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Affordable, convenient, on-demand: All the things university isn’t—but could be

Want to hear a joke? Universities haven’t innovated in 400 years. At a time when close to half of all students aren't graduating, Dan Rosensweig explains why and how to fix this broken education system.

Dan Rosensweig: Fifty percent of high school students don’t go on to higher education.

Of the 50 percent that do, 43 percent of them don’t graduate.

Of those that do graduate the average graduation time is six years.

The average age of a current college student today is about 25. And I think 25 percent of college students today actually have a child.

So if you ask me those statistics suggest two things. The current system is not producing what it was designed to produce for the types of people that go, the number of people that go and what they need. And it has not kept up with the modern world in terms of how it makes itself available and what it charges students to be able to get what they need.

So it’s a combination of availability; It doesn’t seem to work for the majority of students, because the number one reason that students don’t go on to further education or drop out of college, it’s a combination of two things which essentially means the same thing: It’s too expensive, or they can’t get the classes at the time of day they’re available.

And that’s because: of the 70 percent of kids that go to state schools, 40 percent of them work 30 hours a week or more. All of this is to say that schools are no longer programmed at the right time. They take too long. They’re too expensive, and what they program is incomplete. It’s not necessarily bad.

our view is the education system needs to evolve to the way we do everything. Everything we do today comes to us (rather than us go to them).

An example, today we would never wait out in the rain for a car and hope that we can get a cab. We’ll just hail Uber and it comes and it takes us exactly where we want to go.

Today we wouldn’t go rush home to watch a TV show at eight o’clock on a Thursday night. We watch it on the device we want to watch it, when we want to watch it, when it’s convenient for us.

Only education continues to require you to come to it, pay a fortune to do it, and have it be a choice between eating or reading or learning and earning.

And so what Chegg is trying to do is reverse it, is try to say let’s use what the internet does best. Let’s make it online, on demand. Let’s make it personalized. You do it the way you want to do it, not the way it’s taught singularly to everybody.

Adaptive which means when we watch what you do and we learn about you, let’s actually adjust how we teach you or what we teach you, what we give you more of and what we give you less of based on your actual abilities.

And then let’s make it exceptionally affordable. And if we do that you’d be amazed how many students need to learn, want to learn, are willing to learn.

So we think that the modern university system has become too expensive; incomplete programming, inconvenient locations, inconvenient time of day for the modern workforce which doesn’t have the time to do both. So even if you look at for-profit colleges they were a mess because they became a scam for a lot of people. But if you realize 3.6 million people at one time were actually taking it, you realize the demand was there to be able to learn in your own environment in your own way. Why? Because the average person was a 30-year-old woman who could not leave her family or her workforce, or in some cases both.

So I just think that the modern education system needs to acknowledge who the modern student is, what the demands on that modern student are—there’s more of them, they’re more broke, they have more diverse needs. They enter the system with different education, different backgrounds, different financial situations, and no “one size fits all” is going to work anymore.

And so what we’ve got is we’ve got a lot of schools – now we’re not talking about the top 50 or 100 schools. Those schools have huge endowments. They’ll be protected for a long time and they’ll probably continue to be able to teach the smaller part of the population that can take four years.

But the ramifications are—well, here’s a question for you.

Why is there something called a four year school? Why does college take four years? That’s a random number. Why does a certain course take two years? That’s a random number.

It has to do with how many classes they’re willing to program that you’re able to take. Not how long it takes you to learn the material. Ninety-five percent of the time that you’re at a four year college you’re not in a classroom in any way, shape or form. In today’s world we binge watch everything that we want. You can binge watch entire series, albums, learn anything you want. Why can’t you binge learn your education? If you’re willing to put in the time at nights, weekends, days, whatever it is and learn and master the subject, why can’t you finish when you’ve learned the things you’re supposed to learn in order to get you a job?

So the ramifications are colleges are going to have to take less time to get somebody from learning to earning. There is no reason why it should take four years. Very little of the population has the time or the finances to delay earning by four years. Only a small subset do. And so I think the ramifications are you’re going to see fewer colleges, you’re going to see them combined, more of them are going to have to get online. They’re going to have to expand their curriculum to include job skills, and I think you’re going to see a resurgence of institutions that primarily serve people online.

Not because—a teacher can make the argument there’s nothing better than one-on-one in a classroom. That may be true. That may be true for a lot of kids. It’s certainly not true for everybody. But it’s also 100 percent not available to anybody.

Nobody gets to learn one-on-one in a classroom anymore. And so our opinion is it’s unfair to say “Because this is the best way, we’re not going to do the other way” when 90 percent of the people have no access to the best way.

So if education is really going to grow, it’s really going to proliferate, it’s got to be online, increasingly. It’s got to be on demand. It has to be multimodality. Some people learn by taking tests. Some people learn by watching videos. Some people learn by human intervention and human help. All of those ways need to be available.

There’s no benefit in teaching somebody who learns this way, this way over here if that’s not going to work for them. And when you look at the scores 43 percent drop out, they drop out with $7,000 to $9,000 in debt. The ones that survive have $37,000 in debt. So I mean you just look at the math and ask yourself, do you want to put your kid into that system? The answer has to be no.

Why are we taking the most valuable people, the future of this country and delaying their ability to be productive in the workforce, delaying their ability to make money, and saddling them with debt larger than anything else they may do in their life (with the exception of buying a home), and doing it at 18 years old? To me it just sounds unfair and unfortunate.

Want to hear a joke? Universities haven’t innovated in 400 years. A lot has changed since the 1600s. The average college student today is 25 years old. Approximately one-quarter of students have a child. And close to half will never graduate. The higher education model is hopelessly outdated, catering to a student type that no longer exists, at a price people can no longer afford. Dan Rosensweig, CEO of Chegg, asks: Can we design something better? Taking inspiration from industry innovators like Netfilx, Rosensweig explains why higher education must change and what that kind of future would look like. Here's a hint: less debt, less commuting, on-demand courses that you can binge-learn (four years is truly arbitrary), and highly adaptive to how you learn best. When colleges stop failing their students, society can become so much richer.

Does conscious AI deserve rights?

If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.

  • Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
  • Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
  • One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.

A new hydrogel might be strong enough for knee replacements

Duke University researchers might have solved a half-century old problem.

Photo by Alexander Hassenstein/Getty Images
Technology & Innovation
  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
  • The blend of three polymers provides enough flexibility and durability to mimic the knee.
  • The next step is to test this hydrogel in sheep; human use can take at least three years.
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Hints of the 4th dimension have been detected by physicists

What would it be like to experience the 4th dimension?

Two different experiments show hints of a 4th spatial dimension. Credit: Zilberberg Group / ETH Zürich
Technology & Innovation

Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.

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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.