School Leadership, Leadership, in General, Tools and Resources, Advice and humor
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School Leadership, Leadership, in General, Tools and Resources, Advice and humor
Tools, tips, resources, advice, and humor to support today's school leader and leaders, in general
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Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives

Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
O'Neil calls these harmful models "Weapons of Math Destruction," and not all fault models qualify. For a model to be a WMD, it must be opaque to its subjects, harmful to their interests, and grow exponentially to run at huge scale.

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Predictive Analytics in K-12: Advantages, Limitations & Implementation -- THE Journal

Predictive Analytics in K-12: Advantages, Limitations & Implementation -- THE Journal | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Predictive analytics is growing rapidly in popularity among school district leaders. K-12 school districts are collaborating with universities and businesses at an accelerating pace, using advanced analytics to create innovative new models and tools to advance students' performance.
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article info: 

School districts use predictive analytics in several ways:

To build early warning indicators based on students' attendance, course failure and behavior to predict dropouts1, 2;To predict on-time high school graduation and being on track in Grade 93,4,5;To examine indicators that predict college- and career-readiness and postsecondary success5;Recently predictive analytics has also gained momentum in identifying and retaining great teachers6.


Read more at http://thejournal.com/articles/2014/06/12/predictive-analytics-in-k-12-advantages-limitations-implementation.aspx#JA7yMgiLQvYoPjk3.99

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Daniel Kahneman changed the way we think about thinking. But what do other thinkers think of him?

Daniel Kahneman changed the way we think about thinking. But what do other thinkers think of him? | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it

Thinking, Fast and Slow was a global bestseller, and had a profound impact on psychology and economics, as these tributes from other leading figures show...He pretty much created the field of behavioural economics and has revolutionised large parts of cognitive psychology and social psychology. His central message could not be more important, namely, that human reason left to its own devices is apt to engage in a number of fallacies and systematic errors, so if we want to make better decisions in our personal lives and as a society, we ought to be aware of these biases and seek workarounds. That's a powerful and important discovery.

Sharrock's insight:

This is an informative article about Daniel Kahneman and his contemporary "colleagues" revolutionizing thought and experimentation in the social sciences. Working around our irrationality, our tendency to make decisions based on fallacies and cognitive biases, should be one of the main goals of education. 

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▶ Is Punishment or Reward More Effective? - YouTube

 

 

The psychologist Daniel Kahneman, winner of the 2002 Nobel prize in economics, pointed out that regression to the mean might explain why rebukes can seem to improve performance, while praise seems to backfire.[8] http://en.wikipedia.org/wiki/Regression_toward_the_mean

 

 

I had the most satisfying Eureka experience of my career while attempting to teach flight instructors that praise is more effective than punishment for promoting skill-learning. When I had finished my enthusiastic speech, one of the most seasoned instructors in the audience raised his hand and made his own short speech, which began by conceding that positive reinforcement might be good for the birds, but went on to deny that it was optimal for flight cadets. He said, “On many occasions I have praised flight cadets for clean execution of some aerobatic maneuver, and in general when they try it again, they do worse. On the other hand, I have often screamed at cadets for bad execution, and in general they do better the next time. So please don’t tell us that reinforcement works and punishment does not, because the opposite is the case.” This was a joyous moment, in which I understood an important truth about the world: because we tend to reward others when they do well and punish them when they do badly, and because there is regression to the mean, it is part of the human condition that we are statistically punished for rewarding others and rewarded for punishing them. I immediately arranged a demonstration in which each participant tossed two coins at a target behind his back, without any feedback. We measured the distances from the target and could see that those who had done best the first time had mostly deteriorated on their second try, and vice versa. But I knew that this demonstration would not undo the effects of lifelong exposure to a perverse contingency.

http://en.wikipedia.org/wiki/Regression_toward_the_mean

Sharrock's insight:

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 

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Sharrock's curator insight, January 11, 2014 4:50 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
Sharrock's curator insight, January 11, 2014 4:50 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
Sharrock's curator insight, January 11, 2014 4:51 PM

Why do people resist research findings from areas like leadership, education, parenting, and other areas related to psychology and sociology? One reason may result from the confusion between the use and value of controlled experiments and the value of anecdotal evidence. 

