversity assessment). Becoming adept at a special skill had to be the right move because several of my peers were getting faculty positions based on their “special skills”. You’re a quantitative ecologist, we’ll hire you! You use the latest molecular technique, we’ll hire you! It seemed that if you had a specific, timely skill-set, you were highly marketable. The message was that Jack-of-all-Trades (JOAT) need not apply.

Still, I wasn’t personally satisfied with just learning the latest sexy tools. When an opportunity came up to do something completely different for my next post-doc, I jumped at the chance. Not only would I get to work in a new system (rivers of the Canadian Rockies), but learn more about theoretical ecology. Here I was expanding my academic repertoire yet again to the detriment of specialization. One could blame my lengthy sojourn as a post-doc (5.5 years) on not having an obvious niche research area. Nonetheless, my academic breadth made it possible to apply to a broad swath of jobs, and end up on interview short-lists. Based on some feedback though, it was apparent that search committees either found it difficult to pigeon-hole my research area, or didn’t think I quite fit the specialization they were looking for.

I was very fortunate to be hired by a new university in Canada that didn’t have the luxury of hiring specialists. They needed someone who could teach a broad selection of biology courses, as well as have an applied research angle to fulfill their STEM mandate. This was an extremely rare kind of faculty hire at a Canadian research university. In the United States, this is apparently the typical hiring emphasis for small, teaching-focused universities as vouched by Terry McGlynn (@hormiga) on Twitter:

Although I breathed a sigh of relief upon securing a tenure-track faculty position, I then had to fret about the views of research-funding committees. I know several colleagues who were denied funding, in part, because they could not convince the reviewers they were expert enough. To add to my angst, the Great Recession had begun and the current government was slashing and burning research funding. Ironically, it was these dire funding circumstances that showcased the strengths of being an academic JOAT. I quickly discovered that I could access a broader pool of funding sources compared to my specialist colleagues. I secured grants in ecology, conservation, and biotechnology. Now one could argue this approach allows funding agencies to direct your research program (i.e., tail wagging the dog), which is true to some extent. Ultimately, the researcher has to decide to what degree they will chase money this way, and perhaps only use this funding model during the lean years. In my mind, if it can keep your lab running and let you and your students continue to do science, it certainly has its merits.

So admittedly up to this point, I have provided a narrative that asserts my credentials as a card-carrying JOAT. What does that mean exactly? Am I really a Master of Nothing? The very nature of grad school is to become a specialist at something, at least compared to the general population. Along the way, grad students and post-docs acquire specialized skills in their fields, some more than others. Serendipitously, I became a leading expert on Didymosphenia geminata (aka “Didymo” or “rock snot”) during my second post-doc, and will unabashedly credit D. geminata for saving my career (a blog entry for another day). Does this mean I lose the right to claim the JOAT label at all?

Brett Favaro (@brettfavaro) sums it up nicely by stating:

Brett cites an interesting opinion piece by Parsons (2012) in the Journal of Environmental Studies and Sciences that certainly extolls the virtues of a broad skill-set in an interdisciplinary field like Conservation. However, it is not enough to know about a lot of things, but to also have a deep understanding of them too. Thus, one needs to have a complement of specialized skills, perhaps at the “expert-lite” level and not necessarily “leading-expert” level. Would you accept your oncologist or cardiologist being “expert-lite” in your treatment options? Probably not, but I think this approach lends itself to disciplines such as ecology and environmental science, where a broad and somewhat deep skill-set can be an asset in research collaboration and communication.

Offering an intriguing new layer to this discussion on the JOAT phenomena in academia, Britt Koskella (@bkoskella) pondered on Twitter:

Britt cites an article by Wang et al. (2013) that assesses the role of gender in influencing career choices in STEM vs. non-STEM fields. The authors determined that individuals with high ability in both math and verbal skills tended not to pursue STEM careers. In contrast, individuals who had high math skills, but moderate verbal skills tended to choose STEM careers. This suggests that having a broad-skill set (i.e., being a JOAT) offers more career options, and thus an increased capacity to choose a career outside of STEM. What is also notable about these findings is that the group with high math and verbal ability included more females. This raises interesting questions about the underlying cause(s) of fewer women than men entering STEM careers. Is it ultimately about inherent freedom to choose a career path rather than ability?

Overall, I think it is clear that there is no clear-cut answer to the question posed in the title of this blog post. In my own personal experience, I can say that being an academic JOAT likely helped or hindered me at different points along my career path. Based on the unique experiences of every academic, I imagine there is a multitude of views on the JOAT phenomenon, and whether it matters or even exists. I think it exists, but is defined by perception on a sliding-scale.

References

Parsons, E. C. (2012). You’ll be a conservationist if…. Journal of Environmental Studies and Sciences, 1-2.

Wang, M. T., Eccles, J. S., & Kenny, S. (2013). Not Lack of Ability but More Choice Individual and Gender Differences in Choice of Careers in Science, Technology, Engineering, and Mathematics. Psychological Science, 24(5), 770-775.

Why I don’t take high school students into my lab

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Once in a while, I am approached about taking on a high school student over the summer. I always say no, for the same reason that I turn away most premeds: they want research “experience.”

Bungee jumping is an experience. Discovering that you’re allergic to seafood is an experience. Going backpacking in Europe is an experience. I don’t provide research “experiences” for students; I train scientists. I’m a scientist and a university instructor, not an unpaid private tutor.

High school students want to look awesome so that they can get into a fancy university. That has nothing to do with why I am paid to work for the State of California, so I’ll take a pass. But I don’t let the high school students off with a simple “No, thank you.”

The primary purposes of my research lab are to get research done and to train scientists. My lab doesn’t have room for tourists having an “experience,” because there is only space for researchers. I turn away high school students because they take resources (time, space, roles) away from the students who really need it and deserve the opportunity. These students that want to join my lab are the kind that end up winning science fairs because of privileged access to university resources.

I have another reason for turning away the high school students that come to me in search of a research experience.

The high school students who have sought research experiences have two common denominators: The first is that they’re wealthy. They attend either an expensive prep school, or attend public school in a district with million-dollar homes and a well-endowed foundation supplementing the inadequate funding provided by the State of California. These high school students think it’s perfectly normal – perhaps even laudable – to seek out research experiences at the local university that trains undergraduates.

The second common denominator among the high school students who ask to volunteer in my lab is they never, ever, will even consider attending my university, CSU Dominguez Hills.

When high school students ask me for a slot in my lab, the first thing I do is ask them about their college plans. They name schools with pricetags that would clean out the bulk of my salary. I then give these students a heavy dose of righteous indignation. I slightly raise my voice. I get visibly perturbed. I want them to know that I’m offended. It’s not a show, but I don’t make much effort to hide my genuine umbrage:

Do you think it’s acceptable to come to my lab and ask me to spend taxpayer dollars giving you free research training?

If getting research experience in my lab is good enough for you as a high school student, then why isn’t it good enough for you in college?

Why do you think that you might deserve a space in my lab over students who are enrolled at Dominguez Hills? Presumably you’re hard-working and smart, but how does that entitle you to special opportunities over the hard-working and smart students who have chosen to come to Dominguez Hills?

If this campus not good enough for you in two years, how is it good enough for you now? That’s a serious question and I’d like an answer. Please answer. I’m not joking. Why don’t you want to come to this university?

I have no tolerance for people who think that prep school students can slum around my low-income university to get free research credentials, as a way to further their access to elite institutions that my students are unable to access. Moreover, these people wanting a spot in my lab expect that it’s somehow part of my job to provide this training for free to students who have already chosen to opt out of the state university system.

This particular form of entitlement is offensive to my values and to my students. Even asking for the opportunity to join my lab as a high school student, while simultaneously ruling out the possibility joining as an undergraduate, shows how little these students and their families value education as a public good. I refuse to be their tool.

