Math 33A
Applied Linear Algebra
Applied Linear Algebra
Math 33A is the first course in Linear Algebra and its applications at UCLA. This course has a focus on concepts behind calculations, but also on applications, including solving systems of linear equation, linear regression using orthogonal projections, discrete dynamical systems using eigenvalues and eigenvectors, and singular value decomposition.
Prerequisites: Student's should have taken at least one course in Calculus, or another college-level math course
Text: Otto Bretscher's Linear Algebra with Applications 5th ed.
Syllabus (Spring 2021)
I taught Math 33A in Fall 2020, Spring 2021 and am scheduled to teach it in Fall 2021 and Spring 2022. This is approximately 1000 students per year.
This course is taught in a flipped format. This means the primary material is conveyed through pre-recorded videos and class time is used for worksheets, Q&A and to go over additional examples and supplementary material.
Coming in Fall 2021:
I am in the process of converting this course to mastery-based grading. This is a system of evaluating students based on their demonstrated mastery of material rather than their final exam score. Mastery-based grading will:
Base all student grades on their achievements relative to clear expectations, rather than their performance relative to other students. This makes the course more equitable!
Increase flexibility for students and gives them a greater sense of agency over their learning.
Communicate to students the exact requirements to earn a particular grade and highlight which skills from the class are essential for their forward progress.
Incentivize learning for learning’s sake, and encourage students to approach the material with a growth mindset.
Maintain rigorous expectations for students, and ensure that grades better reflect the knowledge students carry with them into subsequent courses. For example, any student who receives a C under mastery-based grading must have completely mastered 70% of the material. This is in contrast to the current system where a student can earn a C by partially understanding all of the material, but without having completely mastered any of the learning objectives.
Finally, by rendering transparent exactly what is required for success, mastery-grading helps all of our students succeed.