 
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Nate Silver: What I need from statisticians - Statistics Views

Nate Silver: What I need from statisticians - Statistics Views | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
"Nate Silver: What I need from statisticians"
Great piece from Statistics Views: http://t.co/2B6SFy4Vd4
#ddj #teaching #designthinking

Via Bill Bentley
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Bill Bentley's curator insight, September 20, 2013 12:54 PM

Not 'weird' but a serious, well thought out and easy to understand article.  If you are interested in statistics and how the media and others butcher data, read this.

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predictive analytics

In simplest terms, Predictive Analytics is the branch of statistics that  uses a variety of techniques such as data mining and game  theory to analyze current and historical facts in order to make...
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Nassim Nicholas Taleb - Wikipedia, the free encyclopedia

Nassim Nicholas Taleb (Arabic: نسيم نيقولا نجيب طالب‎, alternatively Nessim or Nissim, born 1960) is a Lebanese American essayist, scholar and statistician, whose work focuses on problems of randomness, probability and uncertainty.[3] His 2007 book The Black Swan was described in a review by the Sunday Times as one of the twelve most influential books since World War II.[4]

He is a bestselling author,[5][6][7] and has been a professor at several universities, currently at Polytechnic Institute of New York University and Oxford University.[8][9] He has also been a practitioner of mathematical finance,[10] a hedge fund manager,[11][12][13] a derivatives trader,[14][15][16] and is currently a scientific adviser at Universa Investments and the International Monetary Fund.[17][18]

He criticized the risk management methods used by the finance industry and warned about financial crises, subsequently making a fortune out of the late-2000s financial crisis.[19][20] He advocates what he calls a "black swan robust" society, meaning a society that can withstand difficult-to-predict events.[11] He proposes "antifragility" in systems, that is, an ability to benefit and grow from random events, errors, and volatility[21][22] as well as "convex tinkering" as a method of scientific discovery, by which he means option-like experimentation outperforms directed research.[23]

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Want a top job? Do the math

Want a top job? Do the math | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
A rundown of the five worst and best jobs for 2011, according to CareerCast, including what the jobs pay, job prospects and working conditions.
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Are School Homicides 'Becoming the Norm'? - Hit & Run : Reason.com

Are School Homicides 'Becoming the Norm'? - Hit & Run : Reason.com | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Don't assume schools are getting more violent.
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Statisticians slam popular teacher evaluation method - Washington Post (blog)

Statisticians slam popular teacher evaluation method - Washington Post (blog) | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Washington Post (blog) Statisticians slam popular teacher evaluation method Washington Post (blog) The ASA just slammed the high-stakes “value-added method” (VAM) of evaluating teachers that has been increasingly embraced in states as part of...
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Edward Tufte forum: Making better inferences from statistical graphics Edward Tufte

Edward Tufte forum: Making better inferences from statistical graphics Edward Tufte | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Edward Tufte home page for books, posters, sculpture, fine art and one-day course: Presenting Data and Information (Making credible inferences from data #visualization
Cognitive biases in #data #analytics

Via AnalyticsInnovations
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Regression toward the mean - Wikipedia, the free encyclopedia

Regression toward the mean

In statistics, regression toward (or to) the mean is the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement-and, paradoxically, if it is extreme on its second measurement, it will tend to have been closer to the average on its first.

