Fractals, Algorithms, and Us

This summer I taught a six-week class, which I had designed over the spring, called Fractals, Algorithms, and Us. The students are currently CPS high schoolers—most are black and Latinx, roughly 80% are low-income, and about 60% will be first-generation college students. The original syllabus is here. Things had to be flexible because of the short timeline and lack of experience with the students, so we deviated from it a bit, but the course description remains true:

This course is designed around developing mathematical skills, with a focus on programming, while also taking seriously the cultural and social implications of mathematical work. We will design algorithms to solve equations, create and explore a variety of different fractals, and use neural networks to recognize images and generate art; simultaneously, we will discuss how mathematics combined with various forms of power have shaped the world, consider the ethical implications of artificial intelligence on human lives, and embark on a cross-cultural survey to reckon with the richly varied lived experiences of people doing math. 

This course will have a considerable component of in-class discussion and writing, as well as homework mostly conducted in Python, and will include a substantial final project.

I've had a lot of friends and fellow educators ask me to share the experiences of creating and facilitating this course, which I will do via this blog here and possibly by formal write-up sometime in the future. The planned outline is as follows:

• Preface: why the blog format?
• Teaching objectives: agency, power, and shared trauma in learning math.
• Building the syllabus: choosing readings and math that fit together.
• Discussion and reflection: talking about our feelings in a math class!
• Solving polynomials*: complex numbers, ancient algorithms, and wicked fractals.
• Intro to coding*: tying shoes, fun with Turtles, and sorting lists.
• Graphics and dynamics*: finding the beauty hiding in complex numbers with code.
• Indigenous math and colonialism*: the deeply human origins of math contrasted with post-colonial Eurocentrism, imperialism, and the myth of cultural neutrality.
• Neural networks*: cool math problems while peeling back the curtain on computers' assumed objectivity.
• Contemporary STEM*: gerrymandering, nuclear weapons, and marching for science.
• Final projects*: revisiting agency in math education.
• Postface*: evaluations, next steps, and math according to the students.

* = coming soon!