I'm kinda curious why so many people think that Linear Algebra Done Right is an introductory book for beginners who have math anxiety. Don't get me wrong, the book is great and I enjoyed working it through. It was a magical experience when I saw how simple it was to prove some seemingly hard theorems by just linking the right definitions and theorems. That said, the book does require certain level of math maturity as it achieves its elegance by staying at certain level of abstraction and its style is quite formal, so much so that a person who can use this book as its first linear algebra textbook shouldn't have math anxiety at all.
Speaking as one of the people who recommended it in this thread: I don't think math anxiety is the right focus for which textbook to choose. More precisely, I don't think you should try to solve that problem by getting a different linear algebra textbook. To put it bluntly, someone with math anxiety probably just doesn't have the mathematical maturity for linear algebra yet. In that case they'd be doing themselves a disservice by attempting the material using some sort of "more accessible" book; instead, they should focus on resolving that anxiety through developing a solid foundation in the prerequisite material.
Linear Algebra is typically the first course in which students have to transition from predominantly rote computation to proof-based theory. Axler's Linear Algebra Done Right is very often the textbook used for that course because it (mostly [1]) lives up to its name. This isn't Math 55: compared to Rudin and Halmos, Axler is a very accessible introduction to linear algebra for those who are ready for linear algebra. The floor for understanding this subject doesn't doesn't get much lower than Axler (and in my opinion, it doesn't get much better at the undergraduate level either).
It's unfortunate that so many people want to skip to math they're not ready for, because there's no shame in building up to it. A lot of frustration can be eliminated by figuring out what you're actually prepared for and starting from there. If that means reviewing high school algebra then so be it; better to review "easy" material than to bounce around a dozen resources for advanced material you're not ready for.
Tools from linear algebra can be accessible and useful to many people who don’t want to (or are not yet prepared to) prove nontrivial theorems. Indeed, a book like Axler’s should probably be used in a second semester-long linear algebra course for typical undergraduates wanting to study abstract mathematics; a gentler more concrete introduction would probably be better for students without previous exposure to linear algebra or hard mathematical thinking. For engineers or others who want to use linear algebra in practical contexts, something like Boyd & Vandenberghe’s new book might be a better for a first (or even second) course than Axler’s book, https://web.stanford.edu/~boyd/vmls/
Elkies’s post is in the context of a course for very well prepared and motivated first-year undergraduate pure math students who are racing through the undergraduate curriculum because most of them intend to take graduate-level courses starting in their second year.
Yes, that's precisely why I said, "This isn't Math 55: compared to Rudin and Halmos, Axler is a very accessible introduction to linear algebra for those who are ready for linear algebra."
How do you propose to teach linear algebra beyond basic matrix operations and Gaussian elimination if you're not teaching any theory? You can take some disparate tools from linear algebra (just like you can with analysis to make calculus), but The presentation of learning the mechanical tools of linear algebra versus the theory of linear algebra is a false dichotomy. Axler's textbook is a very nice compromise that provides students an understanding of why things are the way they are while still teaching them how to work through the numerical motions of things. You need not go so far as reading Finite Dimensional Vector Spaces if you want to avoid theory, but you need enough of it to put the mechanical operations in some kind of context.
Personally I think that the undergraduate mathematics curriculum does a poor job of exposing people to examples and concrete situations before introducing new abstractions.
Students are often entirely unfamiliar with the context (problems, structures, goals, ...) for the new abstractions that are rained down on them, and end up treating their proofs as little exercises in symbol twiddling / pattern matching, without much understanding of what they are doing.
The undergraduate curriculum is put in this position because there is a lot of material to get through in not much time, and students are generally unprepared coming in. Ideally students would have a lot of exposure to basic material and lots of concrete examples starting in middle school or before, but that’s not where we are.
I think we're in agreement on that point. In my experience most peoples' difficulty with higher mathematics comes from the tendency of elementary and high schools to push students along through grades without ensuring they've really mastered the material. Unfortunately most students come to hate math because they're introduced to ever more abstract and complex material when they haven't achieved a solid foundation to build upon. I don't see this artifact of our education system going away any time soon.
Personally I used David Lay's Linear Algebra and Its Applications as my first linear algebra book. It's more formal than Gilbert Strang's famous text book, but less formal than Linear Algebra Done Right. It's emphasis on geometric intuition really struck home, particularly the discussion on coordinate systems, change of basis, and quadratic forms.
For me, it really was the first time math had clicked. I had a non-proof based linear algebra course before going through the book, but it made very little sense to me. After doing LADR, I understood the subject intimately, lost my math anxiety, and performed better in every class I took afterwards than I would have otherwise.
As a teenager I thought I was bad at math and even went to get a film studies/communications bachelors (I've defended this week my masters thesis in computational mathematical physical; this after an undegraduare degree in econ with lots of math of course).
The thing is, I couldn't write the damn matrices well lined up and made mistakes when doing calculations. This was really a (de)formative experience. In college Linear Algebra for econ was 40% gaussian elimination, 40% eigenvalues and 20% linear programming. I mean, I still can't do gausian elimination by hand right.
I started crawling out of it when I started seeing (in self-study) a book on linear algebra that takes the linear transform/vector space-first approach.
