Archive for: April, 2012

Where's my bike tire pump?

Apr 26 2012 Published by under [Education&Careers]

So here's a question for the blog peeps: what percentage of the students in classes you have taken or taught get A's?

In my classes I probably hand out somewhere between 10-25% A's depending on the class. Is it because I'm an asshole and expect unreasonable standards?

Maybe. I guess it all depends on the comparison. Friend of the blog, Namnezia, let it be known on twitter this evening that his 130 student mid-level class has a 65% rate of A's and 90% of the students "earn" a B or better.

To me, this is mind blowing. I don't know where Nam teaches, but perhaps it's the Xavier Institute for Higher Learning but I've been at a few universities in my time. I've even taught a few undergrads.

So my question to you is whether, in places I have not inhabited, it is common for 90% of the students to master 80%+ of the material? Or, could we be looking at a case of ridiculous grade inflation?

Perhaps I'm way off base here.

46 responses so far

A space question

Apr 26 2012 Published by under [Education&Careers]

Is there a formal Space Policy at your institution or are changes are at the discretion of the Dean? If there is a policy, how long do investigators get before they are at risk of space contraction?

8 responses so far

Risks in research: why you have to take them

Apr 25 2012 Published by under [Education&Careers]

"Risky" is a double-edge sword in science that can cut both ways when it comes to funding agencies. In some contexts, such as the R21 mechanism at NIH and some seed programs, risky with a high up-side is a good thing. In more typical mechanisms, risky can be StockCritique (TM) for "we want to see proof before we give you money". Sometimes that criticism is warranted, other times it's just a bar-raiser for having most of the project done before you submit for funding.

Both NIH and NSF have certainly be criticized for shying away from risky projects and both have had trouble responding to those claims. Panels and Study Sections can be conservative with limited funds and unless the POs actively encourage the consideration of potentially transformative (in NSF-speak) work, a prove it or lose it mentality can take over.

But when was the last time you walked out of a really good talk and thought "that was some super cool data that came from a totally ordinary idea!"? Sure, it can happen, but...

When I started my lab I basically started three projects: One that was a slam dunk in terms of working, one that was a reach but I knew we could do and a related one that needed a LOT of ground work to be laid but would be worth it.

That first project we were able to get funded relatively easily (one resubmit), but the other two have taken some time. Part of the reason is that those two have had to be developed from scratch and that process takes longer (and more start-up $) than you think it will. In retrospect, it may have been wiser to have one more slam dunk project in the hopper earlier on before working on these but hindsight is always 20/20.

In any case, with project number two the gamble appears to be paying off. We had a lab meeting today where my grad student presented some compelling data that are demonstrating some of the things we had hoped to see. We have the data and a well thought out analysis plan that have borne some very exciting findings already with more undoubtedly behind them. The project is evolving from something that was risky into something that will be a slam dunk for funding* once we wade through the remaining data. Nearly fours years since starting the lab, with many adjustments along the way, we're seeing the project come together the way we hoped it would.

Yes, this could have blown up in our faces and we had several plan Bs ready to get something out of the data if it did, but if things keep going the way the are** this will be well worth the loss of sleep and gray hairs cultivated over the data and finances of the project.

Four years may seem like an eternity when trying to get the lab rolling (and it has), but seeing the fruit of that labor, the incredible collaborations that have come out of it and the development of the students who have made it happen, is all pretty sweet.

*Inasmuch as anything is....

**que lab disaster that smites me for hubris

4 responses so far

Welcome

Apr 23 2012 Published by under [Et Al]

No responses yet

Teaching effectiveness

Apr 23 2012 Published by under [Education&Careers]

More than other aspects, teaching has been one of the most difficult to learn on the job. There is no shortage of advice out there, both in person and on the intertoobs, but the gap between knowing and implementing can be wide at times. The first time I taught my main course I simply survived it. It was the most difficult semester I have had as a PI and there were times when I questioned whether I had made the right career choice. I was a terrible teacher at that point and made dozens of N00b mistakes, mainly because I spent most of my time on content and had nothing left when it came to effective communication.

In year two I was able to get my head around improving the organization and delivery. The third time around I overhauled several aspects of the course and gave it a central theme that wove through the semester. Now that this semester is winding up I think this has been largely effective, as have been several adjustments I have made to how I teach.

But every time I grow comfortable with the class, I realize it needs more. As I make up the exam for the class I am starting to realize that there are a significant number of slides I disregard when making test questions. Whereas some of them are important for context, I have to ask myself whether many of those slides add value or whether they just eat space. The need to fill the class certainly drove some of the content in the early stages of the class, but I feel like I'm past that now.

It has become abundantly clear to me that my students need about three main points from each lecture, and beyond that they get lost. And I struggle to balance my belief that they should be able to handle more if they put the time into the class with the repeated observation that these students do not effectively learn even core concepts without significant and repeated reinforcement. I can either fail a large number or adjust my teaching to the realities of the audience. It's easy to fault the students for not "getting" the material, but I'm not arrogant enough (yet!) to absolve myself of blame. Streamlining the lectures to demonstrate key points and engaging the students in discussion of those points are the goals that I am starting to focus on at this stage.