While not in my lab, in labs all around the country, wealthy high school students are getting high quality research training at universities while the majority of the nation’s public school children are now living in poverty and qualify for subsidized school meals. If I were to use my lab at CSU Dominguez Hills to provide research opportunities to the 1%, I’d only worsen this tragic failure of our nation.

I’m not inherently opposed to taking on a high school student, but I’ll be damned if I take an opportunity away from an underprivileged student who truly needs it and transfer it to one who comes from a position of privilege.

I’m not going to be an instrument of the upper class by perpetuating the heritability of educational and economic disparities.

Of course, if some parents of a high school student pony up the $2 million for an endowed chair at my university, I’d be pleased to reopen a conversation on the topic.

Teaching Tuesday: Incorporating primary literature into courses

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As academics, we spend a lot of time reading primary literature (although we often feel it is not enough). It is a real skill to learn to decipher how journal articles are written and how to read them effectively. One barrier is the language and learning a discipline involves learning the language. However, even if you know all the words and concepts, the format of papers is different from most everything else we might read.

From a survey I did of ecology teachers*: many think that reading primary literature is important in teaching ecology. I included answers for reading textbooks as a comparison. I wasn’t surprised that there was a bit less emphasis on textbook reading but it is obvious still a useful resource for teaching ecology. I certainly also had the impression that reading journal articles was important as an undergraduate but I wasn’t quite sure how to do it.

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So if you are using or want to use primary literature in an undergraduate class, how should you go about it? There are perhaps 101 ways to effectively use journal articles as teaching tools. The link is a detailed article which outlines what you can use primary literature for, how to identify good articles, challenges with using primary literature and how to overcome them and finally how to assess learning. There is tons of good advice there, so if you are looking for ways to incorporate the literature but are unsure how, it is a good place to start. Here’s a more personal account of one professor’s approach to integrating the primary literature into a class. I like the idea of building up understanding and directing the students so that their reading is productive.

I found when I was an undergrad, I basically learned how to read primary literature by doing it a lot. My first attempts felt a bit like looking through a fog. I would attend discussion sections where we’d read papers and there were a few students presenting each time. I don’t think I learned anything until I presented a paper myself. Before that, it seemed that every time I missed the main point of the paper.

So when I started running my own section for a writing intensive group of an ecology course as a teaching assistant, I realised I didn’t want my students to be stuck in the rut I had been in. We were to discuss many papers during the semester and I couldn’t wait for the end for all of them to be comfortable. I also didn’t want the focus to be on me (the section was meant to facilitate their independence), so I didn’t want to break down every paper for them. Inspired by discussions in a class about how to teach writing that I was taking, I came up with a simple plan to get students to overcome any issues they might have with discussing primary literature.

The methods were simple**:

  1. Choose recently published papers on topics that students will be able to understand without much background.
  2. Describe the general layout of a paper and how to read it (be brief to give students as much time as possible to read).
  3. Break students into pairs, and have each pair read a different paper for 10-15 minutes.
  4. Allow the pairs to discuss the paper for ~5 minutes.
  5. Give each pair 2-3 minutes to tell the class what the paper was about.

As instructors, we often discuss how to approach reading a paper but we rarely address the intimidation that many students feel when reading scientific writing. Often students get so bogged down in the details of a paper that they can’t see the forest through the trees. So I wanted students to avoid getting caught up in details they didn’t understand (e.g. statistical methods are particularly prone to this). My hope was that I could help students overcome their fears of both reading primary literature and then having something to say about it. I have to admit the first time I tried this I was terrified. I knew that I could briefly read a paper before a discussion and contribute if I needed (sometimes happened more than I’d care to admit as a grad student) but I wasn’t sure how they would do. I wasn’t asking them to describe in detail the paper and I specifically choose papers that were relatively easy to understand the main points.  I hoped this was enough. To my relief, it worked!

Student comments on this activity:

  • “An invaluable skill! Keep encouraging this. Thank you!”
  • “Was useful because it helped me think about the essential information”
  • “Speed reading will be a skill I keep-usually I spend so much time I get confused in the readings.”
  • “Great. Not only familiarized us with various ecological concepts and studies but helped with the ability to skim/read scientific papers for pertinent information.”
  • “Speed reading was helpful in understanding take away messages from papers—it is a great skill.”
  • “very useful”, “relevant and important”, “practical”

I was able to describe paper reading very briefly in the beginning of section because my students had all been exposed to reading primary literature in previous courses. If this is the first time your class has seen a journal article, maybe more effort would be needed here. At the end of class I would also take a few moments to point out what they couldn’t pick up from their quick reading. For example, I’d ask some directed questions to the teams about the articles that I was pretty sure that they wouldn’t have picked up on. My goal was to get them to be able to figure out the main story of a paper and realise that they could understand that without knowing all the details. But I didn’t want the take away message to be that fully reading a paper is never necessary. The rest of the semester we discussed many papers and they also needed to read and summarize papers working up to their final proposal so there was many opportunities to teach them about how to read and learn from the literature.

I was lucky because I had small groups of students to work with. I can see ways in which you could modify the activity for larger groups. Maybe having them share what the paper is about in smaller groups rather than the whole class, for example. Mainly I think it is important for them to have to say something about the paper. It is through being forced to quickly summarize the points that students actually learn to ignore all the detailed methodology that they tend to get caught up in. We can tell them to focus on the big picture but most of them (including me as an undergrad) won’t. By not giving the time to get bogged down, they quickly learned to look at the big picture. I was really pleased that both times my students were able to use this experience throughout the course. The discussions were more lively than I’d ever had before as a TA and I did very little talking.

In general, I think incorporating primary literature is important for learning in the sciences. Whether it is exposing students to the papers themselves or their products in an deconstructed way, efforts we make to teach students how to read the scientific literature can only expand their understanding of what science is all about. Now whether they should be able to access the literature after their degree is complete is a whole another debate…

*if you are new to Teaching Tuesdays, I’ve been doing a series of posts that have derived from a survey I distributed broadly to ecology teachers earlier this year. If you are interested in knowing more about what ecology teachers are up to, you can read more here (intro, difficulties, solutions, practice and writing).

**after doing this activity with my students in a couple of courses I remember reading something similar. I think the article was maybe in an ESA newsletter (Eco 101, perhaps) but my cursory searching hasn’t found it. Although I had thought I downloaded it, there is nothing on my hard drive either. If you know of this article, please send me the link! (Update: link, thanks Gary)

How a research institution can mentor undergrads better than an undergraduate institution

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More doctoral students emerge from small liberal arts colleges than from the undergraduate populace of research institutions.

This is a point of pride held by liberal arts colleges, that market themselves as the best place to go if you want to become a scientist receiving a Ph.D. from a big-name research institution. Demographically, they’re correct.

Are small teaching schools better equipped to train undergraduate researchers better than big research institutions? I don’t think so.

In practice, liberal arts schools are far better at producing high quality researchers, but it’s not because of any inherent property of liberal arts schools. Some could argue that the curriculum itself might matter – that’s a discussion for another time – I’ll spend the rest of this post thinking about the single reason that people identify about what makes liberal arts schools a special place for budding researchers.

Here is the standard reasoning: Teaching schools provide students with the opportunity to have close professional interactions with their professors. Students in labs in small teaching institutions benefit from direct mentorship from the PI, which will more likely result in a higher quality research experience, better insights into how to do research, and greater opportunities to own their own research projects, enabling them to present at major venues and eventual publication as undergraduates.

How true is the preceding paragraph? It’s a straight-up fact that students at small teaching campuses are more likely to do more original research of their own working with their PI. And, if an undergraduate arbitrarily selects a research lab to join, then they’d probably end up getting a better experience at a teaching institution.

