Category: Education

Lax College Accreditors May Be “Doing More Harm than Good”

(p. A19) Most colleges can’t keep their doors open without an accreditor’s seal of approval, which is needed to get students access to federal loans and grants. But accreditors hardly ever kick out the worst-performing colleges and lack uniform standards for assessing graduation rates and loan defaults.
Those problems are blamed by critics for deepening the student-debt crisis as college costs soared during the past decade. Last year alone, the U.S. government sent $16 billion in aid to students at four-year colleges that graduated less than one-third of their students within six years, according to an analysis by The Wall Street Journal of the latest available federal data.
. . .
(p. A12) Accreditors say their job is to help colleges get better rather than to weed out laggards. Colleges pay for the inspections, which can cost more than $1 million at large institutions.
“You’re not there to remove an institution,” says Judith Eaton, president of the Council for Higher Education Accreditation, a trade group. “You’re there to enhance the operation.”
The government has relied on accreditors as watchdogs since the 1950s. Colleges are evaluated by teams of volunteers from similar institutions, who follow standards set by the accreditation group. For example, colleges sometimes are required to collect student-retention data but given the freedom to set their own goals for those numbers.
. . .
Stephen Roderick, former provost at Fort Lewis College in Colorado, says he now has misgivings about his 2013 review of Glenville State College in West Virginia for the Higher Learning Commission. The review team wrote that the college had a “responsible program” to minimize default rates and “demonstrates a commitment” to evaluating graduation data.
Glenville’s graduation rate is 30%, while about 22% of students defaulted on loans from 2011 to 2013. Both percentages rank near the bottom 10% of accredited four-year colleges. David Millard, assistant to Glenville’s president, says the figures reflect the opportunity offered by the college to students in one of the poorest parts of the U.S.
Mr. Roderick says accreditors are inclined to see the best in colleges like Glenville, but that might not be the best for students. “Sometimes I feel that we’re doing more harm than good,” he says.

For the full story, see:
ANDREA FULLER and DOUGLAS BELKIN. “Education Watchdogs Rarely Bite; Accreditors keep hundreds of schools with low graduation rates or high loan defaults alive.” The Wall Street Journal (Thurs., June 18, 2015): A1 & A12.
(Note: ellipses added.)
(Note: the online version of the article was dated June 17, 2015, and had the title “The Watchdogs of College Education Rarely Bite; Accreditors keep hundreds of schools with low graduation rates or high loan defaults alive.”)

Antiquated Education Needs Reform to Encourage Entrepreneurship

(p. 22) . . . “Most Likely to Succeed: Preparing Our Kids for the Innovation Era,” by Tony Wagner and Ted Dintersmith — argues that the only way to ensure any kind of future security for our children is to totally upend the education system and rethink what school is for.
“Disrupt” is a buzz word these tech-world gurus use sparingly, but that’s what they mean. Wagner works at Harvard’s Innovation Lab, Dintersmith in venture capital, funding education and tech start-ups. . . . Their argument is this: Public education in America is based on antiquated late-19th-century priorities, on the need “to educate large numbers of immigrants and refugees from farms for basic citizenship and for jobs in a growing industrial economy.” Most of the stuff children are forced to know, and on which our culture’s sense of achievement is based, is unnecessary in the age of Google. But tests and test-makers still run the show, and kids are required to “jump through hoops” and drill and drill to assimilate reams of facts (“content”) instead of learning the skills that will keep them employed and employable for years to come — which is to say, the skills to be entrepreneurs.
. . . .
. . . the assumption that undergirds this whole tract: that every person can — or should — be molded into an entrepreneur.

For the full review, see:
LISA MILLER. “Raise Them Up; A Vision of Education for an Entrepreneurial America.” The New York Time Book Review (Sun., AUG. 23, 2015): 22.
(Note: ellipses in original.)
(Note: the online version of the review has the date AUG. 18, 2015, and has the title “‘Most Likely to Succeed,’ by Tony Wagner and Ted Dintersmith.”)

