It’s shocking how much we know about how learning happens, all the way down to the mechanics of what’s going on in the brain. And it’s not just how learning happens, but also, what we can do to improve learning. There are plenty of learning-enhancing practice strategies that have been tested scientifically, numerous times, and are completely replicable. They might as well be laws of physics. For instance: we know that actively solving problems produces more learning than passively watching a video/lecture or re-reading notes. (To be clear: active learning doesn’t mean that students never watch and listen. It just means that students are actively solving problems as soon as possible following a minimum effective dose of initial explanation, and they spend the vast majority of their time actively solving problems.) Another finding: if you don’t review information, you forget it. You can actually model this precisely, mathematically, using a forgetting curve. I’m not exaggerating when I refer to these things as laws of physics – the only real difference is that we’ve gone up several levels of scale and are dealing with noisier stochastic processes (that also have noisier underlying variables). Okay, but aren’t these findings obvious? Yes, but… Yes, but in education, obvious strategies often aren't put into practice. For instance, plenty of classes that still run on a pure lecture format and don't review previously learned unless it's the day before a test. Yes, but there are plenty of other findings that replicate just as well but are not so obvious. Here are some less obvious findings. -- The spacing effect: more long-term retention occurs when you space out your practice, even if it's the same amount of total practice. -- A profound consequence of the spacing effect is that the more reviews are completed (with appropriate spacing), the longer the memory will be retained, and the longer one can wait until the next review is needed. This observation gives rise to a systematic method for reviewing previously-learned material called spaced repetition (or distributed practice). A "repetition" is a successful review at the appropriate time. -- To maximize the amount by which your memory is extended when solving review problems, it's necessary to avoid looking back at reference material unless you are totally stuck and cannot remember how to proceed. This is called the testing effect, also known as the retrieval practice effect: the best way to review material is to test yourself on it, that is, practice retrieving it from memory, unassisted. -- The testing effect can be combined with spaced repetition to produce an even more potent learning technique known as spaced retrieval practice. -- During review, it's also best to spread minimal effective doses of practice across various skills. This is known as mixed practice or interleaving -- it's the opposite of "blocked" practice, which involves extensive consecutive repetition of a single skill. Blocked practice can give a false sense of mastery and fluency because it allows students to settle into a robotic rhythm of mindlessly applying one type of solution to one type of problem. Mixed practice, on the other hand, creates a "desirable difficulty" that promotes vastly superior retention and generalization, making it a more effective review strategy. -- To free up mental processing power, it's critical to practice low-level skills enough that they can be carried out without requiring conscious effort. This is known as automaticity. Think of a basketball player who is running, dribbling, and strategizing all at the same time -- if they had to consciously manage every bounce and every stride, they'd be too overwhelmed to look around and strategize. The same is true in learning. -- The most effective type of active learning is deliberate practice, which consists of individualized training activities specially chosen to improve specific aspects of a student's performance through repetition (effortful repetition, not mindless repetition) and successive refinement. However, because deliberate practice requires intense effort focused in areas beyond one's repertoire, which tends to be more effortful and less enjoyable, people will tend to avoid it, instead opting to ineffectively practice within their level of comfort (which is never a form of deliberate practice, no matter what activities are performed). -- Instructional techniques that promote the most learning in experts, promote the least learning in beginners, and vice versa. This is known as the expertise reversal effect. An important consequence is that effective methods of practice for students typically should NOT emulate what experts do in the professional workplace (e.g., working in groups to solve open-ended problems). Beginners (i.e. students) learn most effectively through direct instruction. Now, this might seem like a lot of new information -- a common reaction is “Wow, the field of education is experiencing a revolution!” But here’s the thing: Most key findings have been known for many decades. It’s just that they’re not widely known / circulated outside the niche fields of cognitive science & talent development, not even in seemingly adjacent fields like education. These findings are not taught in school, and typically not even in credentialing programs for teachers themselves – no wonder they’re unheard of! But if you just do a literature review on Google Scholar, all the research is right there – and it’s been around for many decades. Naturally, this leads us to the following question: Why aren't these key findings being leveraged in classrooms? Why do they remain relatively unknown? Here are a handful of reasons that I’m aware of. 1. Leveraging them (at all) requires additional effort from both teachers and students. In some way or another, each strategy increases the intensity of effort required from students and/or instructors, and the extra effort is then converted into an outsized gain in learning. This theme is so well-documented in the literature that it even has a catchy name: a practice condition that makes the task harder, slowing down the learning process yet improving recall and transfer, is known as a desirable difficulty. Desirable difficulties make practice more representative of true assessment conditions. Consequently, it is easy for students (and their teachers) to vastly overestimate their knowledge if they do not leverage desirable difficulties during practice, a phenomenon known as the illusion of comprehension. However, the typical teacher is incentivized to maximize the immediate performance and/or happiness of their students, which biases them against introducing desirable difficulties and incentivizes them to promote illusions of comprehension. Using desirable difficulties exposes the reality that students didn’t actually learn as much as they (and their teachers) “felt” they did under less effortful conditions. This reality is inconvenient to students and teachers alike; therefore, it is common to simply believe the illusion of learning and avoid activities that might present evidence to the contrary. 