But, though this trend is real, research institutions have tremendous potential for training undergraduates. Without providing any additional resources, any research institution can be a top-notch training ground for undergraduates. After all, there is nothing inherent about teaching institutions that makes them better at training researchers.

There is nothing magical about having the PI as your direct mentor that will make you a better researcher and help you get into a better grad school. Looking closely at what supposedly makes a teaching institution better for training undergraduate researchers – close involvement with the PI – I see a massive handicap.

All of the literature on research mentorship says that the relationship is most successful when the mentor is just a little above the mentee in research experience. Even though the PI is a better academic expert and has mentored more, the Ph.D. student and the postdoc are in a position to be more effective as mentors.

The best mentoring arrangement is a multi-level team, in which the early undergrad works with a senior undergraduate, who then works with a Ph.D. student, who works with a postdoc as well as the PI. The PI knows everyone personally, and spends some time with the undergrads, but the graduate students are the better formal mentors. (A colleague of mine at a research institution recently tried to kick one of her own undergrad researchers out of the lab, because she didn’t recognize her. That’s not good.)

I suppose a young PI can connect more easily with students, but as we get older, then the nature of the relationship evolves. Add on a few years, and the gap between the PI and the student grows. Even if the PI is affable, and might truly understand the perspectives and thoughts of the students, it would be silly to ignore the fact that our students can’t relate to us and that we can’t relate to our students, even if we were once in their position. No matter how much time I spend with my students, now matter how similar our backgrounds are, the fact of who I am limits my ability to serve as a model. I can do all the right things in the mentoring process, but if a grad student did all of the right things, it would be even better. (And for my students from underrepresented groups, having a mentor from the same group is particularly powerful.)

I really like most of my students. I enjoy their company, and over time some have become good friends of mine. But, let’s face it, there’s a big gap. I’m older, have a kid and am married, and we don’t have that many overlapping interests. While I try hard to be transparent, I recognize that I seem like an enigma in a bunch of ways. (For example, earlier this summer one of my students was totally surprised that I use torrents to watch a couple TV shows. He just thought this was outside my realm for some reason.) I didn’t go to grad school in the middle ages, but things have changed since I’ve been there, and this is true for anybody who is at least halfway to tenure. If I try to discuss grad school with my students, I’m not nearly as credible or powerful as the same information coming from a current graduate student.

My position of authority makes me a less influential mentor.

I don’t want to overgeneralize from my experience, but I doubt that I’m alone.

You might be thinking, “Do your students really have to relate to their mentor to have an excellent research experience, and move their career to the next level?” Not necessarily. But I think it really helps. Especially for students who aren’t able to visualize themselves as capable of excelling in graduate school, a proximate model is an essential part of the mentoring process. Having seen my undergrads interact with doctoral students on a regular basis, it’s clear to me that without this kind of opportunity, that my students would missing out, big time.

Having a student know that the path has been blazed in front of them by other students, like them, matters. If students see other students throw themselves into research with great passion, they are more likely to allow themselves to get that excited. Of course, the same was true for me. But now, I’m an old bald dude with kids, and I get really excited about research, but in a different way. I can’t serve as a model for my students, even if I tried.

While grad students might not have the same authority and skill set as the PI, they can offer things that the PI can’t. This is exactly why a multi-level mentoring scheme is the way to go. The PI can choose to become involved when it is wise, and step back and focus on other things when the grad student has things under control.

Research institutions have grad students, but this doesn’t mean that they deliver great research experiences for undergraduates. While the personnel are available for a multi-level mentoring system, in many labs the system is nonfunctional because undergrads are often treated as serfs. I know many R1 labs that that are exceptional for undergraduates who work with graduate student mentors. However, I’m aware of far more labs that do not focus on making sure that undergraduates have their own research experience and are able to focus on building their own academic identity. In general, undergraduates in research institutions that receive their own project (as a piece of their mentor’s work) are the exception rather than the norm.

As for the mass production of Ph.D. students from small liberal arts colleges, I would bet that the outcome is a done deal even before the students enroll in college. The social and economic class that produces doctoral students is the same caste that is able to send students to fancy private liberal arts schools. Yes, there are scholarships and financial aid. But even if you look at small liberal arts colleges that heavily emphasize economic and ethnic diversity, they simply can’t match the diversity of the nation’s populace because, simply, most people can’t afford it. As long as the average cost of a liberal arts college is more than average cost of research universities, of course a higher proportion of doctoral students will emerge from liberal arts colleges.

How do I get my own students a multi-level mentored experience? Well, I don’t have that happen inside my lab on a day-to-day basis. I may have Master’s students around, but I usually have undergrads that are more seasoned than my grad students. That experience helps, but the way I really bring in graduate student and postdoc mentors is by having my students conduct their research in a hub of collaborative activity during the summer at a field station: La Selva Biological Station, in Costa Rica. There, my students build strong relationships with scientists from all over with different levels of experience, and these bonds typically stay tight after they leave the field station. Sometimes their projects become collaborations with grad students and postdocs at other institutions. I like that a lot, for a bunch of reasons.

If multi-level mentoring is important for the success of undergraduates, then what does this mean for you?

If you’re in a research institution: Postdocs and grad students should become genuine mentors and give undergraduates the time and resources to have their own students, and supervise them properly.  Faculty at research institutions should support their lab members, not just in the process of research but also in the process of mentorship. Don’t exploit undergraduates as trained monkeys. If you want someone to be an unthinking data-generating machine, then hire a technician. If you take an undergraduate to do “research,” then do actual research with them. Your own research agenda is easily split up into several smaller questions. Hand one of those questions to your undergraduate researcher, and learn how to mentor them. Give them the same support that you expect to receive from your own research advisor. Yeah, it’s not easy, but it will pay off for both of you in the long run.

If you’re at a teaching institution: Seek routes for multi-level mentoring in the lab. At a minimum, the undergraduates with more than two years of experience in the lab should be given the chance to actively supervise new students. Ideally, you can develop relationships with colleagues in other institutions with graduate students and postdocs. Find a way for your undergrads to become friends with doctoral students. I don’t know how to make this happen, and it varies with institutional context and geography, but from where I sit, it’s an ingredient that really promotes success. (For starters, you can bring students to smaller national meetings where they can build relationships with the students of your colleagues.)

I don’t have a big specific solution to the problem, but recognizing the fact that we as faculty are inherently flawed mentors is a start, and recognizing that the lack of graduate students at teaching institutions isn’t a strength, but a weakness, of the mentorship process.

Model systems don’t work at teaching universities

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Many research strategies, developed inside large research institutions, don’t work well in small teaching-centered institutions.

One of these strategies, I suggest, is the use of a biological model system.

What do I mean by model systems? Any system, used in multiple laboratories, that has been optimized for a broad variety of lab investigations. I’m thinking of zebrafish, Drosophila, mice, C. elegans, E. coli, Arabidopsis, and honey bees. For the ant people, this includes Temnothorax.

It might seem counterintuitive that model systems can prevent you from getting research done in a teaching-centered institution. After all, these model systems were developed, in part, to make research easier and remove methodological barriers experienced by those working in a broad variety of organisms.

Even though model organisms are easy to work with, have lots of standardized methods, and a massive bank of potential collaborators, the costs and risks of working with a model system far outweigh the benefits and the opportunities.

My initial thought on this topic came from observation. I don’t see much research on model systems getting done within teaching institutions. I also have seen a variety of people, who work on model systems in teaching institutions, experience substantial challenges that have kept them from getting work done. Here’s a list of problems that I’ve seen crop up for those using model systems in teaching institutions.

