A small group of schools account for a disproportionate amount of billionaire education. Just 20 universities and colleges account for 52% of the billionaire graduates while 182 schools count for the remainder.

Via Yahoo Finance.

Given calculus I could’ve derived and actually understood all those formulas, instead of just memorizing them. And memorize them I never did – in fact the other time I remember being distinctly pissed off was when I spent the first 30 minutes of the AP Physics exam deriving formulas because I was too stubborn/stupid to memorize them.

Calculus is really not that hard. A good teacher can explain it to an 11 year old. It will take some effort, but it can be done. And once the kid knows calculus, think of how much easier Physics and Chemistry will be.

Anyway, this ramble came about as a result of reading A Gentle Introduction to Learning Calculus.

Apparently the reasons for the immovability of the “4 years, x dollars” are numerous and complex, but an over-riding one is driven by students. If your university takes 4 1/2 years and mine takes 4, it is thought that students will go to mine instead of yours.

This and some of the other commentary made me wonder what function universities are optimizing. It seems the function is something like: maximize the number of graduates you can produce in 4 years and x dollars.

It’s not clear to me that’s the right function. From an employer’s perspective, the function I care about is: how many graduates can you produce within a reasonable time and cost that I can hire.

There’s a big difference between the employer’s optimization and the university’s optimization. Of all the graduates, only a small subset will have the skills I need. Increasing the number of graduates doesn’t necessarily increase the number I can hire; in fact it could make it harder to find the needle in the haystack.

Imagine a university that produced a very small number of graduates, but 90% of those graduates were a good fit for my hiring needs. That would be much better for me than a university that produces a very large number of graduates, but only 1% were a good fit for me. I could virtually guarantee the former university’s graduates a well paying job without even interviewing them.

So what’s the presumed “show-me-the-money” student’s optimization function? The desire for the shortest / cheapest path to a degree is a fallacy. The function the student is trying to optimize is the effort and time they put in versus the resulting payoff. Increased time and / or cost is acceptable if there is a commensurate increase in payoff. This is why people spend extra time and money getting MBAs.

My interests are well aligned with the student’s. He wants to graduate and make good money, and I want him to graduate and pay him good money in return for good work.

The “4 years, x dollars” optimization function is aligned with neither the student’s nor the employer’s interests. I can image there are valid reasons for its existence, but the presumed student driven aspect is not one of them. Btw, if you know of the reasons, please enlighten me.

My take is: if you’re running an engineering school, go for the high-margin graduates that get the high-margin jobs. Spend any extra time or money necessary. Recognize that in an increasingly global engineering economy the low-margin jobs will likely not be in the US, so even if you’re churning them out in 4 years and x dollars you’re not doing them any favors.

Btw, I’m not convinced extra time is necessary to teach a full curriculum, but I do recommend undergrads take 5 years to graduate and throw some internships in for good measure.

Most of the nonsense I spewed can be summarized as: don’t approach the CS degree as a vocational degree. Don’t teach resume-checklist items. Don’t concern yourself with what technology/programming language/IDE is in vogue at the moment.

It’s very tempting to create curriculum to fill out a resume, as it presumably helps candidates find jobs. However, it’s the wrong thing to do.

Instead, universities should teach science.

The reason is simple: tools and technology change quickly; science changes much less quickly.

If you’re graduating as an “X programmer” for any value of X (say, Java), you’re doing yourself a disservice. X (say, Java) will be out of vogue in a little while.

Science goes stale more slowly. Understanding algorithms, computational complexity, statistics, data structures, operating systems, and compilers will remain useful 20 years from now. Knowing the minutia of J2EE will not be useful 5 years from now (or is that today?).

And my pet peeve: for heavens sakes, if you’re graduating an “engineer”, make sure he understands statistics, at least a basic level. If he doesn’t understand what a standard deviation is and can’t explain it to a 10 year old, he’s no engineer. If he doesn’t know what sampling is and why and when you’d use it, he ain’t engineer. Stats people, stats!

» Lectures are not where you learn, I agree. I missed as many lectures as I attended as an undergrad. Grad school is a different story as lectures tend to be more conversational and informative and the material more challenging.

» A lot of the smartest professors are terrible lecturers. Another little story: one of my grad school professor’s lecture consisted of standing in silence, staring at the class in misery, writing an equation on the board, staring at it, turning back and staring at the class, and saying “there”. This was the normal session.

» The best pre-recorded lecturers are likely better than your average live lecture. But most learning takes place outside the lecture.

» Being there physically is still very important. A study at Google found physical proximity is the single highest determinant of people voting the same way, which is interpreted as a good measure of information flow. I’m a big believer in telepresence, but there is no way telepresence is a substitute for physically attending the same university as someone else. At one point in undergrad my friend and I spent 3 days physically locked up in a lab creating a visual perception system, on a whim. No way that would’ve happened over telepresence. Eating tacos at 3am with your cohorts is an integral part of the experience. This is why Paul Graham (since we’re quoting Paul ) forces the startups he funds to move to where he is.

» Chance interactions with people due to physical proximity carry as much or more information as pre-scheduled meetings. The same professor who would stare at the board in his lectures was incredibly insightful and helpful when I asked for his help as I ran into him in the hallway of the CS department. So were any number of my classmates that co-habitated that dungeon of a building.

» Good universities are filters for smarts and achievement. The level of drive and ability you’ll find at Berkeley is certainly different than what you’ll find at your local community college. The average level of drive and ability falls off from the top schools to the lesser schools. Would you want to spend 4+ years with the smartest, most driven people you could find, or with less smart, less driven people?

» Smart people don’t want to talk to you unless you pass the filters. Daniel mentions: “… you could just go on the Web and interact with super-smart people from all over the world without having to pay Harvard-level tuitions” and that bandwidth and latency are the primary barriers. They’re not. Part of what you pay for when you pay Harvard tuition is the privilege of talking to very smart people. Those same smart people wouldn’t talk to you if you were some random person who hadn’t passed a smarts filter because you’d likely be a waste of their time. Daniel is a professor at a well known school and as such can call on smart people as he likes; try doing the same as an undergrad in a community college.

» Expectations are important. What’s expected of the average student at a name school is quite different than what’s expected of a student at a community college. Again it’s a gradient. I firmly believe what you expect to achieve is a key indicator of what you will achieve.

For all these reasons I think you should go the “best” school you can get into, physically be there, and live in the dorms (I commuted). This doesn’t mean you can’t achieve everything you want going to a “lesser” school, but you’ll have to work harder at it.