So, dear readers, what are the tricks you use to organize your lectures and deliver them effectively? How do you get students involved? Is something like clickers useful for a ~25 student class, or have you found different ways to get them engaged? I have tried a few novel (for me) strategies recently to get them talking in groups about certain concepts, but I'm not entirely happy with the outcome.

I feel like I am finally at a point with this class that I can experiment a bit and get out of the straight lecture routine. I make a lot of effort to get responses from the students during lecture, but at this point I realize the limitations of that style, as many students have never contributed a single time. I also think that mixing things up will keep the students involved and make the class more enjoyable for both them and I. I'm open for suggestions.

21 responses so far

Interlude

Apr 19 2012 Published by under [Et Al]

Between being away last week and one of my favorite small conferences this weekend, I'm up to my ass in alligators. But on my ride in this morning, I was reminded of this song and have been on a Fiona Apple kick today. Besides, this video cracks me up and is a solid antidote for the "fusion" crap @drugmonkeyblog keeps posting to twitter.

4 responses so far

What I learned at an NSF Bio preproposal panel

It was my intention last week to blog a bit about the NSF Bio Preproposals while I was in DC, but that just didn't happen. What did I learn? Well, I can tell you what happened on one panel, but I got the impression that there is some decent variability in the system right now. Below are a few observations.

- The Big Idea is no more important than before. In talking to people leading up to writing the preproposals, there was a lot of emphasis on selling your Big Idea. Theoretically there was going to be less emphasis on methods and more on potential. Well, that kinda turned out to be bullshit. They were essentially judged like mini-proposals.

Cut rate. Our target cut was supposed to be 80%, with 15% landing in the category of "High Priority Invite" and 5% in the "Low Priority Invite". In the end we were closer to 20% HPI and 15% LPI, with everything else landing in "Do Not Invite". How many from the LPI category will actually get invited was not clear.

Two flavors. A lot of good science went into the DNI category. If you get a panel summary you will know why: The DNIs with a summary were discussed, the rest were triaged.

Triage. Anything that got less than three ratings of "good" in the preproposal stage was not discussed. Slapped a boiler-plate panel summary on those and moved on. Roughly 25% of the initial pool went undiscussed.

- BI still matters. Thought you could short the Broader Impacts section just because it was a preproposal? Wrong. A crappy BI section bumped several proposals to DNI.

- Small proposals get killed. For a long time there has always been the party line at NSF that there was no reason for a small grant mechanism because you could always send in a small proposal. Well, guess what happens when you remove the budget and measure all proposals with the same stick? Yeah.

- NSF is worried about new PIs too. Much was made of the concern for the N00bs, and NSF is watching this closely. If new PIs get disproportionately whacked, there will be a correction (This goes for RUI as well). BTW, current average to grant is three years.

- Possible funding from preproposals. One possibility that came up was that the very top preproposals might, in future years, just get funded without a full proposal. Things are still in flux, but my panel felt it could make some awards now.

- Incorporation of preproposal panel members for the full proposals is being discussed. There was some concern by panelists over having two very different hoops for the PIs to jump through, between the preproposals and the full proposals. One way to keep some continuity could be if preproposal panelists agreed to serve as ad hocs for the proposals that got invited and for which they were the primary reviewer in the first round. Everyone started with eight primaries, but I don't think anyone had more than two or three make it to the invite stage, which would be a manageable load to ad hoc.

- Shrinking everything. The full proposal may be going on a diet soon, too.

- Three's often enough. Most proposals got a pretty fair treatment with three people having read them and no ad hocs. There may have been some that could have benefited or been hurt, but overall a panel-only review didn't seem to be an issue.

- The long month. The time line to notifications is roughly a month for those getting an invite, longer for those that got bumped.

So, do I think this is going to be an effective process? It's too early to tell. Just based on my preferences as a PI, I think I would prefer something more along the lines of the 8 month cycle that MCB has gone to, so that you can more effectively manage one's grant load. As it stands now, anyone who can apply to DEB and IOS could have 4 preproposals going in every January. The 8 month cycle with 1 proposal per round would spare people the year between submissions and spread the load out a bit.

But we will have to see how it all goes. One thing was clear: no one, at NSF or as PIs, really know how this is all going to play out.

41 responses so far

Where's the line?

Apr 09 2012 Published by under [Education&Careers]

One of the things I like about reading grant proposals is that it makes me think. I'm asked to read and judge topics that can be far flung from my field and interests. But part of that process is, of course, the generation of ideas.

Some of the proposals are closer to my wheelhouse and I would be lying if they haven't made me ponder some alternative approaches to what we do. How could they not? One proposal, in particular, introduced me to a system that I was vaguely aware of, but not in any detail. While the proposal and questions were quite distinct from anything I do, the system piqued my interest as a vehicle to demonstrate principles we are working on in other systems.