2. Leveraging cognitive learning strategies to their fullest extent requires an inhuman amount of effort from teachers. Let’s imagine a classroom where these strategies are being used to their fullest extent. -- Every individual student is fully engaged in productive problem-solving, with immediate feedback (including remedial support when necessary), on the specific types of problems, and in the specific types of settings (e.g., with vs without reference material, blocked vs interleaved, timed vs untimed), that will move the needle the most for their personal learning progress at that specific moment in time. -- This is happening throughout the entirety of class time, the only exceptions being those brief moments when a student is introduced to a new topic and observes a worked example before jumping into active problem-solving. Why is this an inhuman amount of work? -- First of all, it's at best extremely difficult, and at worst (and most commonly) impossible, to find a type of problem that is productive for all students in the class. Even if a teacher chooses a type of problem that is appropriate for what they perceive to be the "class average" knowledge profile, it will typically be too hard for many students and too easy for many others (an unproductive use of time for those students either way). -- Additionally, to even know the specific problem types that each student needs to work on, the teacher has to separately track each student's progress on each problem type, manage a spaced repetition schedule of when each student needs to review each topic, and continually update each schedule based on the student's performance (which can be incredibly complicated given that each time a student learns or reviews an advanced topic, they're implicitly reviewing many simpler topics, all of whose repetition schedules need to be adjusted as a result, depending on how the student performed). This is an inhuman amount of bookkeeping and computation. -- Furthermore, even on the rare occasion that a teacher manages to find a type of problem that is productive for all students in the class, different students will require different amounts of practice to master the solution technique. Some students will catch on quickly and be ready to move on to more difficult problems after solving just a couple problems of the given type, while other students will require many more attempts before they are able to solve problems of the given type successfully on their own. Additionally, some students will solve problems quickly while others will require more time. In the absence of the proper technology, it is impossible for a single human teacher to deliver an optimal learning experience to a classroom of many students with heterogeneous knowledge profiles, who all need to work on different types of problems and receive immediate feedback on each attempt. 3. Most edtech systems do not actually leverage the above findings. If you pick any edtech system off the shelf and check whether it leverages each of the cognitive learning strategies I’ve described above, you’ll probably be surprised at how few it actually uses. For instance: -- Tons of systems don't scaffold their content into bite-sized pieces. -- Tons of systems allow students to move on to more material despite not demonstrating knowledge of prerequisite material. -- Tons of systems don't do spaced review. (Moreover, tons of systems don't do ANY review.) Sometimes a system will appear to leverage some finding, but if you look more closely it turns out that this is actually an illusion that is made possible by cutting corners somewhere less obvious. For instance: -- Tons of systems offer bite-sized pieces of content, BUT they accomplish this by watering down the content, cherry-picking the simplest cases of each problem type, and skipping lots of content that would reasonably be covered in a standard textbook. -- Tons of systems make students do prerequisite lessons before moving on to more advanced lessons, BUT they don't actually measure tangible mastery on prerequisite lessons. Simply watching a video and/or attempting some problems is not mastery. The student has to actually be getting problems right, and those problems have to be representative of the content covered in the lesson. -- Tons of systems claim to help students when they're struggling, BUT the way they do this is by lowering the bar for success on the learning task (e.g., by giving away hints). Really, what the system needs to do is take actions that are most likely to strengthen a student's area of weakness and empower them to clear the bar fully and independently on their next attempt. Now, I’m not saying that these issues apply to all edtech systems. I do think edtech is the way forward here – optimal teaching is an inhuman amount of work, and technology is needed. Heck, I personally developed all the quantitative software behind one system that properly handles the above challenges. All I’m saying is that you can’t just take these things at face value. Many edtech systems don’t really work from a learning standpoint, just as many psychology findings don’t hold up in replication – but at the same time, some edtech systems do work, shockingly well, just as some cognitive psychology findings do hold up and can be leveraged to massively increase student learning. 