The book under review, is:
Wagner, Tony, and Ted Dintersmith. Most Likely to Succeed: Preparing Our Kids for the Innovation Era. New York: Scribner, 2015.

Too Much Positive Thinking Creates Relaxed Complacency

(p. D5) In her smart, lucid book, “Rethinking Positive Thinking: Inside the New Science of Motivation,” Dr. Oettingen critically re-examines positive thinking and give readers a more nuanced — and useful — understanding of motivation based on solid empirical evidence.
Conventional wisdom has it that dreams are supposed to excite us and inspire us to act. Putting this to the test, Dr. Oettingen recruits a group of undergraduate college students and randomly assigns them to two groups. She instructs the first group to fantasize that the coming week will be a knockout: good grades, great parties and the like; students in the second group are asked to record all their thoughts and daydreams about the coming week, good and bad.
Strikingly, the students who were told to think positively felt far less energized and accomplished than those who were instructed to have a neutral fantasy. Blind optimism, it turns out, does not motivate people; instead, as Dr. Oettingen shows in a series of clever experiments, it creates a sense of relaxation complacency. It is as if in dreaming or fantasizing about something we want, our minds are tricked into believing we have attained the desired goal.
There appears to be a physiological basis for this effect: Studies show that just fantasizing about a wish lowers blood pressure, while thinking of that same wish — and considering not getting it — raises blood pressure. It may feel better to daydream, but it leaves you less energized and less prepared for action.
. . .
In one study, she taught a group of third graders a mental-contrast exercise: They were told to imagine a candy prize they would receive if they finished a language assignment, and then to imagine several of their own behaviors that could prevent them from winning. A second group of students was instructed only to fantasize about winning the prize. The students who did the mental contrast outperformed those who just dreamed.

For the full review, see:
RICHARD A. FRIEDMAN, M.D. “Books; Dare to Dream of Falling Short.” The New York Times (Tues., DEC. 23, 2014): D5.
(Note: italics in original; ellipsis added.)
(Note: the online version of the review has the date DEC. 22, 2014.)

The book under review, is:
Oettingen, Gabriele. Rethinking Positive Thinking: Inside the New Science of Motivation. New York: Current, 2014.

From Self-Funding, and Sony, Khanna Builds PlayStation Supercomputer to Advance Science

KhannaGauravPlaystationSupercomputer2015-07-05.jpg“Gaurav Khanna with a supercomputer he built at the University of Massachusetts Dartmouth physics department using 200 Playstation 3 consoles that are housed in a refrigerated shipping container.” Source of caption: print version of the NYT article quoted and cited below. Source of photo: online version of the NYT article quoted and cited below.

(p. D3) This spring, Gaurav Khanna noticed that the University of Massachusetts Dartmouth physics department was more crowded than usual. Why, he wondered, were so many students suddenly so interested in science?”

It wasn’t a thirst for knowledge, it turns out. News of Dr. Khanna’s success in building a supercomputer using only PlayStation 3 video game consoles had spread quickly; the students, a lot of them gamers, just wanted to gape at the sight of nearly 200 consoles stacked on one another.
. . .
Making a supercomputer requires a large number of processors — standard desktops, laptops or the like — and a way to network them. Dr. Khanna picked the PlayStation 3 for its viability and cost, currently, $250 to $300 in stores. Unlike other game consoles, the PlayStation 3 allows users to install a preferred operating system, making it attractive to programmers and developers. (The latest model, the PlayStation 4, does not have this feature.)
“Gaming had grown into a huge market,” Dr. Khanna said. “There’s a huge push for performance, meaning you can buy low-cost, high-performance hardware very easily. I could go out and buy 100 PlayStation 3 consoles at my neighborhood Best Buy, if I wanted.”
That is just what Dr. Khanna did, though on a smaller scale. Because the National Science Foundation, which funds much of Dr. Khanna’s research, might not have viewed the bulk buying of video game consoles as a responsible use of grant money, he reached out to Sony Computer Entertainment America, the company behind the PlayStation 3. Sony donated four consoles to the experiment; Dr. Khanna’s university paid for eight more, and Dr. Khanna bought another four. He then installed the Linux operating system on all 16 consoles, plugged them into the Internet and booted up the supercomputer.
Lior Burko, an associate professor of physics at Georgia Gwinnett College and a past collaborator with Dr. Khanna, praised the idea as an “ingenious” way to get the function of a supercomputer without the prohibitive expense.
“Dr. Khanna was able to combine his two fields of expertise, namely general relativity and computer science, to invent something new that allowed for not just a neat new machine, but also scientific progress that otherwise might have taken many more years to achieve,” Dr. Burko said.
. . .
His team linked the consoles, housing them in a refrigerated shipping container designed to carry milk. The resulting supercomputer, Dr. Khanna said, had the computational power of nearly 3,000 laptop or desktop processors, and cost only $75,000 to make — about a tenth the cost of a comparable supercomputer made using traditional parts.

