Jun Li, Select Department | 2020-2021
Math 214 is the introduction to Linear Algebra class for non-math majors, with an emphasis of applications
of linear algebra in economics, computer science, engineering etc. Most students are those majors. Last
several years have seen the vast development of Data Science where Linear Algebra serves as the
foundation. And from a survey, students expressed a strong desire that the introductory linear algebra
class cover some applications to Data Science and machine learning, in particular, more on algorithms and
computer programming to solve real problems.
The aim of the project is to add computer programming technology of linear algebra to Math 214, both in
lectures and group works. Student group works will also be digitalized and possibly extended to build an
online project repository and will be shared with students and future instructors of this course and other
related courses. Various information technology will be used in this project: In the lectures we are going
to use programming languages that’s most popular in modern IT industry such as Python and Jupyter
notebook to demonstrate examples. Because of the Covid-19 remote instruction, all such course notes
will be written in python files and distributed to students in cloud-based services (a GitHub site has been
created for this purpose). A senior student assistant will help prepare/proofread programming files and
documents. We’ll also video record those zoom lectures and post them weekly on YouTube/Canvas. Group
work assignments that emphasizes on solving real-world problems using applied linear algebra with
computer programming will also be created, and students will collaborate through cloud-based websites.
Students who excel in their group assignments will be invited to digitize their reports and possibly do
extensions. These will then be gathered to form a digital project repository for the course.
This project is going to greatly improve the remote instruction, in the following three aspects: 1) The live
programming part in the lecture will effectively attract students’ attention in the remote instruction mode.
2) Students can download the digitized lecture notes/project solutions, and interactively play with them
using their own computers to help their self-study or review process. 3) The cloud-based way of working
on the lecture notes/projects will facilitate the collaboration between students in the current situation;
this is also great for the (future) instructors remote collaborations—all the digital project repository are
reusable and by simple revision ( changing numbers, etc.), new assignment can be generated.