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Goji Berries---Why is Online Learning Offline?

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The rate of production of knowledge is rapidly increasing. Yet, our ability to distill that knowledge
 
November 21 · Issue #33 · View online
Goji Berries
The rate of production of knowledge is rapidly increasing. Yet, our ability to distill that knowledge and communicate it has stagnated. Ever-increasing specialization and rise in the number of years in school are but two consequences of this growing gap. And while it is common to mistake the effects for solutions, neither are. The underlying problems remain mostly unsolved. 
In this newsletter, I expand on some of the issues with some structured learning solutions, e.g., Coursera, etc., and unstructured learning solutions, e.g., Youtube.

Why is Online Learning Offline?
Coursera solves for highly motivated students. Today, millions of motivated people have cheap access to high-quality teaching on some topics. For instance, more than 4.5M students have enrolled in Andrew Ng’s courses. But the rate at which people finish the courses remains abysmal. There are many other problems, most of which are founded in the fact that Coursera is a poor facsimile of offline education. 
It is telling that nothing has changed since I wrote about (what I thought were) fairly obvious ways to build a true educational platform five years ago: 
“For Coursera etc., to be true learning platforms, they need to provide rich APIs for allowing the development of both learning and teaching tools (and easy ways for developers to monetize these applications). For instance, professors could get access to visualization applications, and students could get access to applications that put them in touch with peers interested in peer-to-peer teaching. The possibilities are endless. Integration with other social networks and other communication tools at the discretion of students are obvious future steps.”
Read more here.
What is the Next Best Thing to Learn?
Recommendation engines are everywhere. These systems recommend what shows to watch on Netflix and what products to buy on Amazon. Since at least the Netflix Prize, the conventional wisdom is that recommendation engines have become very good. Except that they are not. Some of the deficiencies are deliberate. Netflix has made a huge bet on its shows, and it makes every effort to highlight its Originals over everything else. Some other efficiencies are a result of a lack of content. The fact is easily proved. How often have you done a futile extended search for something “good” to watch?
Read more here.


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