For the full story, see:
LAURA PARKER “An Economical Way to Save Progress.” The New York Times (Tues., DEC. 23, 2014): D3.
(Note: ellipses added.)
(Note: the online version of the story has the date DEC. 22, 2014, and has the title “That Old PlayStation Can Aid Science.”)

More Tech Stars Skip College, at Least for a While

(p. B1) The college dropout-turned-entrepreneur is a staple of Silicon Valley mythology. Steve Jobs, Bill Gates and Mark Zuckerberg all left college.
In their day, those founders were very unusual. But a lot has changed since 2005, when Mr. Zuckerberg left Harvard. The new crop of dropouts has grown up with the Internet and smartphones. The tools to create new technology are more accessible. The cost to start a company has plunged, while the options for raising money have multiplied.
Moreover, the path isn’t as lonely.
. . .
Not long ago, dropping out of school to start a company was considered risky. For this generation, it is a badge of honor, evidence of ambition and focus. Very few dropouts become tycoons, but “failure” today often means going back to school or taking a six-figure job at a big tech company.
. . .
(p. B5) There are no hard numbers on the dropout trend, but applicants for the Thiel Fellowship tripled in the most recent year; the fellowship won’t disclose numbers.
. . .
It has tapped 82 fellows in the past five years.
“I don’t think college is always bad, but our society seems to think college is always good, for everyone, at any cost–and that is what we have to question,” says Mr. Thiel, a co-founder of PayPal and an early investor in Facebook.
Of the 43 fellows in the initial classes of 2011 and 2012, 26 didn’t return to school and continued to work on startups or independent projects. Five went to work for large tech firms, including a few through acquisitions. The remaining 12 went back to school.
Mr. Thiel says companies started by the fellows have raised $73 million, a record that he says has attracted additional applicants. He says fellows “learned far more than they would have in college.”

For the full story, see:
DAISUKE WAKABAYASHI. “College Dropouts Thrive in Tech.” The Wall Street Journal (Thurs., June 4, 2015): B1 & B10.
(Note: ellipses added. The phrase “the fellowship won’t disclose numbers” was in the online, but not the print, version of the article.)
(Note: the online version of the article has the date June 3, 2015, and has the title “College Dropouts Thrive in Tech.”)

