Friday links: what’s flipped learning anyway?, bad null models, peer reviewers vs. lightbulbs, and more

Also this week: old conservation vs. new conservation, some highlights from our recent comment threads, and more…

From Meg:

I enjoyed this ProfHacker post on managing work-life balance. His point? Achieving work-life balance is hard, but that shouldn’t stop you doing your best to achieve it. Towards that goal, he has two key points/tips: try to manage other’s expectations without being “an uncollegial jerk”, and “you don’t actually have to tell people where you are all the time”.

This post focuses on a new attempt to come up with a definition of flipped learning. I certainly have found that lots of people have very specific definitions of flipped learning and flipped classrooms, but those definitions are not very consistent. And, in a related vein, here’s a Chronicle article on microflipping. (I think a subscription is required.) It says, “Unlike the fully flipped approach where students are expected to come to class prepared, microflipping is designed to instruct both those students who have done the required assignments before class and those who have not. It blends the flipped-classroom and traditional-lecture approaches.”

From Jeremy:

Over at EEB and Flow, Caroline Tucker says something important that’s been said before but bears repeating: simple, easy-to-apply null models in ecology mostly don’t work as advertised and often are badly misinterpreted. One common use of null models is to tell you what the data would be expected to look like in the absence of some effect, factor, or process. In the case Caroline discusses, we want to know how species’ climatic niches would evolve if they just speciated and migrated at random, with no selection acting on species’ climatic niches. The problem is that most ecological null models don’t correctly describe the other processes that generate the data, not even approximately. So that deviations of the observed data from the null model-generated expectations can’t be attributed to the purportedly-omitted effect, factor or process. For instance, in climatic niche modeling, it’s common to assume that, in the absence of selection, species’ climatic niches would evolve as a Brownian motion process, at least approximately. That seems reasonable, right? After all, Brownian motion is a random walk, and in the absence of selection niche evolution will be random, right? Wrong. Turns out that if you simulate a process-based spatially-explicit, mechanistic model with speciation and migration but no selection, the resulting niche evolution is nowhere near Brownian motion. This is just one example of a common and very important problem in ecology, which I’ve talked about before (here, here, here, and here) and to which I plan to return in the future.

Florian Hartig on old conservation (conserving nature for nature’s sake) vs. new conservation (conserving nature for our sake). Notes that this is just one instance of a very old philosophical debate (utilitarian vs. non-utilitarian ethics). Argues that we shouldn’t decide between the two approaches on the grounds of which works better as “marketing” to the general public. And argues that this is a debate we can’t avoid having for the sake of a united front against the enemies of conservation in all its forms. Related posts from Brian on “united fronts” in science, and from me on the (questionable, highly contingent) value of biodiversity.

What fraction of papers go uncited? Turns out the answer varies a lot among fields–and that some of the most widely-reported numbers in the popular media aren’t based on reliable sources. (ht Ed Yong, via Twitter)

Alex Bond of The Lab and Field fame is leaving academia and taking a position as a conservation scientist with the Royal Society for the Protection of Birds. Here he talks about how he ended up taking that path.

A scientist’s guide to social media. Good starting point for newbies.

And finally: how many peer reviewers does it take to change a lightbulb?🙂 (ht The Molecular Ecologist)

Hoisted from the comments:

The excellent comment thread on Meg’s excellent post on the male bias of recent NSF Waterman award winners includes comments from Mayra Montrose, the NSF manager of the award. She shares Meg’s concerns and invites feedback on how to address them.

If you missed the comment thread on Brian’s post in praise of Biosphere II, go check it out. It’s a wide-ranging conversation on everything from what “bold” predictions are and why we might want them, to whether ecosystems can be engineered, to population viability analysis, and more. Stick with it to near the end to see Brian expertly dodge my deliberately-loaded question, “So, would you rather have NEON, or two more Biosphere II’s?”🙂

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