University Engineering Optimization Function

I was surprised by the persistent constraint of “4 years, x dollars” that came up in the Engineering Dean’s conference. Apparently any change to the university curriculum that challenges the 4 years or the cost basis for graduating is virtually impossible to make. This came up in the context of input from the industry panel suggesting new and increased requirements for graduates (things like “ability to communicate” and “leadership”, which, frankly, I’m not entirely on-board with).

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.