The Complementarity of Humans and Robots in Education

(p. 6) Computers and robots are already replacing many workers. What can young people learn now that won’t be superseded within their lifetimes by these devices and that will secure them good jobs and solid income over the next 20, 30 or 50 years? In the universities, we are struggling to answer that question.
. . .
Some scholars are trying to discern what kinds of learning have survived technological replacement better than others. Richard J. Murnane and Frank Levy in their book “The New Division of Labor” (Princeton, 2004) studied occupations that expanded during the information revolution of the recent past. They included jobs like service manager at an auto dealership, as opposed to jobs that have declined, like telephone operator.
The successful occupations, by this measure, shared certain characteristics: People who practiced them needed complex communication skills and expert knowledge. Such skills included an ability to convey “not just information but a particular interpretation of information.” They said that expert knowledge was broad, deep and practical, allowing the solution of “uncharted problems.”
. . .
When I arrived at Yale in 1982, there were no undergraduate courses in finance. I started one in the fall of 1985, and it continues today. Increasingly, I’ve tried to connect mathematical theory to actual applications in finance.
Since its beginnings, the course has gradually become more robotic: It resembles a real, dynamic, teaching experience, but in execution, much of it is prerecorded, and exercises and examinations are computerized. Students can take it without need of my physical presence. Yale made my course available to the broader public on free online sites: AllLearn in 2002, Open Yale in 2008 and 2011, and now on Coursera.
The process of tweaking and improving the course to fit better in a digital framework has given me time to reflect about what I am doing for my students. I could just retire now and let them watch my lectures and use the rest of the digitized material. But I find myself thinking that I should be doing something more for them.
So I continue to update the course, thinking about how I can integrate its lessons into an “art of living in the world.” I have tried to enhance my students’ sense that finance should be the art of financing important human activities, of getting people (and robots someday) working together to accomplish things that we really want done.

For the full commentary, see:
ROBERT J. SHILLER. “Economic View; What to Learn in College to Stay One Step Ahead of Computers.” The New York Times, SundayBusiness Section (Sun., MAY 24, 2015): 6.
(Note: ellipses added.)
(Note: the online version of the commentary has the date MAY 22, 2015, and has the title “Economic View; What to Learn in College to Stay One Step Ahead of Computers.”)

The Levy and Murnane book mentioned above, is:
Levy, Frank, and Richard J. Murnane. The New Division of Labor: How Computers Are Creating the Next Job Market. Princeton, NJ: Princeton University Press, 2004.
Some of the core of the Levy and Murnane book can be found in:
Levy, Frank, and Richard Murnane. “Book Excerpt: The New Division of Labor.” Milken Institute Review 6, no. 4 (Dec. 2004): 61-82.

Cultural and Institutional Differences Between Europe and U.S. Keep Europe from Having a Silicon Valley

(p. B7) “They all want a Silicon Valley,” Jacob Kirkegaard, a Danish economist and senior fellow at the Peterson Institute for International Economics, told me this week. “But none of them can match the scale and focus on the new and truly innovative technologies you have in the United States. Europe and the rest of the world are playing catch-up, to the great frustration of policy makers there.”
Petra Moser, assistant professor of economics at Stanford and its Europe Center, who was born in Germany, agreed that “Europeans are worried.”
“They’re trying to recreate Silicon Valley in places like Munich, so far with little success,” she said. “The institutional and cultural differences are still too great.”
. . .
There is . . . little or no stigma in Silicon Valley to being fired; Steve Jobs himself was forced out of Apple. “American companies allow their employees to leave and try something else,” Professor Moser said. “Then, if it works, great, the mother company acquires the start-up. If it doesn’t, they hire them back. It’s a great system. It allows people to experiment and try things. In Germany, you can’t do that. People would hold it against you. They’d see it as disloyal. It’s a very different ethic.”
Europeans are also much less receptive to the kind of truly disruptive innovation represented by a Google or a Facebook, Mr. Kirkegaard said.
He cited the example of Uber, the ride-hailing service that despite its German-sounding name is a thoroughly American upstart. Uber has been greeted in Europe like the arrival of a virus, and its reception says a lot about the power of incumbent taxi operators.
“But it goes deeper than that,” Mr. Kirkegaard said. “New Yorkers don’t get all nostalgic about yellow cabs. In London, the black cab is seen as something that makes London what it is. People like it that way. Americans tend to act in a more rational and less emotional way about the goods and services they consume, because it’s not tied up with their national and regional identities.”
. . .
With its emphasis on early testing and sorting, the educational system in Europe tends to be very rigid. “If you don’t do well at age 18, you’re out,” Professor Moser said. “That cuts out a lot of people who could do better but never get the chance. The person who does best at a test of rote memorization at age 17 may not be innovative at 23.” She added that many of Europe’s most enterprising students go to the United States to study and end up staying.
She is currently doing research into creativity. “The American education system is much more forgiving,” Professor Moser said. “Students can catch up and go on to excel.”
Even the vaunted European child-rearing, she believes, is too prescriptive. While she concedes there is as yet no hard scientific evidence to support her thesis, “European children may be better behaved, but American children may end up being more free to explore new things.”

