Rise and Kill First


Cheery Friday Greetings to our Learning How to Learners!

Book of the Week 

Rise and Kill First: The Secret History of Israel’s Targeted Assassinations, by Ronen Bergman. This fascinating book has been named one of the best books of the year by The Economist, The New York Times Book Review, BBC History Magazine, and Kirkus Reviews. It is a tour de force explanation of how a people who have suffered through the Holocaust and myriad other horrors through the centuries have developed a “kill first” policy as an integral part of their approach to terrorism. As Bergman describes, this policy has been adopted by others in the West, for example, Barack Obama. When successful, targeted killings are very effective at saving lives. When unsuccessful—well, read the book to find out. As spy-master extraordinaire John le Carré writes: “A remarkable feat of fearless and responsible reporting . . . important, timely, and informative.” [Hat tip Ali Ali Binazir MD MPhil] Of course, other countries have related programs—perhaps not as tightly monitored, benevolently intentioned, or ultimately as accountable to the public.

How and Why the MOOC Learning How to Learn  came to life 

This insightful article, by our own Terry Sejnowski, gives insight into how Learning How to Learn came to life, and the impact it’s had on the world of learning.

A Puzzle for Learning How to Learners

This week, we have a puzzle for you involving the conclusions of two separate research meta-analyses.

Both papers have been cited thousands of times, although oddly enough, Freeman’s paper doesn’t cite Kirschner’s apposite findings.

Your challenge this week is to discuss how two meta-analyses could draw such dramatically different conclusions. If you’re on for the challenge, take a careful look at both papers, and then go to the discussion forum here and weigh in about how such different conclusions could arise. Is there a way to reconcile the two very different findings?  

New Research Finally Provides Insight Into the Costs of Various College Classes

This article in Inside Higher Ed provides interesting insights into issues such as why costs are higher for fields where graduates earn more money. 

“[T]he cost of teaching electrical engineering is 109 percent higher than teaching English, but teaching math is 22 percent lower than teaching English, according to the authors of the paper, ‘Why Is Math Cheaper Than English? Understanding Cost Differences in Higher Education.’

“This variation in costs is a function of large differences in class size and, to a lesser extent, differences in average faculty pay,” the researchers wrote. “We observe different stories across fields in terms of the trade-offs implied by the cost drivers. Some fields, like economics, offset high wages with large classes, resulting in costs that are comparable to English despite higher faculty pay.

“Other fields, such as mechanical engineering and computer science, do not offset high faculty pay with large classes, resulting in costs that are much greater than English. Still others, like physics, partially offset higher faculty salaries with heavier faculty workloads, resulting in costs that are moderately higher than English.”

“The findings have implications for higher education policy and funding decisions at a time when state and federal lawmakers are increasingly demanding more accountability from colleges and universities, and more evidence that they provide students with measurable academic and employment outcomes.”

Cal Newport on Thinkspot and the Rise of Long Tail Social Media

We’re longtime fans of Cal Newport—his book Deep Work, for example, is the best we’ve ever read on trying to focus intently. In this thoughtful blog post, Cal describes the important rise of long tail social media. “In this new model, users don’t want to connect with everyone they already know, but instead want to connect with small groups they find really interesting. Similarly, they don’t need access to massive libraries of low-quality content, but instead want access to curated collections covering topics they really care about. The old model requires massive audiences before a given platform becomes useful. The new model does not.” If you don’t follow the usual crowd, but instead like to think for yourself—and you admire others of that mindset, you may wish to check out Cal’s post.

That’s all for this week. Have a happy week in Learning How to Learn!

Barb, Terry, and the entire Learning How to Learn team

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