Universities v/s MOOCs

Aswath Damodaran has two excellent posts on the unsuccessful onslaught of MOOCs on traditional universities, and the lessons that universities should learn, before the next wave of more potent attacks is unleashed.

[Business as usual would be a mistake], analogous to music companies reacting to the demise of Napster more than a decade ago by going back to their old modes of business (selling CDs through music stores), only to be swept away by Apple iTunes a few years later. The MOOC model represented the first serious foray of online entities into education and like Napster, it failed because it not only came with flaws but because it's promoters failed to fully understand the business it was trying to disrupt.

Universities are not merely vehicles to deliver content; instead they offer a bundled product which includes screening, certification, networking, entertainment, friendship etc. Each university offers a different, or differently weighted mix of "services" in the bundled product. Choosing which university to go to involves choosing the bundled product that best matches individual preferences and budgets.

If you are a faculty member or a college administrator, ... you have to look at what it is that you offer (as a college or university) that makes your education bundle unique, different and difficult to replicate (either online or in another institution). If you are an online education entrepreneur, your task is to figure out ways to unbundle the product and probe its weakest points.

In the second of the two posts, he elaborates on the latter. His summary is really spot on (emphasis mine).

I believe that change is coming to education but that it will come in stages and be under-the-surface. The first to feel the heat (if they have not already) will be colleges that have loose or non-existent screens, mechanized degree programs, content-heavy but learning-light classes and nonexistent networks. As they fall prey to online or alternative education systems, it is an open question as to how schools further up the food chain will react. I won’t claim to know the mindset of faculty/administrators at the top schools but my interactions with them suggest that many of them will, for the most part, resist change (especially if it inconveniences them) and argue that there is no chance that their civilized citadels will fall to the barbarians. But they are fooling themselves, since the disruptors have the luxury of being able to experiment, with nothing to lose, until they find the weapons that work. It is only a matter of time!

Scientists Kill Really Old Things

I haven't been keeping up with big science stories reported in the popular press for the past few months. 

Only yesterday, I was catching up on unplayed SGU podcasts on my iPod, when I heard about Ming, a mollusk who was killed by scientists in the process of determining his age. He was 507 (plus or minus 2)!

They murdered the oldest (known) animal.

It immediately reminded me of Donald Rusk Currey and Prometheus, who I first heard about on Radiolab.

Yes. They also murdered the oldest (nonclonal) organism.

Why do scientists hate old things so much!?

Interesting Maps

The Washington Post presents "40 maps that explain the world".

Maps can be a remarkably powerful tool for understanding the world and how it works, but they show only what you ask them to. You might consider this, then, a collection of maps meant to inspire your inner map nerd. I've searched far and wide for maps that can reveal and surprise and inform in ways that the daily headlines might not, with a careful eye for sourcing and detail.

Staring at them is a useful perspective-building exercise. 

Solution: Shortest distance between points on a cubic grid

One simple algorithmic solution to the puzzle is as follows.

1. Define \(\Delta x = |x_A - x_B|, \Delta y = |y_A - y_B|, \Delta z = |z_A - z_B|\).
2. Sort these quantities: \[[\text{min, med, max}] = \text{sort}[\Delta x, \Delta y, \Delta z].\]
3. Set \(n_{111} = \text{min}\), \(n_{110} = \text{med-min}\), \(n_{100} = \text{max-med}\).
4. The minimum distance is given by \[d_{min} = \sqrt{3} n_{111} + \sqrt{2} n_{110} + n_{100}\]
As an example consider A = (5, 3, 2) and B = (4, -1, 2).

1. \(\Delta x = 1, \Delta y = 4, \Delta z = 0\).
2. [min, med, max] = [0, 1, 4]
3. \(n_{111} = 0\), \(n_{110} = 1\), \(n_{100} = 3\).
4. Minimum distance is \(\sqrt{2} + 3\).