  • The low-hanging fruit has been picked. In model systems, the things which are a combination of easy, obvious and trivial have already been done. That only leaves things which are either difficult, requiring particularly deep insight, or trivial.
  • Model systems have intense competition. In model systems, many labs compete rather than collaborate. A small lab in a teaching institution isn’t built to deal with this kind of competition. This doesn’t mean that you should avoid competition by working on minutia, but it also means that you should choose an avenue that has high pressure competition. As any ecologist will tell you, competition is an interaction which has a negative effect on both parties. (An economist will tell you the same thing, though it’s better for the consumer).
  • You might get scooped. The probability that someone is doing exactly what you are working on is higher in a model system.
  • Collaborating is difficult. The labs that run model systems typically have lots of routine methods happening like clockwork, run by technicians and students who have become specialized in the model system. If you’re working on this model system, you are not likely to be able to contribute anything of substance to a big lab, which could do the same thing much more quickly than you could offer. Collaboration is easier if you have a specific resource or skills that others want or need, and that’s harder from a teaching institution if you work in a model system.
  • You may become isolated. In the community of people working in model systems, if you have a small undergraduate lab you’re more likely to be overlooked by your peers. I’m not sure how or why this is the case, but it’s what I’ve observed on several occasions. Everyone I know who has worked on a model system wasn’t well integrated into the community of frenemies that works on the system. It’s hard to have a scientific impact if you are unrecognized by your peers.
  • The bar for evidence is very high. Peer review is more likely to be rough and demanding. People with model systems tend to be territorial, and especially if you’re not perceived as a competitor that can bite back with teeth, then at least one reviewer is likely to go the extra mile to find something wrong with what you’ve done.
  • The minimum publishable unit is greater. If you’re working in a model system, odds are that the big labs working in the field are able to heavily replicate their experiments, and sandwich multiple experiments together into a paper. This establishes a standard for a large volume of data in a paper. I’m not arguing that you should seek to publish as soon as you have enough data for any kind of publication. However, if you have a genuine, interesting, and cool finding and want to get it out for everybody to read, it’s a bummer to have others telling you that you that it’s ready for publication because you don’t have a mountain of data.
  • Maintaining colonies takes continuous effort. Mustering any kind of consistent student work in the lab is a success. You don’t want your success in long-term student research to be squandered on the maintenance of lab colonies of a model system. You want to work on a system in which students can dive in and collect actual data, rather than spending all of their time keeping critters fed, clean, reproductive and healthy. Also, you want to be free to disappear for long periods of time, and not chained to the lab to maintain your organisms.

So why would one ever work with a model organism? One great reason would be to provide lots of valuable hands-on laboratory experiences to students. But in my observation, this kind of approach is a poor recipe for completing original research in a teaching institution.

In my opinion, if we are giving students research training, that means we’re giving them research training. Which means that they’re doing research, and research is something that ends up in new findings that are shared with the scientific community. If you want to give a genuine research experience to students, then you need to regularly publish the work that you are doing. From my vantage point, it’s very difficult to do this while working with a model system in a teaching institution.

I have a couple other alternative explanations for the (perceived) phenomenon that researchers working on model systems in teaching institution have a harder time publishing their work. The first alternative is that I’m just wrong, and that my experiences or perceptions aren’t representative or accurate.

The second alternative is that less research is completed because of the use of strategies from R1 labs that don’t translate to a teaching institution. Most people at teaching institutions, who work on model systems, are continuing with their dissertation system, I think. The research approaches from a dissertation lab probably don’t translate well to a teaching institution. I haven’t spent much time inside the labs of teaching institution professors using model systems, so I don’t know how they run things on a day-to-day basis, and am not too sure about this.

Do you think that it’s hard to get research done on a model system at a teaching institution? Did you switch into one, or out of one, to get research done? Thinking about it?

Broader impacts ≠ reaching underrepresented groups

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When the National Science Foundation introduced the required “Broader Impacts” criterion, it took more than a little bit of explaining at the outset.

Several years later, most of us understand what a “broader impact” is: In some shape or form, the funded project affects society beyond the scientific findings. There are a lot of ways to approach broader impacts. How do we go about deciding which way to fulfill the broader impacts requirement?

Earlier this year, Nadkarni and Stasch answered this question quantitatively, by evaluating the broader impacts included in nine years of funded proposals within the Ecosystem Studies program. There were some interesting finds, but there is one that I want to single out in particular.

Only 11% of the broader impacts in these proposals specifically targeted groups underrepresented in the sciences.

That’s right, only 11% of the proposals had broader impacts targeting underrepresented groups.

When I think “broader impacts,” I first, and foremost, think of providing training and mentorship opportunities to students from underrepresented groups. I also think of outreach efforts targeting underrepresented populations.

That seems to be a relatively rare priority.

It doesn’t seem to be a big stretch to say that one of the major factors imperiling the future of scientific progress in the USA is that massive sections of our population – and the ones that are growing more quickly – are not interested in, or prepared for, careers in science. If you read every other piece of policy paperwork about science education, you’ll see that the country needs to open the pathway for careers in science to Latino and African-American students. It matters, big time.

But nobody’s doing it in their broader impacts. Doesn’t that strike you as odd?

There are so many possible reasons for this phenomenon, and I don’t want to speculate ad nauseum. Here’s one possibility, though: when people think “broader impacts” they actually do first think about targeting “underrepresented groups.” However, they don’t have a simple or effective route to do so.

How do you reach students from disadvantaged and underrepresented groups? You start with students who are in disadvantaged and underrepresented institutions. Which means that the people who are getting all of these grants funded to implement broader impacts, if not at a disadvantaged institution, should start reaching out.

Are you one of those who haven’t included underrepresented groups in your broader impacts? If so, could you leave a comment about what kinds of things could smooth the path? What do you think that NSF, and we as a community, could do to help researchers at institutions with lots of NSF grants (and relatively few disadvantaged underrepresented students) reach out to underrepresented groups?

Reference:

Nalini M Nadkarni and Amy E Stasch 2013. How broad are our broader impacts? An analysis of the National Science Foundation’s Ecosystem Studies Program and the Broader Impacts requirement. Frontiers in Ecology and the Environment 11: 13–19.

A method to develop scientists from underrepresented groups: Research Recruits

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The United States needs to develop more scientists from underrepresented groups. This post describes an approach I’ve developed that has helped me do this more effectively.

The United States has always been, and remains, a nation of immigrants. For a variety of complex sociological reasons, our nation’s scientists are principally being drawn from one pool of historic immigrants. Now, the demographics of the country are changing more rapidly than the culture of our scientific community.

The subset of the US population from which scientists are drawn is proportionally shrinking. If our nation is going to remain (or regain) global prominence as a research powerhouse, then we need to recruit scientists from the entire population of the country. We need to make more Latino and African-American scientists, particularly women, from these groups.

The nation needs to overcome the sociocultural divisions that inhibit students from a variety of cultural backgrounds from becoming scientists.

A few generations ago, all women were excluded from most career paths, but these restrictions also applied to the men in my family because of their heritage. My Irish and Italian great grandparents living in Brooklyn were members an underrepresented ethnic and religious minority subjected to substantial discrimination (the movie Gangs of New York puts this history into context). A hundred years ago it would have been laughable that a fresh-off-the-boat McGlynn could become respected science professor in the US. Now, my ethnic background is such a part of the mainstream that I’m now considered to be a member of the privileged class.

It’s now, literally, my job to build that kind of progress for Latinos and African Americans, ethnic groups that have a longer history in the US than my own ancestors. I work in a university that gives me the opportunity of training many of these underrepresented students, and I create avenues of opportunity for those who aspire to become research scientists.

For nearly all of my students, the concept of going to graduate school to become a scientist isn’t even on their radar. Most students are oriented towards careers as technicians in the medical, biomedical or biotechnological fields. Some are broadly interested in environmental science but more about on-the-ground conservation work rather than become a research leader in the field.