Herein lies a dilemma with all reviewing - determining where the line is between stimulating independent thought and leaning on someone else's ideas. In science, we lean on the work of others all the time, but not in its nascent stages.

So, readers, how do you draw the line when reviewing?

12 responses so far

NSF Broader Impacts, take eleventy

Apr 04 2012 Published by under [Education&Careers]

We have been through this before. And before that. And before that. Yet still, I keep reading proposals where the PIsclear said "OMG! BI section!" and either vomited up everything that sounds remotely like outreach that they can think of, or wrote down everything they already do that seems like training.

Click on the links above for what a BI section IS, but it is certainly NOT something that should be feared. It is also not:

-Entering information on your organisms/system into some database like Tree of Life. Whereas that is a good thing to do, it does not constitute meaningful BI.

-Creating your own website to host your data and "distribute" software. You might as well yell your results down the hall. You will probably affect the same number of people. Again, software should be accessible, but this is not a BI of note.

-Training grad students. You already get paid to do this.

-Teaching. Ditto.

-Doing all these things in some mixed BI turd sandwich. Just because you write a whole paragraph doesn't mean you have thought about potential BI in your project.

Broader Impacts do not have to be complicated, but you need to show that you've given some thought about engaging people you wouldn't otherwise. This is really not that hard if you find out what your institution is already doing on this front. If you are at a museum or have one associated with your institution, you are surrounded by BI opportunities. If you are in a city, the same. If your institution has ANY program to engage high school or minority students (or both) in science, your work is 80% done. If you have field sites in location where science engagement would be seen as a Good Thing, develop that.

Opportunities to develop interesting and useful BI plans abound, which makes it frustrating when PIs can't even bother to see what is happening at their own institution. While the Web is a useful tool, most websites don't get much traffic, and when they do, it is from people search for that specific thing. In this case, your page about your sub-sub-sub-field is going to be looked at by people you probably already know by first name. Engage them at the bar.

38 responses so far

How I prepare for an NSF review panel

Apr 02 2012 Published by under [Education&Careers]

The first time I went to NSF for a panel I wasn't quiet sure what I needed to do to be prepared. I read like crazy and showed up fairly apprehensive about whether or not I would be prepared to do a good job. Facing my second panel in a few weeks, I have a much better feel for preparing this time around. Below are some suggestions if you are making a trip to NSF in the future.

- Get you reviews in be the requested week before... or close. This isn't just for the benefit of your PO, it is for you. NSF has a couple of different choices behind the panelist sign-in:

You reviews all get filed under the Panel Review System tab, but once you have submitted a review for a proposal you can go check out the other reviews under the Interactive Panel System tab. This is important. Not only because you'll want to know if your assessment is radically different from the other panelists (and ad hocs if you are on a full proposal panel) so that you can reread it, but for the reasons below.

-Decide which proposals you are going to fight for and find out who you will be fighting. You will be going into the discussion with a short list of proposals you really liked. By looking up the other reviews ahead of time you can figure out how much of a fight you have on your hands. What did the other panelists think of your Good List? Go look those panelists up and find out what they do. Is their expertise strong in the proposal topic? People may write opinionated reviews, in either direction, before the panel discussion and change their minds during the discussion. This seems especially true if they were out of their element a little when writing and didn't "get" the proposal. Don't be scared off of fighting for something that got hammered by another panelist, but figure out where they are coming from.

-Identify your panel enemy. Alright, maybe "enemy" is a little strong but in both of my experiences I have found that I share the majority of the proposals I am responsible for with a small group (3-5) of other people. Among that group, there seems to be one person who thinks every idea put forth is doomed for failure. Their reviews often focus on poking holes in any perceived methodological flaws, as if the PI(s) have no recourse but to follow exactly what is written without modification. This is the person you will need to convince that the proposals you are fighting for will work. Read their review, know what they work on and be prepared to spar with them.

-Get a sense of the panel's mood. After reading the reviews you have access to, are they generally positive or negative? Is this going to be a panel that spends most of its time finding reasons to whack a proposal or finding reasons to support them. There is always a mix of both, but there can be a very different feel to panels that go one way or the other.

-Figure out if anyone else shares expertise in your area. Scan the list of names on the panel. Know anyone? Read anyone's work? I wouldn't go e-stalking anyone or reading people's stuff just for kicks, but I find it useful to have a little idea what other people do and what they may weigh in on.

That's what I do in the lead up to a panel. I'm sure some of the more experienced Peeps out there may have other suggestions as well. Above all, remember that you are there to talk science and participate in the process of getting people funding. As a group you'll have to make some hard decisions and it's easy to walk out of one of these feeling a little depressed by the amount of good science that doesn't make the cut. But do what you can, learn what you can and get to know the other panelists - there's a decent chance they will be reviewing one of your grants some day.

13 responses so far