“What I’ve learned” from this is complicated for me as well, and not all of it is coherent enough to put out here. I am both inspired by and concerned about the prospects of liberal learning, which makes it hard to come up with a cogent precis of where I’ve been and where we all might be headed.
But with so many partially-written posts on my dashboard I decided it was worth at least putting something out there. As you say, it’s a place to start. The real challenge ahead, to my mind is how to fulfill the charge of the collaboratives project to “build capacity and a network of faculty.” Potential abounds.Easy answers, not so much.
Thank you, Gardner for asking me to join this project. I’ve learned so much and hope to carry the experience forward to wherever the next adventure leads us. Thanks so much for your vision and leadership — it’s been absolutely essential and I’m counting on you to carry the beacon for the foreseeable future.

[…] dedicated significant time and energy to saving and maintaining a major OER in my field (Soviet History) that is used by tens of thousands of people around the globe annually — most […]

Excellent read, I just passed this onto a colleague who was
doing some research on that. And he just bought me lunch as I found it for him smile Therefore let me
rephrase that: Thank you for lunch!

Interesting post. I won’t argue against keeping diversity in higher education because I agree it’s a good thing. A small point you made at the start was about a “society of Einsteins” is interesting. Aldous Huxley mentions this idea briefly in his classic novel, Brave New World. In his novel, society is bred into castes, with metered intelligence. Huxley writes (in 1932) that many of the elite caste, the alphas, wouldn’t perform much of the manual labor required, thus they create the epsilons. Of course, Huxley wrote before mass automation was possible, and his novel is dystopian and not a guide to good living. I would also acknowledge that automation is difficult, and some tasks we cannot automate (at least for a while). I also think we are a long way from saturating our intellectual capital, so turning away potential talent because a nation has “too much talent” seems foolish. If people want to be successful, and they see moving to a new country as a means of doing so, I think it’s for the best.

I liked your point #8: know your limitations, know your niche. As you put it, in grad school you are surrounded by many brilliant people, and that can be a double-edge sword: you may be stimulated to grow intellectually, or you may feel as if you don’t fit. Finding your niche is the key to success, not only in grad school, but after graduation too. To succeed in academia you need to find what sets you apart from the rest, or else you’ll dissolve among the yearly mass of newly graduated PhDs.

I’ll add one more point to your list: once you’ve made the decision to get a PhD, don’t fall into “the grass is always greener somewhere else” mood. You will see job offers passing in front of you, often when you are at the lowest in your program, but you’ve got to stick with your decision and finish. It is the endurance component of grad school, and I’d say it is also number one key to success at a PhD.

Entertaining read. Sometimes the process of exploration may be just as important as the results, and negative results may be just as valuable as positive results. Would save everybody so much time if there was data available about what did not work, rather than only what did work. The PLOS Current seems to be moving in the right direction about what it means to share research. In my discipline of geotechnical engineering, design failures are encouraged to be reported. Historically, that’s how the profession has advanced. There are technical sessions at conferences specifically dedicated to the presentation of case histories, whether they were successes or failures. However, journal articles still seem to be reserved for the so called positive results, and that renders research inefficient a lot of times.

Thanks for the feedback Amogh, so here’s where I was coming from with that. The pot in pot refrigerator was a simple innovation that almost anyone in the world with access to dirt and fire could potentially make. It’s been invented several times in both recent and ancient history and relies upon simple principles of evaporation that elementary schoolers are taught. It also has significant potential to save lives via reduced risks of foodborne illness, nutrition, and general economic circumstances.
I view the fact that it had been lost/ not re-discovered sooner as a failure worth further introspection. As exciting and inspiring as it may be to count the number of higgs bosons in a pound of soil, we need to be mindful of whether we could with comparable effort deliver (re)discoveries with more direct impact upon the public. It matters not whether one pursues such for the direct, altruistic goal of preserving life or the pragmatic goal of ensuring our gains remain comprehensible enough to capture the public imagination and secure our continued funding.

This is a well written piece, and I have to say, I agree with a lot of what you propose.
“Metrics may be derived to prove most any biased claim in a manner sufficiently compelling to sell a product yet prohibitively expensive to disprove”- This I believe has always been true in a sense, and I believe is the reason why computational methods have always been popular or sought after.
“Increasingly granular analyses and computations may allow increasingly granular findings, but their inherent complexity allows for the the masking of errors and bias” – Well said. You state this in the context of computational work, but I believe this is very much true in the experimental sciences as well.
Overall, I fail to understand your example of the pot in pot refrigerator in relation to the issues you raise, and I would be glad to discuss why this particular example is representative of what you describe as “the challenge in communication”.