Mark Guzdial points to an article by Nicholas Lemann in the Chronicle of Higher Ed entitled The Soul of the Research University. It’s a good essay about the schizophrenic nature of the modern research university. But Lemann takes some shots at the notion of teaching skills in the university. Here’s some devil’s advocacy from the piece:
Why would you want to be taught by professors who devote a substantial part of their time to writing projects, instead of working professionals whose only role at the university is to teach? Why shouldn’t the curriculum be devoted to imparting the most up-to-the-minute skills, the ones that will have most value in the employment market? Embedded in those questions is a view that a high-quality apprenticeship under an attentive mentor would represent no loss, and possibly an improvement, over a university education.
Later on, Lemann refutes that perspective, that students are better off being taught at research universities by professors engaged in research. He seems to miss the irony that this apprenticeship model is precisely how these research universities train PhD students. For bonus irony, here was the banner ad I saw atop the article:
At McGill University, the computer engineering program evolved out of the electrical engineering program, so it was very EE-oriented. I was required to take four separate courses that involved (analog) circuit analysis: fundamental of electrical engineering, circuit analysis, electronic circuits I, and electronic circuits II.
I’m struggling to think of what the equivalent of “circuit analysis” would be for software engineering. To keep the problem structure the same as circuit analysis, it would be something like: Given a (simplified model of?) a computer program, for a given input, what will the program output?
It’s hard to imagine even a single course in a software engineering program dedicated entirely to this type of manual “program analysis”. And yet, reading code is so important to what we do, and remains such a difficult task.
Two posts caught my eye this week. The first was Anil Dash’s The Blue Collar Coder, and the second was Greg Wilson’s Dark Matter, Public Health, and Scientific Computing. Anil wrote about high school students and Greg spoke about scientists, but ultimately they’re both about teaching computer skills to people without a formal background in computing. In other words, training.
In the hierarchy of academia, training is pretty firmly at the bottom. Education at least gets some lip service, being the primary mission of the university and all. But training is a base, vulgar activity. And it’s a real shame, because the problems that Anil and Greg are trying to address are important ones that need solving. Help will need to come from somewhere else.
I’m hoping to blog more about this later, but I loved Gelman and Loken’s column in Chance magazine (what a great name!) about statistics professors not eating their own dogfood. I’m a big fan of Andrew Gelman’s blog.
Nice to see Greg Wilson win a Sloan Foundation Grant to advance his Software Carpentry project. It’s an education project to teach much-needed software development skills to scientists.