Math Academy

Math Academy

Stories, challenges, and discoveries from the front lines of building the ultimate math learning system.

Episodes

  1. 18 DEC

    #5, Part 2 – Getting Kids To Do Hard Things

    What we covered: – Most kids are not intrinsically motivated to do the hard things: practice their soccer drills, do their math homework, eat their broccoli. Getting them to do the hard things often requires gamification and/or incentives. – A little gamification goes a long way. Jason gamified drills for his kids’ soccer team to get the most out of each practice (e.g., “zombie attack”), and it was unreasonably effective. XP and leaderboards on Math Academy are also unreasonably effective. – A good incentive can change kids' behavior overnight. The incentive doesn’t need to be big; it just needs to be something the kid really cares about. Find the thing the kid would rather be doing, and use it to motivate them to do what they’re supposed to be doing. They won’t need the incentive forever; as the kid gets used to the feeling of a new behavior, it gradually turns into a habit that they can maintain on their own. – Even when you’re doing what you love, there will be grindy phases. But kids typically don’t understand this. They might get interested in a talent domain and want to become good enough to build a life around it, while simultaneously resisting doing the hard work to make that happen (i.e., stage 2 in Bloom’s talent development process). It’s often up to parents, who can see the long game, to push their kids through the difficult parts in paths that they find rewarding. – For instance, the most mathematically gifted student Justin ever worked with, who was drawn into math by his own intrinsic interest, still needed to be pushed to learn calculus. Now he’s having the time of his life working on physics-y, calculus-heavy research-level math problems in high school. Even after finding something he loves and is good at, he still needed to be pushed to do the hard work to unlock more of it. Timestamps: 00:00:00 - Most kids are not intrinsically motivated to do hard things – homework, drills, practice. They usually need incentives to get through. 00:08:16 - A little gamification goes a long way. Jason gamified drills for his kids’ soccer team to get the most out of each practice (e.g., “zombie attack”). 00:14:05 - A good incentive can change behavior overnight. It doesn’t need to be big, just something the kid really cares about, and they won’t need it forever. It’s about building a habit until they can maintain it on their own. 00:41:17 - The stress of high school 00:54:16 - The most mathematically gifted student Justin ever worked with needed to be pushed to learn calculus, and now he's having the time of his life working on calculus-heavy research-level math problems. 01:11:54 - Even when you’re doing what you love, there will be grindy phases. It’s important for parents to help kids push through those grindy phases so that they can unlock more of what they love.

    1h 41m

  2. 11 DEC

    #5, Part 1 – Building Without Bloat

    What we covered: – Any successful endeavor requires a great team: capable people, who like and trust each other, and have complementary skillsets and ways of thinking. Some modes of thinking cannot be performed at the same time within a single brain. – Accountability requires control. You can’t hold someone responsible for outcomes unless you also give them control over the system that produces those outcomes (though you can set reasonable operational boundaries). – Solve today’s problems today. Smart people can invent endless hypotheticals and build giant solutions to fake problems. Not only does this waste time, but it also burdens the system with complexity that becomes a future straitjacket. Everything you build must be carried forward, so focus on what’s present in front of you, not on imagined futures five steps away. – In a scaling system, the sheer volume of interactions will expose a long tail of bizarre scenarios, almost like rare diseases you’d never anticipate. Users will often try to repurpose software beyond its design, like hauling a trailer with a motorcycle. Timestamps: 00:00 - Introduction 03:48 - The importance of finding your complements 24:07 - The origin story of Math Academy's content team 43:36 - No meta-work; just solve the problems in front of you 54:26 - Jason time vs real time (real time is longer) 59:00 - The long tail of rare edge cases and unexpected user behavior

    1h 17m

  3. 3 DEC

    #4, Part 2 – Knowledge Graph Engineering: Mental Models & War Stories

    What we covered: – Building a knowledge graph is like city planning & road construction. Too many prerequisites leading into a single topic creates a cognitive traffic jam. – Elegantly rewiring a live knowledge graph: the evolution of our tooling and automatic validations. How to avoid staging servers & migrations and NOT have it blow up in your face. – UI work takes time and adds complexity, so we spend it on the customer. Internal tools are almost entirely command-line; clickable buttons are for customers. – Justin's transition from research coding to real-time systems. He started with mathy, notebook-driven quant code and had to learn production engineering the hard way. Once he did, it was a massive level-up. – Alex's plan for dealing with "content papercuts" - small issues that pile up. Inspired by Amazon’s “papercuts team.” – Our upcoming differential equations course, the last course in the core undergrad engineering math sequence. Timestamps: 00:00:00 - Building a production-grade knowledge graph is like city planning and road construction 00:07:26 - Elegantly rewiring a live knowledge graph: the evolution of our tooling and automatic validations 00:24:47 - Justin's transition from research coding to real-time systems 00:44:51 - Alex's plan for dealing with "content papercuts" - small issues that pile up 00:58:02 - Our upcoming differential equations course