Nobody new has come to me and said, “I want to go to graduate school and become a researcher.” If I were to introduce this concept to students, most would be neutral or opposed to the idea, meet resistance from their families, and would be more oriented towards finding a 9-5 job right after graduation or seeking vocational training.

Research is not an easy sell, even though I have some students who I intuitively know right off the bat that they would both excel at, and relish, a career in scientific research. How do I make this happen? There are many books and articles written about the general approach. This post describes one specific practice that can enhance recruitment efforts.

In general, researchers are created by the placement of promising students in an immersive and amazing research experience. They also are made with the provision of proximate models (e.g., not an old white married professor with a family) to show them how possible it is for them to pursue this route.

How do you get students into immersive experiences with the right role models? How I can I, at an underfunded state university with scant research activity on campus, make this happen?

One of the problems in recruiting students from underrepresented groups into scientific careers is that most of this underrepresented population goes to high school and college in environments where it sucks to do science. These urban high-need schools are so focused on raising test scores in English and math that science is merely an afterthought at best.

It’s no wonder that our underrepresented students don’t want to become scientists. They’ve never done genuine science in school, and at our university, our labs are shabby and poorly equipped, and there are no big active research labs on campus, so they don’t have any idea what it looks like to do research.

If I want to make research scientists out of my students, I’ve got to them the heck out of Dodge.

I’ve got to get them to a place where serious research happens all over the place, surrounded by a multiethnic group of students that are one step above them in experience and aspiration. There’s lots of fun tinkering in my lab, but nothing that can inspire someone to make the switch towards a life in science.

I’m not going to bring these students to local research universities like UCLA or Caltech, or to well-endowed undergraduate campuses with great undergraduate research programs like Occidental or Pomona. That could, and does, work, but I’ve got what I think is a better plan.

I’m writing this post right now on a plane. The six seats in front of me are occupied by students from my university, and when they started college they were not planning to become scientists. I’ll wager that a few years from now, about half of them will be published authors and enrolled in a great PhD program in biology. This plane is heading for Costa Rica, and they’ll be spending either 2.5 weeks, or 2.5 months, doing research on trophic ecology in a tropical rainforest. (Their work supported by the NSF International Research Experiences for Students program, also the Louis Stokes Alliance for Broadening Minority Participation administered by NSF.)

The rainforest itself isn’t what makes the students become scientists. Instead, it’s the research environment located at the edge of this massive fragment of forest, called La Selva Biological Station. There, my students interact with undergraduates, grad students, and postdocs  from all over the US, Latin America and Europe. They hang out with people who are supremely excited about research, and they also see the social and ethnic diversity of scientists that is rare at most US universities. Many of my students speak Spanish at home, and at La Selva, they’re able to talk with research students from Latin America who are also native Spanish speakers. They see Latinos excelling at research, and it is inspiring.

What my students see at La Selva is something that I could never just explain to them: they can have a genuine future as a research scientist. If they love the research (and only some do), then this experience makes the avenue to success perfectly clear and obvious.

They know that it’s my job to clear the path for them, for the next few years, by bring them to conferences, making them published authors, and helping give them the skills they need. (You’ll be able to meet a bunch of them if you go to the Association for Tropical Biology and Conservation meeting this summer, by the way.) They know it’s their job to deliver the goods as well, by being productive members of my research lab, primarily as the engines of data creation.

I don’t necessarily need to schlep these students to the rainforest to give them that kind of immersive research environment. I think active biological field stations are the best for this kind of experience, and there are lots of these within the US. Some universities are great for this as well, especially for those whose research orientation is focused on what happens in the lab. I bring these students to La Selva because that’s my biological home where I’ve worked for almost 20 years. I work there because my undergraduate advisor brought me there, and she remains a top mentor and model for my work with students.

Bringing the right students to the rainforest became really difficult since I came to a university filled with students from ethnicities underrepresented in the sciences (in California, you can’t call Latino a “minority” after all). When I worked at schools filled with relatively wealthy students with northern European ancestry, I had no problem finding students who wanted go down and work in the rainforest for a few weeks for a few months. They could pay for it themselves, and they enjoyed the experience, though not so many of them enjoyed it enough to become scientists.

I was surprised when I got to CSU Dominguez Hills. I posted signs up all over the (dilapidated) science building which read:

SUMMER RESEARCH IN THE RAINFOREST. ALL EXPENSES PAID PLUS $4000 STIPEND. APPLY NOW!

Who wouldn’t want to do that? It turns out, nearly everybody.

I thought I’d be overwhelmed with applications. I didn’t get enough credible applications to fill my slots. The few applicants I had were hardcore premeds who I knew (from past experience) would never be won over to research, and I didn’t want to waste NSF’s money (nor my time) that way.

I eventually filled the slots, mostly with the right students, but it took a serious recruitment effort. The most frustrating part of the experience is that there were students who I knew well, who I was confident would enjoy and succeed in the summer rainforest research experience, but I couldn’t convince them to apply. It turned out that nearly all of my best potential candidates were the ones that I couldn’t convince to come along.

In hindsight, I shouldn’t have been surprised. Many of these students were closely tied to their families and had never been away from family for a week, much less two months. Also, though I could pay a full stipend, this amount couldn’t fully match the revenue they would be earning from summer employment. Third, many students were counting on taking summer school so that they could graduate in 5 or 6 years instead of 7 or 8 years (no, I’m not exaggerating. Welcome to the contemporary California State University).

I couldn’t pull a student away from home for a whole summer of paid research unless they were exceptionally untied at home and had a great degree of financial freedom, combined with an independence of vision or a particularly free spirit that would allow them to have an open mind to the future. There were students I wanted to take down for the whole summer, but I just couldn’t hook them.

So, what did I do? As the title of the post suggests, I created a new category of student researcher, which I called the “Research Recruit.”

Remember how I wrote that some of the students traveling with me joined me for just 2.5 weeks. They spend two weeks doing research at La Selva, and a few days on “cultural experiences” such as the beach, cloud forest, volcano expeditions, hot springs, museums and zip-lining before going back home. They don’t receive a stipend, but they do get all their travel expenses covered plus a little per diem. Nothing has to come out of their own pockets.

It’s not that hard to convince most students to leave for the rainforest for 2.5 weeks. They can take that much time off their jobs with enough advance warning, and even if they have overprotective family, they can escape and reassure them with video chats from abroad. Students can get someone to watch their pets for that long, if not the whole summer. While not many people apply as research recruits on their own initiative, when we seek out students who we think are a good fit and ask them to apply, then we get a large and high quality applicant pool.

The Research Recruits don’t run their own projects like the long-term students. They pitch in as research technicians on the projects run by the other students. They also are encouraged to tag along with other researchers on station, which gives them the chance to meet a variety of grad students from the U.S. and also gives them exposure to a variety of biological and research system. Exceptional ones might be invited to stay for the whole summer, if there is adequate funding and mentorship.

By hosting a short-term cohort of Research Recruits, I am able to give students a taste of field biology and a thrilling research community. We are able to entice a number of recruits to apply to, and plan for, a full summer of research abroad in the following summer. Some research recruits don’t return to the rainforest for a full summer, as they discovered that they are not field biologists, but they have emerged from the experience excited about research and some have wound up as researchers in other lab-oriented disciplines. Others have gone into careers in teaching, and their tangible research experience has enhanced their classroom teaching.

It is hard work to make a scientist out of a person whose background precludes scientific research as a genuine career option. It is a highly personalized process, and it takes building genuine personal relationships. It also takes multiple years. Not all of my “research recruits” become scientists, but some of them do. These students who wind up in grad school never would have committed to a full summer of research without having an initial taste of research. If I gave up on them because they were wary of a summer of dedicated research, then it’s likely that they never would have been turned onto scientific research as a career option.

