So what are people saying they wish they’d learned during their years as a student? What does that say about how we educate students?

The answers coming in from commenters are heavy on statistics and programming as well as specific areas of biology (especially micro-scale areas of biology) and “research methods” type courses.

If I may, focusing in on that want for more stats and programming, its worth pointing out that both areas are undergoing rapid development, and being able to keep up therefore requires more than just a quick intro to interpreting ANOVA tables or a how to make pretty plots in the currently most popular programming language. So what should we teach students so that they can keep up once they get out of school?

I’ve found that the milestones most consider to be the moments when the really picked up stats and/or programming are actually milestones when they picked up a working familiarity with tricky concepts in probability, linear algebra and other core areas in applied mathematics, and/or when they picked up core programing skills that allow them to (somewhat) comfortably take a computational task and turn it into a series of steps they can carry out on a computer.

Importantly, both kinds of milestones have little to do with specific statistical methods or tests, or the syntax details of one language or the other. That’s hugely important for how we educate young biologists who will be working and competing in the increasingly quantitative biological sciences.

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“Don’t worry yourself over brilliance or mathematics. You need neither to be a good scientist.” — E. O. Wilson

and it got me wondering… is he right?

After giving it some thought, I’m very confident that he’s wrong… and that he’s right… sort of. Let me just explain what I mean

Now, make no mistake,* being brilliant and/or having a solid understanding of mathematics (especially statistics) will make you be a better scientist*! I say this based on having the good fortune to have interacted with some very accomplished scientists who tended to be brilliant and to have a deeper grasp on mathematics

Importantly, I’ve also met some really, really smart people in my life, including some mind-bogglingly smart mathematicians, who just weren’t good scientists. So what’s the connection, and why does it matter whether Wilson’s quote is right or not?

First, “brilliance” is a bit of a nebulous term, meaning exceptionally talented or otherwise excellent. I think it’s fair to interpret Wilson’s use of the word as “intellectually exceptional”, and in a sense, he’s right. Tons of good science are done by your average scientist, and far too many scientists suffer needlessly from “imposter syndrome” and benefit from encouragement to kick that habit of self doubt. This, in fact, was the main point made by Steve Strogatz during his keynote speech last week at the 2012 SACNAS conference in Seattle. *All young scientists need to be reminded that they’re doing good work, and that their mentors and those senior to them in the field are proud of them and have high hopes for their futures*.

Importantly, we all have room to learn more and grow as scientists and science communicators, and there’s a risk of statements like Wilson’s giving people the impression that it’s alright to slack when it comes to shoring up your weaknesses, to pass on striving to become THE expert in your field, or to slack when it comes to developing a broad level of scientific literacy.

Second, * modern science is highly quantitative, and the more math you know, the better*. Since “mathematics” is a broad term that most use to include statistics, it really makes me wince to hear Wilson say such things! But is he right? Can you get away with not knowing any mathematics? I think you can, but it comes at a cost. You simply don’t have the tools necessary to see how your work interfaces with the theoretical underpinnings of science which these days are almost always best specified in the precise language of mathematics. Mathematical understanding is essential in physics, engineering, chemistry, etc. and biology is in the middle of a huge shift to being a quantitative discipline as well. Simply put, you do need to have a working understanding of mathematics (and statistics) to be a good scientist.

Finally, and this is where I think I agree with Wilson, * these things alone won’t make you a brilliant scientist*. Yes, being really really smart helps and knowing more of any STEM subject can make you a more capable scientist, but knowing how to pick good questions, how to collaborate, how to develop expertise in your field, how to manage your time, how to be your most creative, how to get work done, how to bring together what you are most passionate about with who you are as a scientist, these things all probably matter a whole lot more. Recognize your limitations, work on them, but don’t let them consume all of your time.

I suppose it’s only fair to let Wilson have the final word on the matter:

“You are capable of more than you know. Choose a goal that seems right for you and strive to be the best, however hard the path. Aim high. Behave honorably. Prepare to be alone at times, and to endure failure. Persist! The world needs all you can give.” — E. O. Wilson

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There was also a huge added bonus: they were given a guided tour of the world class research opportunities these institutes provide to students and researchers in the mathematical sciences community. Add to that a preview of the events taking place as part of the international effort to dedicate 2013 as a special year for the Mathematics of Planet Earth? Yup, that too.

So, what exactly is the MMW, and who are these “Math Institutes”?

The Math Institutes are the 8+ NSF funded mathematics research institutes in the U.S. Each year they send representatives to the MMW at SACNAS to share a little about what they do and what’s going on in the world of applied mathematics. This year, the MMW talks touched on a really nice spread of mathematical applications in various scientific fields, and really drove home the points that 1) basically all areas of mathematics have really useful applications, and 2) modern mathematics is being heavily influenced by advances in the biological sciences and computation.

Each institute introduced the audience to what they do, how they operate, and most importantly, the opportunities for undergraduates, graduate students, postdocs, professors and researchers in the mathematical sciences community. I plan to write a post or two on what each of the institutes has to offer, but for now, here’s a quick rundown of names and websites:

**ICERM**: Institute for Computational and Experimental Research in Mathematics*Location*: Brown University, Providence, RI.

**AIM**: American Institute of Mathematics- www.aimath.org
*Location*: Palo Alto, CA

**NIMBioS**: National Institute for Mathematical and Biological Synthesis.- nimbios.org
*Location*: University of Tennessee, Knoxville, TN.

**MBI:**Mathematical Biosciences Institute- mbi.osu.edu
*Location*: The Ohio State University, Columbus, OH.

**MSRI**: Mathematical Sciences Research Institute*Location*: Berkeley, CA

**IMA**: Institute for Mathematics and it’s Applications- Location: University of Minnesota, Minneapolis, MN

**SAMSI**: Statistical and Applied Mathematical Sciences Institute*Location*: Research Triangle, NC

**IPAM**: Institute for Pure and Applied Mathematics*Location*: UCLA

**IAS**: Institute for Advanced Study*Location*: Princeton, NJ

**Yes, I was one of the speakers, but they really were excellent talks!
*

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But, after reading some of the posts over at the recently-turned-group-blog *Dynamic Ecology* (@DynamicEcology), I’ve decided the hiatus is over and **it’s time to start writing again!!!**

To keep things more or less on topic, I’m going to do my best to keep the mathy/sciencey/academic stuff separate from posts about chasing after herps or the lastest big birding news to hit Central Ohio, etc. Those of you wishing to keep up with my birding and other recreational nature pursuits should keep an eye on my other blog, Mostly Birds.

See you soon!

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