21–30 of 57 posts
I think it makes sense for them to emphasize a strong understanding of the fundamentals. It will help those students who later want to go into data science as well.
It's rote learning though as ChatGPT proves by its scores on AP calculus exams. This is just a way to maintain elite admissions.
While I’ve led a data science team, I’ve never taken a data science course — so I’m not sure what it teaches. But i do feel pretty confident in saying that I think math does lose its usefulness around after trig. Not to say there aren’t useful aspects, but the curriculum is so inefficient. And maybe it’s because everyone needs some part of it, but that part is different for each person. Math is interesting in that th…
“math does lose its usefulness around after trig” This is the most jarring thing I’ve read today. I can’t say I agree, but I haven’t spent 15 years studying math myself, so who am I to disagree.
For example, if you go into medicine and medical research having a good understanding of statistics is useful, but very little in calculus or analysis is useful (and even if you do need Calculus, most of the useful stuff for those fields is taught in the 1st semester of Calculus).
Earlier quoted context omitted.
“math does lose its usefulness around after trig” This is the most jarring thing I’ve read today. I can’t say I agree, but I haven’t spent 15 years studying math myself, so who am I to disagree.
I think most people would agree if pressed. Math is so ridiculously useful prior to trig. Almost any white collar job relies on these maths. Trig is an interesting inflection point in that so much math gets built on top of it, although its not that useful in of itself. And then after trig, things become much more fragmented and you really need to go into specific subfields to determine which branch of math is of valu…
A whole lot of finance and pharmacology are about exponential functions and their derivatives and integrals, for instance. A whole lot of fields use optimization, even if "just asking the computer to do it", etc.
I admit I am weaker now in calculus and linear algebra because I lean on CAS and simulation a lot... but at least I know how it works so that I have an idea of what I'm doing.
Every high school student should learn how to grapple with uncertainty, how to evaluate statistical claims and experiments, how to interpret graphs and charts, understand how machine learning models work (at a high level), and internalize concepts like "significance", "error bars", and "expected value."
This training will help all students every single day of their lives, because it teaches them how to think. Society benefits from having more people with the tools to evaluate data and deal with uncertainty, especially as we face a looming epistemological crisis.
Calculus, on the other hand, will be used by very few students, and even for those few, it will not likely be used every day. Yes, it is a prerequisite for some STEM courses as part of a degree program, and so calculus can be taught to undergraduates pursuing a STEM field in their first year (or those who take it as an elective in high school.)
It's a shame that Stanford and Harvard, which set the tone for high schools and high schoolers, are going the wrong direction here.
Earlier quoted context omitted.
It's rote learning though as ChatGPT proves by its scores on AP calculus exams. This is just a way to maintain elite admissions.
Just because ChatGPT can do it, doesn’t mean that it isn’t valuable for a human to learn. This is especially true for foundational courses.
No, but it does sort of suggest that, doesn't it?
> This is especially true for foundational courses.
Sure, but calculus is about memorizing ways to answer problems. We're not talking about real analysis, the course in which students develop the calculus and prove it works.
Earlier quoted context omitted.
I think most people would agree if pressed. Math is so ridiculously useful prior to trig. Almost any white collar job relies on these maths. Trig is an interesting inflection point in that so much math gets built on top of it, although its not that useful in of itself. And then after trig, things become much more fragmented and you really need to go into specific subfields to determine which branch of math is of valu…
I think a lot of things use calculus concepts, even if calculus isn't explicitly invoked. A whole lot of finance and pharmacology are about exponential functions and their derivatives and integrals, for instance. A whole lot of fields use optimization, even if "just asking the computer to do it", etc. I admit I am weaker now in calculus and linear algebra because I lean on CAS and simulation a lot... but at least I k…
I spent a chunk of my career optimizing FDMs and FEMs, but above and beyond that I haven't had a great need for Calculus until I started doing some deep learning. Again, very particular subfields.
And I suspect the work that you're talking about is exactly what I was thinking about when I wrote that even if Calculus is needed, it's the stuff taught in the first semester.
A high school "data science" course, if designed properly, will be far more useful to students and beneficial to society than calculus. Every high school student should learn how to grapple with uncertainty, how to evaluate statistical claims and experiments, how to interpret graphs and charts, understand how machine learning models work (at a high level), and internalize concepts like "significance", "error bars", a…
How do you expect students to understand what they are doing with "data science" without learning probability and statistics, and how do you expect students to get probability and statistics without learning calculus?
I mean, Bayes' theorem. How do you get people to get it if they don't know calculus?
A high school "data science" course, if designed properly, will be far more useful to students and beneficial to society than calculus. Every high school student should learn how to grapple with uncertainty, how to evaluate statistical claims and experiments, how to interpret graphs and charts, understand how machine learning models work (at a high level), and internalize concepts like "significance", "error bars", a…
Pet peeve: can we just go back to calling these things statistics?
While I agree with you that statistics should be more heavily emphasized at the high school level, the issue goes much deeper within American math education that the one class.
Note that this is the recommendations for applying for Undergrad, not their classes or program offerings. Those two institutions are recommending more foundational (calculus) rather than applied courses (data science).
They continue to recommend statistics. They removed data science from a sentence that also included calculus and statistics.
I knew a professor from a math department from a top European university who taught data science courses who swore that data science and data mining were just marketing terms invented to sell statistics.