Once our Recruits go home, then they can prepare for the next summer. They can talk to their families, arrange for someone to watch their dog, don’t mind quitting their job and get excited about the projects that they can do. The level of commitment required to leave home for the summer, for the purpose of an intangible and vague experience, is a high bar for underrepresented students. The Research Recruit experience lets students know what they would be doing for the whole summer, and gets talented students to be motivated to make the personal commitment.

Is an exceptional summer experience enough to turn a student into a lifelong scientist? It can be. The hard part is getting students to envision themselves taking part in an experience for one summer. If you bring Research Recruits into your program, you lessen the initial level of commitment and then you can identify those who will succeed in long-term experiences.

Underrepresented students are going to college at underrepresented universities, the campuses that are not actively participating in the research community. To diversify the sciences, you need to recruit students from these campuses. To do this, you’ve got to go through us – the faculty who work with these students on a day to day basis.

To bring students from these institutions into the fold, you can’t just offer amazing experiences and hope that the right students sign up. You’ve got to court them, and convince them that research is a viable avenue. You’ve got to build personal relationships.

You can’t just expect the best students to commit to full summer research experiences. Research ability and motivation may be independent from the ability to envision research as a career path. I wish every program that is trying to recruit students from ethnic minorities included a Research Recruit option, which would bring in not only more students, but also the best students who otherwise would not see research as an option in their future.

We have a high conversion rate from our Research Recruit program, and after doing this for four years, our challenge is that we have too many qualified students looking for full-summer slots. That’s not a bad position to be in, and it also helps us argue for greater levels funding for our programs.

If you don’t have enough talented students from underrepresented groups applying, consider inviting them for just two weeks. Build your research community from the ground up. There are so many amazing students from underrepresented groups at non-research universities that can be excellent scientists. Creating funded opportunities is only the start, you’ve got to court them. I humbly suggest that creating a short-term Research Recruit program is one successful tactic that is absent from most programs.

Drifting towards deadwood, or not: learning to use R (updated)

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Update 15 May 2013: If you’re a newbie to R and want to know where to start, the comments on this post are now replete with (what I surmise to be) wonderful suggestions. Of course learning in the presence of those who know R is best, but this is a great set of suggested resources regardless of your environment.

I’m not that old, but I already feel myself getting a little stale.

How did this happen? Well, I guess it’s because I’m a professor and this is just the default rate of entropy.

When I was an undergrad, one of our introductory bio professors was a kindly man who was the archetype of deadwood. He had a separate slide carousel for every lecture in his course. When it was his time to teach, all he did to prepare was to pull the carousel off of the shelf. He didn’t have any idea what he was going to say until he saw the slide appear on the screen. Then, he would say the same thing he’d been saying for that slide over the past 20 years. It was just so obvious. One day, the slide projector broke. What did he do? He cancelled class.

This kind of thing is even more common now than it was back then, because few people had so many carousels at their disposal. It’s just done with powerpoint.

I’ve worked hard to keep my teaching from becoming stale. And since I’m doing a lot of research, then I can’t get stale at doing research either, right? If only that were true.

I imagine that molecular biologists all had to learn the ropes at PCR as machines and reagents became commercially available, and then relatively cheap and efficient. Nobody’s out there doing allozymes for population genetics after all, I would hope. And the same is true for RNAi, and now with nextgen sequencing approaches to genomics. In my flavor of work, there isn’t as much required to stay current, but nonetheless I’m still getting behind. If only I could have the time to run to just to stay in place.

At least I’ve diagnosed this condition and can fight the entropy. Just I keep the dishes mostly clean in my house and I have the oil changed in my car on time, I’ve got to stay fresh as a practicing scientist too.  It isn’t easy.

This occurred to me, in part, when reading something that Joan Strassmann wrote (in the context of picking a good PhD advisor) that grad students are probably better at using R than their own advisor. I guess that’s the case in most labs, even if their advisors might have better statistical acumen.

If you’re a serious ecologist, nowadays, then R is an essential or near-essential tool. Here’s a confession: I’m useless with R. This is a problem. And it’s not a little problem, it’s a big problem.

I suspect that I’m not the only one in this boat, though I haven’t really heard anybody else admit to it. Every day that passes in which I still can’t use R, I’m not able to collaborate as effectively, the more reliant I am on others, and the less able I am to apply the most current tools to the experiments which I’m running. There is a single analysis that I should be able to do in R in an hour, that’s keeping me from submitting a manuscript that otherwise is pretty much done. That’s a problem.

Now, I’m not a statistical dunderhead. (I teach our graduate biostatistics class, but obviously teaching a class in something doesn’t mean you’re an expert). I design my experiments with specific tests in mind, and I choose ones that work, and I use model selection understanding the power and limitations of the approach. I understand frequentist vs. bayesian perspectives even though I don’t choose to say anything that would start a disagreement. (If you read my stuff, you can decide for yourself if I know what I’m talking about.) I guess you’ll probably just take me at my word that I’m not stupid when it comes to stats.

But there are a few analyses that I just can’t run easily, like NMDS or a GLMM. This is because I mostly use a powerful menu-driven version of SAS called JMP. It does nearly everything I want, and quite well. But there are a few analyses that I can’t run in JMP, which are becoming more and more relevant to the questions which I’m asking in my lab.

How did I get into this situation? Well, when do people learn R? In grad school. When I was in grad school, R was not the standard tool. Before then, I used SPSS on a mainframe (NO, not with punchcards) and a variety of easy-to-use programs on a Mac. (Statview was unparalleled for simple exploratory data analyses on Macs, and it was bought up by SAS and orphaned so that people would use JMP instead. The world has moved on without it.). By the time I was finishing up grad school in the late ’90s, R wasn’t in widespread use but it was ramping up. None of my fellow grad students were using it at the time, and I wasn’t behind the curve.

A few years later, while I was starting on the tenure track in the early 2000s, I put aside a little time to figure out R. That was a disaster and I couldn’t even get it to read my files. I had a few halfhearted attempts, but I couldn’t find the time. I looked into taking a short course, getting a book, but I didn’t have the time to make it happen. At this point, it wasn’t a critical failing, but I saw that more and more people were using R, and that I wasn’t one of them.

My lack of R mojo isn’t a teaching problem. Even if I was an R pro, I don’t think I’d use this in my course because the class is about understanding how statistics works and how to apply them, not how to use the software. I use JMP in the course because it is so easy to use, and I’m not going to waste instructional time on software tutorials. (We should have a separate class or seminar or experience that teaches students to use R, but it can’t fit in this class.) I’ve talked to people who teach with R in their courses, and they’ve reported that you either have to make it a course about learning stats, or learning R, but you can’t do both well with 45 hours of class time. Clearly, by using R you actually learn what you’re doing statistically, because that’s part of understanding coding. So I hear. But I’m not going to spend half of my time in class dealing with coding errors and stress when my students still don’t fundamentally understand probability, randomness and the actual nature of a null hypothesis.

While not a teaching problem, my lack of R mojo is a research problem. I am on it. I’ve been aware of this for a while, and I’ve found a way to deal with it.

For the last month, I’ve had sitting in my backpack wherever I go, what appears to be the exact resource I need: Beckerman and Petchey’s Getting Started with R: An Introduction for Biologists. From my quick browse, I feel mighty confident that using R like a pro is now only a matter of finding the time, and it doesn’t seem as insurmountable.

My hope is that, this summer, I find the time to actually remove the book from my bag and use it. This is the point in the narrative where I could explain everything I’ve done in the last month that would explain why I haven’t found the time to get to it, but you know the story. I won’t try to out-busy you.