Sharrock's insight:

I learned of this term from Thinking, Fast and Slow when I heard this story:

The psychologist Daniel Kahneman, winner of the 2002 Nobel prize in economics, pointed out that regression to the mean might explain why rebukes can seem to improve performance, while praise seems to backfire.[8]

“I had the most satisfying Eureka experience of my career while attempting to teach flight instructors that praise is more effective than punishment for promoting skill-learning. When I had finished my enthusiastic speech, one of the most seasoned instructors in the audience raised his hand and made his own short speech, which began by conceding that positive reinforcement might be good for the birds, but went on to deny that it was optimal for flight cadets. He said, “On many occasions I have praised flight cadets for clean execution of some aerobatic maneuver, and in general when they try it again, they do worse. On the other hand, I have often screamed at cadets for bad execution, and in general they do better the next time. So please don’t tell us that reinforcement works and punishment does not, because the opposite is the case.” This was a joyous moment, in which I understood an important truth about the world: because we tend to reward others when they do well and punish them when they do badly, and because there is regression to the mean, it is part of the human condition that we are statistically punished for rewarding others and rewarded for punishing them. I immediately arranged a demonstration in which each participant tossed two coins at a target behind his back, without any feedback. We measured the distances from the target and could see that those who had done best the first time had mostly deteriorated on their second try, and vice versa. But I knew that this demonstration would not undo the effects of lifelong exposure to a perverse contingency.
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Student Loans Are a Big Problem. So Are Misleading Statistics - Motley Fool

Student Loans Are a Big Problem. So Are Misleading Statistics - Motley Fool | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Student Loans Are a Big Problem. So Are Misleading Statistics Motley Fool That's misleading, because the number of people attending college in America has surged from just more than 15 million in 2000 to 22 million in 2011, according to the...

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Bill Bentley's curator insight, January 4, 2014 10:57 AM

This article isn't weird but it's well done and informative and helps to counteract some of the wildly misleading numbers quoted by irresponsible journalists and politicians.  It starts by showing some of those bad statistics.  Don't pass out, keep reading until the end.  It's not long.   If you or your kids are considering a college education, this analysis is well done.   Bill.

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Meet The Americans Who Don't Use The Internet

Meet The Americans Who Don't Use The Internet | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Why?

A full 85% of Americans use the Internet.

That sounds pretty impressive, but when you think about the converse — the fact that 15% of American adults don't  use the Internet — who exactly are the ~38 million Americans who look at the Internet and think "Nope, not for me"?

Well, the Pew Center for the Internet tried to find that out in a report released yesterday titled "Who's Not Online And Why."



Read more: http://www.businessinsider.com/meet-the-people-who-dont-use-the-internet-2013-9#ixzz2j7ZsuX6D

Sharrock's insight:

We can tell stories based on data we encounter. Students need to learn and practice at telling stories from the charts, graphs, and diagrams they are asked to read. 

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Four Common Statistical Misconceptions You Should Avoid

Four Common Statistical Misconceptions You Should Avoid | School Leadership, Leadership, in General, Tools and Resources, Advice and humor | Scoop.it
Statistics have become a fixture of modern society. We read them in news stories and they're used to determine policies that will affect every aspect of our lives. Unfortunately, many people wildly misinterpret them in fundamental ways.

Via Bill Bentley
Sharrock's insight:

excerpt: "Statistics are heavily math-based, but they're used to analyze real-world scenarios and situations. Separated from reality, statistics are of limited value. Reliance on numbers as an unbiased representation of reality is comforting, but without tying it to real-life people and situations, the information borders on worthless."

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Bill Bentley's curator insight, July 27, 2013 12:46 PM

Several good, basic things to know about using simple statistics.  A quote from the article that I like:  "Separated from reality, statistics are of limited value." Bill


Will Morony's curator insight, July 27, 2013 8:43 PM

Great discussion starters.

 

Sharrock's curator insight, January 6, 2014 12:02 PM

excerpt: "Statistics are heavily math-based, but they're used to analyze real-world scenarios and situations. Separated from reality, statistics are of limited value. Reliance on numbers as an unbiased representation of reality is comforting, but without tying it to real-life people and situations, the information borders on worthless."