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Why MIT switched from Scheme to Python (2009)

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284 points borski | 1 comments | 25 Jul 25 16:38 UTC | HN request time: 0.001s | source
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MontyCarloHall ◴[25 Jul 25 17:23 UTC] No.44685710[source]▶
Isn't this just part of the broader trend of CS departments switching away from teaching computer science to teaching computer engineering, which in turn is part of the more general trend of colleges becoming more vocational?

LISP dialects like Scheme are excellent for teaching pure computer science because they are the closest thing to executing lambda calculus expressions. Whereas Python is excellent for teaching applied computer engineering, because it's essentially executable pseudocode for imperative languages, and imperative languages are the most common language a computer engineer encounters in the real world.

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SoftTalker ◴[25 Jul 25 17:31 UTC] No.44685819[source]▶
Yes. One of the biggest complaints that computer science departments used to get from students is that they weren't learning any languages that employers are using.
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nextos ◴[25 Jul 25 17:57 UTC] No.44686138[source]▶
I always found this to be a shortsighted complaint. Getting exposed to languages where computation models are clear gives you an excellent background to switch to the language du jour and become a master. Going through e.g. HtDP or CTM makes it easy to transition to Python and write excellent code, whereas traversing the opposite path is going to be tough.
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nitwit005 ◴[25 Jul 25 20:51 UTC] No.44688301[source]▶
Sure, it's possible to catch up, but we're talking about at least four years of potential experience. That means spending years catching up, which can seriously impact you career.

Not a unique problem to software either. My sister in-law is a mechanical engineer. Her first employer was upset she didn't know anything practical, and only knew theory. She had to spend years catching up.

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1. nextos ◴[25 Jul 25 20:57 UTC] No.44688378[source]▶
Some technical universities in EU solve this problem by having full-time practical courses e.g. in January and June. For example, as a CS freshman you can build a really solid background in functional programming by going through a sequence of SML or Haskell courses in Autumn and Spring and spend January and June learning trendy technologies in depth. It's the best from both worlds.