This summer is already booked. Learning to use R to some degree of proficiency is going to take the amount of time that it would take to write a whole manuscript, or nearly write a whole grant. I have to decide which one of those things I’m not going to do to keep my skills sharp. Of course, I’ll be using R in the context of a manuscript. It’s just that this manuscript will take 2-3 times longer to write because of my R learning curve.

Maintenance isn’t optional. Learning R feels more like an engine replacement instead of an oil change, but I’ve got enough miles that I guess I’ve got to make the investment to avoid being sold for scrap.

Kodak stopped making the carousel projector less than ten years ago. I still have a carousel sitting around my lab, containing slides from the last talk I gave in this format. It wasn’t that long ago, really. (In the early 2000s, the Entomological Society of America hadn’t yet switched to accepting digital projection. That’s what still in the carousel.)

The world changes really quickly. As I’m doing my day-to-day faculty job, the world will be passing me by unless I actively work to keep pace. I always wondered how some people became deadwood. Now, I see how easy it is. It’s not about giving up, and it’s not about not caring. It’s about not strategically and systematically planning to keep up, which takes you away from immediate responsibilities. I’ve avoided this particular maintenance task for ten years, and just like when I go to get oil changed in the car, I’m not thrilled to spend my time that way. Of course, I’m glad that I can continue to drive a working car that will last a long while, and I’m glad that my soon-to-be-developed R mojo will keep me fresh for a good long while as well.

Mentorship = Training?

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When I was an undergraduate in the early ’90s, I didn’t do much research. But when the students in my midst were doing research, they weren’t being “mentored.” They were getting “research training” or doing “undergraduate research.”

Nowadays, we “mentor.”

Is there any difference in what we are doing now compared to what people used to do, or is it just an evolution of nomenclature?

Here’s exhibit A. On Dynamic Ecology and elsewhere, they were having fun comparing historical trends with Google’s n-grams. I couldn’t resist cooking my own up:

Google n-gram of the use of the terms "undergraduate research," "research training" and "mentorship" in books

Google n-gram of the use of the terms “undergraduate research,” “research training” and “mentorship” in books over time

Oddly enough, the rise and fall of “undergraduate research” corresponds well with the use of that dated term to refer to female college students, “coed”:

ugrescoed

The way I read this, there was a steady climb in “research training” after World War II. On the other hand, the popularity of the term “undergraduate research” tracks disco on the airwaves, or the push for the Equal Rights Amendment. “Mentorship,” though, has steadily climbed since the 1980s, following the wake of “undergraduate research.” I won’t tell the people at CUR if you don’t tell them.

I think what we are doing, on a day to day basis in our labs with our students, hasn’t substantially changed ever since the term “undergraduate research” was popularized.

The term “mentorship” is broadly applied to many circumstances. It’s not just used for undergraduate research. (In 30 Rock, Jack Donaghy was Liz Lemon’s “mentor.”). However, the rise of the term in general does seem to have displaced “undergraduate research” off the radar.

I have to admit that I’m partial to the notion that “mentorship” is different in philosophy than “training.” In the context of training Master K-12 science teachers to help new teachers being inducted into the profession, I’ve gotten some exposure to training in a formalized program that shows people how to mentor, called “Cognitive Coaching.” I bet the Cognitive Coaching people will disagree with me, but this is mostly about learning how to mentor, by learning how to truly listen well and coach someone through a learning process or challenge. I was skeptical of the whole concept at first, but let me tell you that every person I know who has gone through the training is very positive about it and says it was helpful, and these are people who don’t like to have their time wasted.

I can train someone. Mentorship is more difficult, because it takes more patience. Mentorship requires that you help someone figure it out for themselves when they can. Training is just showing someone how to do it and make sure they copy well.

I aspire to the practice of mentorship. I’m not a patient person, but I try. Let’s hope the change in language reflects a change in practice. However, I wouldn’t recommend that the Council for Undergraduate Research change its name to feature the role of Undergraduate Mentorship more prominently.

Training vs. productivity. What’s your currency?

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In a big lab, research gets done through the training of grad students and postdocs. The lab simultaneously fulfills its research mission and meets the “broader effect” agenda of developing the scientific workforce. Training and productivity are mutually compatible.

Granted, some PIs – often those that have the most effective training programs – do lots of independent work and their research happens separate from their students. Regardless, the training of students and the production of research aren’t in conflict.

Theoretically, this statement applies to labs in teaching schools. However, it’s not necessarily the case in practice.

I suspect science faculty – at least senior faculty at teaching schools – can be sorted into three pools:

  • Those who think that their main research responsibility is to mentor student researchers and provide them with high quality experiences to further their careers. The publication of research is an important and useful product of the research experience.
  • Those who think that their main research responsibility is to conduct and publish research and be a part of the scientific community. The mentorship of students and their future success as scientists is an important and useful product of the research experience.
  • Those who think that research distracts from quality teaching. If you can find the time for it, that’s okay as long as it doesn’t harm the students.

Is this an overgeneralization? It might be.

In an attempt to pin a theory on this (overgeneralized) concept, perhaps these perspectives form the axes of a triangular continuum (in ecology, like CSR theory or Holdrige life zones), “productivity,” “training” and “emphasis on the classroom.”

When new faculty start their jobs, maybe they start near the middle of the continuum space, or wherever the departmental culture requires for tenure. As they gain experience and a string of successes and failures of various kinds, they may gravitate to one of the corners. (I should add that an emphasis on training, research, or the classroom doesn’t necessarily mean that someone is better at that particular thing. For example, someone who says that student training is paramount might not necessarily serve their students well.)

Another theoretical framework could be taken from optimal foraging theory. Faculty members can have different currencies for their decisions. For example, when a bird is foraging, is it trying to collect the highest energy food, or trying to collect the most nutrients? Or is it trying to maximize net energy gain (and thus balance food collection with calories spent foraging)? Or is it trying to minimize predation risk? These are all different possible currencies that an  individual could select when making decisions.

Faculty members have different currencies when pursuing their research agenda. Some will seek to maximize grant money or publications, others will seek to increase the quality of student training, or the number of students heading to graduate school. Some will be seeking to maximize scientific discovery, and others are trying to have the most fun possible. Some might be trying to maximize their free time to go play with their pets.

With respect to how research happens in the lab, I think there are two common currencies that undergraduate faculty mentors choose: One is Research Productivity (a composite of publication quantity and quality) and the other is Student Training (a composite of the number of trained students and their entry into top labs in grad school).

The choice of this currency isn’t made because people love productivity or student outcomes per se. Instead, they may love the exhilaration of research and all that it entails (in my case, ants in the rainforest and all their amazing little quirks), and they may love working with their students on a day to day basis and watching them grow and succeed (which cam be spectacular in a way that words fail to describe).

To put it a different way: do you want to do research for the sake of doing the research and all that it entails, or are you doing it as an avenue for training students to be an effective educator and improve student outcomes? These two priorities, of course, are mutually compatible. However, when making decisions on a day to day basis, what is your currency?

Both perspectives, in my view, are valid and useful for the missions of most schools. I posit that a department might work best when it has faculty with diversity of currencies, with mutual respect of each others’ differing choices. A successful department might not require maximal diversity, but needs at least adequate representation of the major functional roles. When you don’t have that functional diversity in a department, things don’t work as well.

To illustrate this principle, here’s a story, slightly modified to protect the innocent: At a field station, I once shared a bottle of rum with a colleague. (This has happened plenty, but only once did it lead to this particular story from at least 10 years ago.) He was mostly a research-for-research’s sake kind of guy, and he was working in a small college in which others focused on research as a vehicle for student training. He would have to have been a top-notch scholar on his campus, I imagine. He told me how he had trouble getting promoted to full professor, because his department didn’t approve of how he conducted his research program. He eventually received promotion, accompanied with a reprimand. Apparently, he needed to involve more students in his research. The odd thing is that he actually did include students in his research, quite a bit.