4. Even if you leverage the above findings, you still have to hold students accountable for learning. Suppose you have the Platonic ideal of an edtech system that leverages all the above cognitive learning strategies to their fullest extent. Can you just put a student on it and expect them to learn? Heck no! That would only work for exceptionally motivated students. Most students are not motivated to learn the subject material. They need a responsible adult – such as a parent or a teacher – to incentivize them and hold them accountable for their behavior. I can’t tell you how many times I’ve seen the following situation play out: -- Adult puts a student on an edtech system. -- Student goofs off doing other things instead (e.g., watching YouTube). -- Adult checks in, realizes the student is not accomplishing anything, and asks the student what's going on. -- Student says that the system is too hard or otherwise doesn't work. -- Adult might take the student's word at face value. Or, if the adult notices that the student hasn't actually attempted any work and calls them out on it, the scenario repeats with the student putting forth as little effort as possible -- enough to convince the adult that they're trying, but not enough to really make progress. In these situations, here’s what needs to happen: -- The adult needs to sit down next to the student and force them to actually put forth the effort required to use the system properly. -- Once it's established that the student is able to make progress by putting forth sufficient effort, the adult needs to continue holding the student accountable for their daily progress. If the student ever stops making progress, the adult needs to sit down next to the student again and get them back on the rails. -- To keep the student on the rails without having to sit down next to them all the time, the adult needs to set up an incentive structure. Even little things go a long way, like "if you complete all your work this week then we'll go get ice cream on the weekend," or "no video games tonight until you complete your work." The incentive has to be centered around something that the student actually cares about, whether that be dessert, gaming, movies, books, etc. Even if an adult puts a student on an edtech system that is truly optimal, if the adult clocks out and stops holding the student accountable for completing their work every day, then of course the overall learning outcome is going to be worse.

universities are still offering translation courses

THE NETWORK SCHOOL We got an island. That’s right. Through the power of Bitcoin, we now have a beautiful island near Singapore where we’re building the Network School. We’re starting with a 90-day popup that runs from Sep 23 to Dec 23, right after the Network State Conference. Rent is only $1000/month with roommates or $2000/month solo. And we have plenty of day passes for visitors. So, go apply online at ns dot com! Then read more below. THE DARK TALENT As motivation, I’ve always wanted to expand equality of opportunity around the world. Because my father was born in a desperately poor country, but with the right opportunity he was able to make something of himself. Like dark matter, he was dark talent. And for more than a decade I’ve been thinking about how to give others who are similarly situated the chance to make something of themselves. That is: I’ve been thinking about how to empower the dark talent of the world. US universities used to fill this role, even imperfectly, and I loved Stanford when I taught there years ago. But the data shows they’ve declined in recent days. And they’re just not affordable or accessible to most of the world. So, it’s time for a new approach. And thanks to Saraswati and Satoshi, I have the resources to endow a new Internet-first institution: the Network School. The purpose of the Network School is to articulate a vision of peace, trade, internationalism, and technology…even as the rest of the world talks about war, trade war, nationalism, and statism. To revitalize democracy for the internet era, with digital polities and verifiable votes. To train the next generation to be not just leaders of companies, but inspirations for their communities. And to pursue truth, health, and wealth by leveling up our attendees personally, physically, and professionally. Let me now describe in more detail how the Network School works, who it’s for, and how to apply. HOW THE NETWORK SCHOOL WORKS The Network School is for people of all ages, not just the youth. And it’s meant to be lifelong rather than one-off, with both a structured and and an unstructured component. The structured part is about continuous daily self-improvement: learning skills, burning calories, and earning currency. Meanwhile, the unstructured part is about having fun and hanging out with people of similar values. For short: learn, burn, earn, and fun. Learn The first part of the Network School is about learning technologies and humanities. As motivation, the existing model of US undergraduate education is broken. You pay $100k+ for a four year degree, and then budget nothing for maintenance over the course of your life. It’s like paying $100k+ for a new car and budgeting nothing for maintenance. By contrast, the Network School is about continuous education. It’s for remote workers, engineers, creators and digital nomads who want to integrate learning into their lives, rather than stopping everything to be a full-time student. Here’s how that works. We set up mini-classrooms where you can drop in to see the problem of the day.5 You solve that problem and a proctor awards you a cryptocredential, a free non-transferable NFT sent to your crypto wallet that establishes “proof-of-learn.” Often your solution will involve putting code on GitHub/Replit (to show you understand a concept), or posting content to your social media profile (to show you understand a new AI tool). And over time, these cryptocredentials actually build up a cryptoresume proving what you know. Our initial material focuses on founding tech communities, as distinct from tech companies. As such it touches on everything from crypto, AI, and social media to history, politics, and filmmaking. It should be useful even if you’re just growing a traditional company or building a following. Over time, of course, every branch of the sciences and humanities becomes relevant when building a community. So if this initial experiment works, we can expand branch-by-branch to build a new kind of university. But we’re intentionally starting