Math Academy Origin Story • Deep Dive into Math Academy and Talent Development Research • Upcoming ML and Programming Courses • Miscellaneous

If we're doing a podcast together, I'm aware that it takes quite a bit of time and effort to compile background information about an interviewee to have a thoughtful conversation.

So, I've compiled some resources that hopefully make your life easier! Don't feel obligated to read all this, but some might be worth a skim if the description catches your eye.

Events up to 2020 (from Sandy and Jason's perspective) and events 2019 and after (from my perspective, with a focus on teaching in the school program and getting the algorithms in place to turn it into a fully automated system)

News articles about our original school program where 8th graders take AP Calculus BC and then proceed on to university-level math in high school

Our quantitative CS course sequence that we ran within our original school program from 2020-23, where we scaffolded our high schoolers up from having little to no coding experience to doing masters/PhD-level coursework (reproducing academic research papers in artificial intelligence, building everything from scratch in Python)

Some info about impressive outcomes of students in our original in-school program: here and here

Podcast transcript where I talked a lot about the sequence of steps that led me to get involved in Math Academy

Nerd Level 1: Why Not Just Learn From a Textbook, MIT OpenCourseWare, Khan Academy, etc.? -- I learned from those kinds of resources myself, and while I came a long way, for the amount of effort I put into learning, I could have gone a lot further if my time were used more efficiently. That's the problem that Math Academy solves.

Nerd Level 2: Overview of our pedagogy, how our AI system works (it's an "expert system," throwback to old-school AI) and a deep dive into our spaced repetition system.

Nerd Level 3: The Math Academy Way, our 400+ page working draft book that compiles and synthesizes evidence from hundreds of scientific papers to answer the following questions: What techniques exist to maximize student learning and talent development, particularly in the context of math? Why are these techniques so impactful, and if they are indeed so impactful, then why are they so often absent from traditional classrooms? How does Math Academy leverage these techniques?

The table of contents of The Math Academy Way is very extensive and functions as a summary of the book. Each chapter also has a one-paragraph summary. Here is a not-too-out-of-date collection of all that summary info.

Kris Abdelmessih went down the rabbit hole reading The Math Academy Way and many of my blog articles, took extensive notes, and compiled them into an incredibly interesting and thoughtful synthesis called The Principles of Learning Fast.

Old table of contents (not bad, but has been continually refined) for our upcoming ML course, along with context around it

Our pedagogical approach to the ML course

We're also going to have plenty of cool coding projects, and those projects will stretch all the way up to implementing research papers from scratch.

Some info about our upcoming Intro Programming courses: here and here.

Podcast transcript where I talked a lot about the upcoming ML course at the beginning.

Previous podcasts I've been on, with summaries and transcripts, lots of stuff about Math Academy in general.

Story about a time we thought the model was broken because a 6th grader was getting Calculus tasks the same year that they placed into Prealgebra, but it turned out to be legit -- the kid completed all of what is typically high school math (Algebra I, Geometry, Algebra II, Precalculus) within a single school year.

Previous podcasts I've been on, with summaries and transcripts, lots of stuff about Math Academy in general.

Math Academy, Jason, Justin, and Alex on X/Twitter

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