This probably seems like an odd story if you haven’t taught in a teaching institution. Similar toxic situations can evolve when newly hired research-active faculty may raise the bar on unproductive faculty, or in a department focused heavily on productivity, and some scientists take care to mentor a small number of students with lots of attention, at the cost of productivity. (And, of course, at research institutions, departments focused on productivity don’t appreciate faculty who want to focus more heavily on classroom teaching.)

Behavioral ecologists have found that animals may switch currencies, depending on the environmental context.

In a low research environment such as my campus, resources cannot be acquired without a moderate to high level of productivity. Frankly, since my campus doesn’t provide me with the resources (time, space, funds) to do any student research training whatsoever, it would be very difficult to accomplish this task unless it’s built on a backbone of productivity. Moreover, successes in student training are not specifically valued or rewarded by the institution (even if it is an explicitly stated priority), whereas bringing in grants is given high priority. So, I don’t have the option to focus primarily on student training, because if I did that too much, I would not have resources to support my students. Though I’m at an undergraduate institution, I need to run my lab like at a big university if I am to get anything done, because we don’t have any other way to support our students.

My own currency, then, is productivity, though this does seem to maximize student training, at least in my current low-resource environment. In an environment where faculty are provided resources to mentor student researchers (time for mentorship, modest supply funds, and a stipend or salary for student research), then a currency switch might make sense. This might explain why small liberal arts schools are known for placing so many students into top graduate programs, not just in relative frequency but in absolute numbers. There, an emphasis on a high quality research experience might serve the students best.

Perhaps the best environment for a budding undergraduate researcher is to be mentored by a graduate student in a big research lab. You will have access to fancy resources and that important pedigree, plus quality time with someone more experienced than you, and lots of feedback and an opportunity to learn. (So far, two of my former undergraduate mentees have moved on to faculty positions at universities, both of whom coauthored a piece of my dissertation. That’s a stronger record than with I’ve had since becoming a professor whose job it has been to mentor undergraduates.)

Perhaps NSF and NIH should include salary for an undergraduate mentee for every graduate student on a project? That might be the best, and a very cheap, way to make more scientists.

Undergraduate first authorship?

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When undergraduates are conducting their own research projects in your lab, should first authorship be one of the main goals of mentorship?

This isn’t common, but it happens. (I’ve met several such undergrads at conferences.) If you work in a research institution, the event would be fun thing to lightly celebrate.

At teaching schools, this would be ultimate evidence of a top-notch operation. It probably would look better for your undergrad to be first author than to be sole author yourself, or better than having several undergrads as coauthors. It could potentially seal the deal on the scholarship expectations for tenure or promotion, especially in an institution that only expects one or a few papers before tenure. Off campus it wouldn’t look like much, but on campus it would be a big frickin’ deal.

Here is the rub: It takes much more of the mentor’s time for the student to be first author than if the mentor just wrote the paper on one’s own. It requires frequent individual meetings, revision of draft after draft, lots of advising about literature review, reading and placing the work in context. Even if the mentor does the final analyses and results and makes the figures (which wouldn’t preclude first authorship in my view), the rest of it is probably a long slog, even if the student is talented and motivated. Some manuscripts are long slogs even without undergrads doing the writing. It could be a joyful process, but simultaneously time-intensive.

I’ve never known an undergraduate to expect first authorship unless the mentor is the one who generates, and reiterates, the expectation. I regularly express this expectation among my students who clearly own their projects. I create a specific set of tiered expectations, first with lots of reading, then generating a set of specific questions for the manuscript and an introduction leading towards it.  Then, well, then… umm…. I’ve never gotten any further than that.

I admittedly set the initial bar high. It takes persistence for anybody to write their first manuscript, especially as an undergrad. I don’t want to have the process drag on for months and years only for a student to drop the ball. So, if the student is up to the first task with gusto, then we proceed. This limits an unnecessary investment.

I would love it if one of my students wrote their own paper and became first author. I’d be over the moon. (I think it might actually be happening this semester for the first time, though I’ve said this before.) Some students are too busy and consistently fail to meet deadlines, and various deadline extensions. Others change their priorities. Others have moved on to grad school and their PIs think they should leave the manuscript behind. Some students might decide that it’s ready, even though it’s not, then get frustrated and give up.

Most of my students don’t even get past the first filter. They stall at the first stack of reprints and come unprepared to discuss them. Clearly, if student authorship is my main goal, I could provide even more care and feeding to students, with more and smaller tiers of expectations. I could be doing the job better.

My first priority when supervising research is to make sure that the work gets finished and published. Because my lab relies on students to generate most of the data, we can’t afford to have students spinning their wheels on projects that result in half-completed projects or data that can’t be used. I’m the only one in the operation who is equipped to ship a manuscript out the door on schedule. I’m also equipped to mentor students through the process of doing it themselves, but this would take more resources and limit productivity.

I want my students to benefit the most they possibly can from being in my lab. In my view, that benefit isn’t the the opportunity to write their own paper. It’s being an actual co-author on an actual paper that comes to press. I could carefully mentor, cajole, coddle and push, and get students to write papers once in a long while. Or I could write a bunch more myself. Without much conscious thought into the process, I’ve fallen into the latter approach.

Perhaps it’s crass to say that I favor creating a productive lab over careful individual mentorship of students leading their own projects to publication. At some liberal arts schools, that’s heresy. However, what I really want to offer students is the opportunity of being in a successful lab, and the fact that I’m writing most of the manuscripts lets this happen. If I didn’t write up student projects, then productivity would take a bit hit. Nobody has suggested that this approach is exploitative of students, and given standard criteria that people apply to authorship, I’m relatively generous with students.

Ultimately, I think my approach offers a much greater benefit to students, and to a greater number of students as well. If my success is measured by the professional trajectories of my students, then I’ve been doing just fine.

Research labs, even in teaching institutions, need outside validation. Outside the microcosm of my campus, nobody gives a hoot about student outcomes. Even NSF cares much more about pubs than the quality of student training (but that’s another post of its own).

Have you had an undergrad write their own paper? Have you been tempted to slap their name as first author even if they haven’t? How do you measure your success as a mentor? Does tenure change the approach? How does departmental climate matter?

Taking a chance on the pre-med

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What criteria do you have for bringing in premeds to do research in your lab?

There are so many reasons to keep away from premeds. For starters, premeds are more prone to:

  1. want research “experience” but don’t want to do actual research
  2. drop lab duties at the drop of a hat whenever an A- might happen
  3. walk away as soon as they think their stellar recommendation letter is a lock

Of course it’s unfair to apply these stereotypes to actual human beings. Even if they are premeds.

It’s difficult to filter unmotivated students, because many premeds are quick to feign interest. But you can’t do research for long if you don’t love it. The bottom line is that if I’m going to invest into a student, I want them to stick around. When you take on a premed, you’re taking a bigger chance that the investment won’t pay off in terms of data productivity. There are enough non-premeds in my midst that I can wholly avoid premeds, when properly identified. But I still accept them on occasion.

I can think of only one good reason to take on a premed. But it’s a really good reason. You can convert them. It’s tempting. Most premeds don’t go to med school, and their premed experience is a big mistake. You can rescue these students early on. You can show that a becoming a scientist is a real option. It gives you the opportunity to make a genuine difference in someone’s life.

Early on, I got burned plenty of times. But I had some successes, and now I have a better spidey sense when a premed is looking for a route off the path that they (or their families) have created. My main motivation is karmic. In retrospect, I still have no idea why I was a premed environmental biology major. The professor who took the chance on me is still an excellent mentor to me, and I like to think that it’s my duty to pass the favor along to her academic grandkids.