For the full story, see:
JAMES B. STEWART. “Common Sense; A Fearless Culture Fuels Tech.” The New York Times (Fri., JUNE 19, 2015): B1 & B7.
(Note: ellipses added.)
(Note: the online version of the story has the date JUNE 18, 2015, and has the title “Common Sense; A Fearless Culture Fuels U.S. Tech Giants.”)

Babies “Have a Positive Hunger for the Unexpected”

(p. C2) In an amazingly clever new paper in the journal Science, Aimee Stahl and Lisa Feigenson at Johns Hopkins University show systematically that 11-month-old babies, like scientists, pay special attention when their predictions are violated, learn especially well as a result, and even do experiments to figure out just what happened.
They took off from some classic research showing that babies will look at something longer when it is unexpected. The babies in the new study either saw impossible events, like the apparent passage of a ball through a solid brick wall, or straightforward events, like the same ball simply moving through an empty space.
. . .
The babies explored objects more when they behaved unexpectedly. They also explored them differently depending on just how they behaved unexpectedly. If the ball had vanished through the wall, the babies banged the ball against a surface; if it had hovered in thin air, they dropped it. It was as if they were testing to see if the ball really was solid, or really did defy gravity, much like Georgie testing the fake eggs in the Easter basket.
In fact, these experiments suggest that babies may be even better scientists than grown-ups often are. Adults suffer from “confirmation bias”–we pay attention to the events that fit what we already know and ignore things that might shake up our preconceptions. Charles Darwin famously kept a special list of all the facts that were at odds with his theory, because he knew he’d otherwise be tempted to ignore or forget them.
Babies, on the other hand, seem to have a positive hunger for the unexpected. Like the ideal scientists proposed by the philosopher of science Karl Popper, babies are always on the lookout for a fact that falsifies their theories.

For the full commentary, see:
ALISON GOPNIK. “MIND AND MATTER; How 1-Year-Olds Figure Out the World.” The Wall Street Journal (Sat., April 15, 2015): C2.
(Note: ellipsis added.)
(Note: the online version of the commentary has the date April 15, 2015, and has the title “MIND AND MATTER; How 1-Year-Olds Figure Out the World.”)

The scientific article mentioned in the passages quoted, is:
Stahl, Aimee E., and Lisa Feigenson. “Observing the Unexpected Enhances Infants’ Learning and Exploration.” Science 348, no. 6230 (April 3, 2015): 91-94.

To Maintain Enrollments Professors Are Often Pressured to Inflate Grades

(p. 198) Dedicated college professors demand that students do the difficult reading and writing necessary to become skillful in understanding the complexities of the world. But the university distributes resources like research funds and new faculty positions based in part on how many students populate classes and how positively students evaluate courses. How much do you simplify to keep up enrollment and keep resources flowing into your department?

Source:
Schwartz, Barry, and Kenneth Sharpe. Practical Wisdom: The Right Way to Do the Right Thing. New York: Riverhead Books, 2010.