    1h 20m

  4. 25 NOV

    #4, Part 1 – The Unreasonable Effectiveness of the Knowledge Graph

    What we covered: – Why “problem solving” is often just a vague label people use when they haven’t explicitly enumerated the underlying skills, and how those skills can in fact be exhaustively mapped in a knowledge graph. – How to approach research problems: Alex's PhD journey, top-down familiarity vs bottom-up mastery. – If you have natural talent, use it, but not as a crutch, otherwise you'll stunt your long-term development. Don't turn your blessing into a curse. – The story behind building our SAT prep curriculum: realizing that the standard school curriculum leaves a massive “missing middle” unaddressed; identifying 115+ missing topics to bridge the gap between textbook math and the hardest SAT questions. – Watching the manifold hypothesis play out in test prep: the SAT may appear to allow an astronomical space of possible problem types, but in reality the actual problems live on a compact, highly structured manifold that can be fully enumerated and scaffolded in a knowledge graph. Timestamps: 00:00 - Intro: "problem solving" is what you call it when you don't really know what it is (i.e. you haven't explicitly enumerated the skills) 04:11 - How to approach research problems: Alex's PhD journey, top-down familiarity vs bottom-up mastery 20:28 - If you have natural talent, don't use it as a crutch. Don't turn your blessing into a curse. 29:06 - SAT prep, iteration 1: Realizing that the standard school curriculum leaves a massive “missing middle” unaddressed 33:45 - SAT prep, iteration 2: Covering the "missing middle" problems 53:38 - SAT prep, iteration 3: Building the "missing middle" knowledge graph 1:08:11 - Watching the manifold hypothesis play out in SAT prep 1:16:42 - The unreasonable effectiveness of the knowledge graph

    1h 22m

  5. 18 NOV

    #3 – Waging War on Mediocrity: Tales From the Trenches

    What we covered: -- How bureaucracies instinctively reject new ideas like an immune system attacking a foreign organ, and what it takes to keep your project from being "spit out." Concrete example: how Jason & Sandy muscled past institutional resistance to get 8th graders passing AP Calc BC. -- Every system inevitably decays into mediocrity unless someone fights to keep the standards high. The way you keep people, systems, and projects moving is by "horsing" them forward. Concrete example: how Justin kept 8th graders passing AP Calc BC, and what it looks like when a school succumbs to the gravity of mediocrity. -- Justin's math self-study journey in high school: grinding math like a video game, running a secret self-study op inside traditional classes, taking talent development seriously while simultaneously hitting his head on every ledge and making every rookie mistake. Ups and downs, lessons learned, with tons of concrete examples.Timestamps: 00:00:00 - Intro: Willing Things Into Existence 00:11:43 - How Jason & Sandy Willed Math Academy Into Existence 00:36:45 - Fighting The Gravity of Mediocrity 01:02:29 - Case Studies in Educational Dysfunction 01:21:53 - The Birth of Justin’s Self-Study Madness 01:50:48 - Self-Studying on the Sly During School 02:02:41 - The Highs & Lows of High School Research 02:22:38 - Outro: Paving the Path with Math Academy

    2h 29m

  6. 4 NOV

    #2 – Teach Like Your Life Depends On It

    0:00 - What Would a Tutor Do, If Their Life Depended On It? (Part 1) 5:47 - Find Your North Star: Why Justin Quit His Data Science Job to do Math Tutoring Full Time 11:23 - Getting "Inside the Trade" 19:31 - What Would a Tutor Do, If Their Life Depended On It? (Part 2) 27:28 - Efficient Learning Techniques are Obvious if You Think About Athletics 33:45 - Enjoyment is a Second-Order Optimization 39:50 - We Need to Stay Hardcore, But Become Less Harsh 51:14 - Math Academy is Like "Yuri's Gym" 59:06 - Vision for the Future of Math Academy 1:14:23 - Goal Setting/Advising and Communicating Progress 1:24:58 - If All You Show Up With is AP Calculus, You're Probably Outgunned 1:51:08 - The Meta-Skills that Kids Need to Work Effectively on Math Academy 2:08:54 - How to Help Students Maintain Successful Learning Habits While Working Independently 2:32:29 - Overhelping: A Common Failure Mode of Well-Intentioned Parents/Tutors

    2h 43m

  7. 3 NOV

    #1 – The Long Game: Building Minds and Machines

    0:00 - Introduction 4:00 - Applying the MA Way to X Growth 7:40 - Status of the ML Course and its Kick-Ass Coding Projects (Part 1) 25:50 - Jason's Near-Infinite List of Important Things 34:20 - The ML Course Has Been a Massive Undertaking 42:10 - Breadth-First Development 44:30 - Status of the ML Course and its Kick-Ass Coding Projects (Part 2) 50:15 - Why Math Academy Needs To Do a CS Course 56:45 - The Never-Ending Stream of Confusion 1:00:30 - The Story of Eurisko, the Most Advanced Math/CS Track in the USA 1:24:20 - Intuition Through Repetition: Machine Learning Edition 1:29:40 - The Importance of Spaced Review 1:43:30 - Upcoming Course Roadmap 1:47:40 - Spaced Repetition 2.0: Accounting For and Discouraging Reference Reliance 1:54:45 - Overhelping: A Pathology of the Over-Involved Parent/Tutor 1:59:21 - Yes, You Need to be Automatic on Math Facts (and Yes, Rapid-Fire Training is Coming) 2:04:55 - What Happens When Students Don't Know Their Math Facts 2:05:50 - The Horror of Attempting to Teach a Class When Students Have Multi-Year Deficits in Fundamental Skills 2:11:30 - Integrating Coding Into the Math Curriculum 2:18:00 - Combining Math and Coding is the Closest Thing to a Real-Life Superpower 2:18:55 - Creating a Full Math Degree and Getting Full College Credit 2:22:15 - The Power of Pre-Learning: The Greatest Educational Life Hack

    2h 36m
  • 7 Episodes

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Stories, challenges, and discoveries from the front lines of building the ultimate math learning system.

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  • Creator
    Math Academy
  • Years Active
    2K
  • Episodes
    7
  • Rating
    Clean
  • Copyright
    © Math Academy
  • Show Website
    Math Academy

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