Well as a physics grad who struggled with first year LA and a parent of a current university student I can fill in some blanks. Linear Algebra specifically is a superpower these days and I was very excited to do the best I could to help by daughter get past the barriers I experienced and learn it well.
I failed. I found her course to be not only sink or swim, but actively hostile to student learning. As mentioned in another post, assignments and quizzes were returned weeks late with little helpful coaching. Assignments very often worked with higher levels of abstraction than presented in the lectures, for example the first time she saw a matrix of functions was on a homework assignment.
Furthermore there seemed to be no additional help for Linear Algebra. To my great surprise the math department had no facility for matching students with tutors. The university math help center was almost exclusively oriented towards calculus and had no resources for Linear Algebra. After weeks of searching online we finally got a call back from a third party tutor, only to be informed that this person (a grad student in math) couldn't help us because the assignments were "too specific to the particular course."
The _only_ place I've ever seen someone show any creativity and ingenuity in teaching linear algebra is 3Blue1Brown, but obviously even though he's got a whole linear algebra series it's not a complete university course, nor is it meant to be.
So yeah, it's a damn shame, and IMO inexcusable. Linear Algebra is the foundation of modern data science and machine learning. Math departments should consider it a sacred duty to bring as many students as possible to at least some level of comfort and familiarity, but instead they seem to treat it as an annoying distraction at best, or a weeder class at worst.
You're totally right that LA is a superpower! I wrote a book on Linear Algebra that might be of interest to you and your daughter in case y'all want to revisit these topics. In particular it covers a lots of applications.
I first learned from Lax's book which I felt was a bit too difficult for an undergraduate course. But in a graduate level class I learned from the lecture notes of Professors Sophie Marques and Fred Greenleaf which I was a huge fan of that you can find on this website:
It's a much higher level of abstraction than an introductory Linear Algebra course but I found them amazing for developing intuition. I believe they have also released them in textbook form which is probably more polished.
I failed. I found her course to be not only sink or swim, but actively hostile to student learning. As mentioned in another post, assignments and quizzes were returned weeks late with little helpful coaching. Assignments very often worked with higher levels of abstraction than presented in the lectures, for example the first time she saw a matrix of functions was on a homework assignment.
Furthermore there seemed to be no additional help for Linear Algebra. To my great surprise the math department had no facility for matching students with tutors. The university math help center was almost exclusively oriented towards calculus and had no resources for Linear Algebra. After weeks of searching online we finally got a call back from a third party tutor, only to be informed that this person (a grad student in math) couldn't help us because the assignments were "too specific to the particular course."
The _only_ place I've ever seen someone show any creativity and ingenuity in teaching linear algebra is 3Blue1Brown, but obviously even though he's got a whole linear algebra series it's not a complete university course, nor is it meant to be.
So yeah, it's a damn shame, and IMO inexcusable. Linear Algebra is the foundation of modern data science and machine learning. Math departments should consider it a sacred duty to bring as many students as possible to at least some level of comfort and familiarity, but instead they seem to treat it as an annoying distraction at best, or a weeder class at worst.