Some Learn in Order to Gain Competence, Others Learn to Gain Direct Rewards

(p. 184) Think about two different tennis pros giving you tennis lessons. The first pro says things like “good shot” and “good swing” all the time, to encourage you. The second one says “good swing” only when you make a good swing. If hearing “good swing” gives you a hedonic charge, then you will prefer the first instructor to the second (more gold stars, more encouragement). But if what gives you the charge is getting better at tennis, you will prefer the second instructor to the first. That’s because the second instructor’s feedback to you is much more informative than the first one’s. You’re not after “good swing” gold stars; you’re after a better tennis game. So feedback is essential to the development of a complex skill– whether it be empathy or a strong forehand. But he-(p. 185)donic feedback, in the form of incentives, is not. It may even be counterproductive, as in the case of instructor number one.
In schools, tests provide an extremely important source of feedback– of information– to the teacher and the student– about how things are going. Tests, or something like them, often offer the best way to diagnose problems and correct them. So tests as a source of information are good and important. The problem is that in addition to providing information, tests provide outcomes that students, and their parents, and their teachers, want and like– outcomes like approval, prizes, awards, honors, special privileges, and school ratings. The hedonic character of these outcomes is what gets students and teachers to orient their work to passing the tests, and to regard what they do in the classroom as merely instrumental, as merely a means to various rewarding ends.
There are important differences between children oriented to getting A’s and children oriented to learning from their mistakes. Psychologist Carol Dweck and her associates have spent thirty years studying the incentive systems that govern the learning of children throughout the educational process. They have uncovered two fundamentally different approaches to learning in kids that can often lead to profound differences in how well kids learn. One group of kids has what Dweck has called performance goals; the other group has what she has called mastery goals. Children with performance goals are primarily interested in gaining favorable judgments of their competence. They want to do well on tests. They want social approval. They want awards. Children with mastery goals are primarily interested in increasing their competence rather than in demonstrating it. They want to encounter things that they can’t do and to learn from their failures. As Dweck puts it, performance-oriented children want to prove their ability, while mastery-oriented children want to improve their ability. Children with performance goals avoid challenges. They prefer tasks that are well within the range of their ability. Children with mastery goals seek challenges. They prefer tasks that strain the limits of their ability. Children with performance goals respond to failure by giving up. Children (p. 186) with mastery goals respond to failure by working harder. Children with performance goals take failure as a sign of their inadequacy and come to view the tasks at which they fail with a mixture of anxiety, boredom, and anger. Children with mastery goals take failure as a sign that their efforts, and not they, are inadequate, and they often come to view the tasks at which they fail with the kind of relish that comes when you encounter a worthy challenge.

Source:
Schwartz, Barry, and Kenneth Sharpe. Practical Wisdom: The Right Way to Do the Right Thing. New York: Riverhead Books, 2010.
(Note: italics in original.)

Should Students Read to Learn, or to Get Gold Stars?

(p. 181) When a consultant tells teachers to concentrate on the bubble kids and ignore the kids who are most in need of help, something has gone wrong. And if gold stars turn reading from an adventure into a job, something has gone wrong. But what? The typical response to examples like these is not to blame incentives but to blame “dumb” incentives. The presumption is that “smart” incentives, or at least “smarter” incentives, will do the job.
This is a mistake. In many situations, for many activities, no incentives are smart enough. Teachers like Deborah Ball and Mrs. Dewey spend their day figuring out how much time to spend with each student and how to tailor what they teach to each student’s particular strengths and weaknesses. They are continually balancing conflicting aims– to treat all students equally, to give the struggling students more time, to energize and inspire the gifted students. Along comes the incentive to bring up the school’s test scores, and all the nuance and subtlety of Mrs. Dewey’s moment-by-moment decisions go out the window. And what “smarter” incentive is going to replace judgment in making sensitive choices in a complex and changing context like a classroom?
Or what, exactly, would you incentivize to encourage hospital custodian Luke to seek the kind and empathetic response to the distraught father who wanted his son’s room cleaned? Incentives are always based on meeting some specific, measurable criterion: read more books; raise more test scores; wash more floors. Left to his own devices, Luke asks himself, “What can I do to be caring?” and because he has moral skill, he comes up with a good answer. With “caring” incentivized, Luke (p. 182) might ask, “What do I have to do to get a raise or a bonus?” “Reclean the room” might be a right answer. “Look sympathetic” might be a right answer. “Be caring” surely is not. Aristotle thought that good
people do the right thing because it is the right thing. Doing the right thing because it’s the right thing unleashes the nuance, flexibility, and improvisation that moral challenges demand and moral skill enables. Doing the right thing for pay shuts down the nuance and flexibility.

Source:
Schwartz, Barry, and Kenneth Sharpe. Practical Wisdom: The Right Way to Do the Right Thing. New York: Riverhead Books, 2010.
(Note: italics in original.)