Speaker
- Ankur Moitra (MIT)
Details
In Fall 2020, we piloted a new version of introductory linear algebra at MIT (and have been teaching it ever since). Our goal was to emphasize modeling and computation, and not just problems that have a recipe-driven solution. For example, when you come across a problem in another domain, can you recognize when it is just linear algebra in disguise? Such examples help students better appreciate the expressive power of the abstractions they are learning. We also integrate hands-on projects so that students can put what they've learned into action. In this talk I will give some salient examples, report on our experiment, and what we've learned along the way. I will also discuss how our course came about (spoiler: It was driven by growing demand for a new data science major).
