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The difference is in the level of the bare minimum. Engineering and science have objective, right-or-wrong answers. At the end of the test, either you got the r
by quanticle 15y ago
The difference is in the level of the bare minimum. Engineering and science have objective, right-or-wrong answers. At the end of the test, either you got the right answer, or you didn't. This imposes a certain minimum level of rigor that, in my experience, is wholly missing from the liberal arts.
Yes, if taught well, the liberal arts can be as rigorous as mathematics. But teaching, say, English, well is whole lot harder than teaching mathematics well. There's just a lot more subtlety that has to be communicated. This means that in practice, there are proportionally fewer good Liberal Arts teachers than there are good math teachers. The quality and rigor of undergraduate liberal arts suffers as a result.
- FreakLegion 15y agoHow are you getting from right-or-wrong answers to rigor? That doesn't follow. In fact, at a professional level you could make the argument that a lack of right-or-wrong answers actually calls for a greater degree of rigor. To quote Heidegger: Precisely from the point of view of science, no field takes precedence over the others, neither nature over history nor vice versa. No one method of dealing with objects dominates the others. Mathematical knowledge is no more rigorous than philological-historical knowledge. It merely has the character of "exactness," which is not the same as rigor. To demand exactness of the study of history goes against the specific rigor of the humanities. Anyway, anecdotally, four years of shepherding would-be engineers through basic writing requirements was enough for me to conclude that as a group, engineers are singularly terrified by the absence of right-or-wrong answers. For my part, I'm glad to have had a rigorous grounding in the humanities before stumbling into coding. It's like what Eric Raymond says about Lisp: "Lisp is worth learning for . . . the profound enlightenment experience you will have when you finally get it. That experience will make you a better programmer for the rest of your days." A sufficiently rigorous study of art and philosophy and history won't just show you new things; it will give you new eyes. It's a shame most people (including, of course, many with humanities degrees) miss out on this.
- bane 15y agoI think both your two points here are interesting: Re: Heidegger: To counter, there's a fairly accepted concept in the sciences that there is a loose hierarchy of the sciences. e.g. Biology is just a subset of Chemistry is just the study of a part of Physics, which is a study of applied Math, which is a subset of Mathematics, which is just a specialization of a subset of Philosophy. It reminds me of this http://flowingdata.com/2011/06/08/all-roads-lead-to-philosophy-on-wikipedia/ http://flowingdata.com/2011/06/08/all-roads-lead-to-philosop... Re: Engineer's proclivity towards right-wrong answers in their work. I agree, and it may be a function of the kind of thinking style that lends itself well to engineering disciplines. The curricula I looked at for Engineers seemed to express an intense desire on the part of the schools to break their engineers out of this kind of mental slavery and to grok softer subjects as valid. Many people who want to become engineers do so because they've mentally dismissed the validity of subjects with non-binary outcomes. I think their is a need to put engineers through a well rounded curriculum that includes exposure to the arts. I think this is very important. But it means as a side effect that they receive a non-trivial portion of a standard liberal arts education on top of the study of their own field. (In my opinion schools that don't provide this kind of education to their engineers are doing their students a great disservice.)
- _delirium 15y agoI agree there is probably a quality difference in average teaching, but I didn't find much of a difference in the objective/subjective nature (I was a CS major with a philosophy minor). In the lower-division courses, both CS and most liberal arts have objective answers you can test on, many of which are memorization. Comparison-based sorting can't be done in better than O(n log n); Marx was not present at the Paris Commune (neither was Bakunin, though he was involved in a related uprising in Lyon); most hash-table designs have amortized constant time for most operations; a key difference between Fichte and Kant was that Fichte rejected the notion of a thing-in-itself; etc. I think it may be true that CS is more likely to actually test on them, in part because many universities expect their liberal-arts courses to double as de-facto "how to write" courses, so they're supposed to have students do essays rather than test them on the subject matter. Imo they would be better structured as having intro-level classes teach subject matter that's tested on in a more rigid style, and then move students to developing their own arguments in essays more towards the 201 level once they've gotten a certain basic amount of factual knowledge under their belt. But that would require teaching intro writing skills somewhere else, and the main alternative, a dedicated "freshman composition" type class, is pretty widely disliked by students and not considered a great success, because it's sort of disembodied writing, "how to write" without any actual subject matter. Once you got to upper-division courses, most of my philosophy and my CS classes were pretty similar in terms of not really having objective, right-or-wrong answers. There were definitely things you could do that were ridiculous and therefore wrong, but for the most part it involved making a case for something. A data-mining project, for example: Given a data set, what can you conclude from it? What's your evidence, what are the potential pitfalls with your evidence, how would you present the results? The methodology is different, but in terms of general approach and the subjectiveness of grading, that felt very similar to me to a philosophy course project, one of which was: develop and argue a case for or against the possibility that machines could produce "creative" output. In both those examples it has less to do with there really being a "right" answer than with being sufficiently fluent with the tools of the domain to build and coherently present a supportable case, while avoiding doing anything that's clearly "wrong", like misusing statistics or using examples that don't logically support your point.
- bane 15y ago