with something simple. Our learning is about continuous education, about solving the problem-of-the-day. Burn The second part of the Network School is about burning calories. Longevity is important, but 20th century communities just aren’t physically set up to maximize physical fitness. Quite the contrary: the default mode of Western society is sedentary and sugary. Those who want to escape this need to roll their own nutrition and workout program, which takes time, money, and energy. We’re changing that. I’ve teamed up with my friend @bryan_johnson to set up Blueprint-inspired food and fitness for the entire Network School community. Bryan will be on campus to set up the program, and then his designates will maintain it on a daily basis. Like many of you, I’ve been both fit and fat at various times, so this is a product I want to use myself. Every member of the Network School gets a daily workout slot with a semi-personal trainer, much like a group fitness class. You run and lift in the morning at your chosen time, getting a proof-of-workout from your trainer. Your group holds you accountable for showing up. Then you get a box with your Blueprint-optimized healthy meals and head to work. The whole point is to provide willpower-as-a-service, where the community6 provides the discipline. We’re starting with the basics of running, lifting, eating, and sleeping properly. The initial goal is to hit the limits of your genetics. But if all goes well, the biotech founders that come to the Network School will eventually help us all surpass our genetic limits, to live much longer than we otherwise would. But again, we’re starting small! And so the “burning calories” part is about lifelong health and the workout-of-the-day. Earn The third part of the Network School is about earning currency. We’ll have crypto prizes of the day for open source projects, AI content creation, and microtasks. There will be $1000 bounties every day for the duration of the program, similar to the various prizes I’ve posted on Twitter and Farcaster. And community members will post their own prizes. Next, in keeping with the overall theme of self-improvement, we’ll have office hours to help with your job, your career, your visa status, and your funding. We’re much more invested in you than a typical college career center because our interests are aligned: the more you earn, and the stronger you are financially, the more you’ll eventually have to reinvest in the community. Finally, we’ll have visitor hours with famous visiting technologists. As my friend Sriram noticed, when investors come through Singapore I typically do a podcast with them. Many will also visit the Network School to meet attendees, invest in them, or hire them. Others will give remote talks. And you can see the quality of visitors from the speakers in our conference and podcast. So, earning is about constant career development and the prize-of-the-day. Fun All work and no play makes Jack a dull boy, of course. So the fourth part of the Network School is about fun. This is the unstructured component. It’s most of what you’re here for. It’s just about assembling great people in one place: positive-sum people who believe in technological progress, internationalism, and capitalism. It’s your internet friends, coming from URL to IRL. Stanford introduced the concept of residential education, but this takes it to the next level. In fact, our initial location is very similar to Stanford. It’s beautiful and sunny, and less than an hour from a major city (Singapore) with an international airport (Changi). That means you can be heads down during the week, head into the city on the weekends for fun, and get to just about anywhere in Asia within the same day. This is convenient for the >50% of the world that lives within the Valeriepieris circle. We’ll do some group outings too, but most of the fun will be up to you. WHO THE NETWORK SCHOOL IS FOR Who is the Network School for? There are four lenses on this: demographical, ideological, professional, and personal. Demographically As mentioned, our focus is the dark talent. The more respect you have for legacy institutions, and the more respect they have for you, the less suitable you’ll be as an applicant. So: the Network School is for Indian engineers and African founders, for makers from the Midwest and the Middle East, for Chinese liberals and Latin American libertarians, for Southeast Asia’s rising technologists and Europe’s remaining capitalists. It’s for everyone who doesn’t feel part of the establishment. But it’s definitely not only for tech, because a community does not run on tech alone. Ideologically Ideologically, the Network School is for people who admire Western values, but who also recognize that Asia is in ascendance, and that the next world order is more properly centered around the Internet — around neutral code — than around either declining Western institutions or a rising Chinese state. For example, the Network School is for those who understand that Bitcoin succeeds the Federal Reserve, that encryption is the only true protection against unreasonable search and seizure, that AI can deliver better opinions than any Delaware magistrate, and that democracy can be rejuvenated with cryptography. It is for those who believe in technology, harmony, internationalism, and capitalism. It’s for those who want Silicon Valley without San Francisco. And for those who want to found, fund, and find not just new companies and currencies — but new cities and new communities. Professionally Our ideal applicant is capable of remote work, or has enough savings to support themselves while at the Network School. For our initial cohort, we’re seeking three major groups of people in particular: - Writers, artists, influencers, and filmmakers - Trainers, athletes, coaches, and clinicians - Founders, engineers, designers, and investors These are, roughly, the demographics focused on learning, burning, and earning respectively. Of course, if you fall outside those categories but still think you have something to contribute, you should still apply to the Network School. Personally I should mention that the Network School is a “product” that I built for the young version of myself — the aspiring young engineer. This is the community I want to live in: a technocapitalist college town, a Stanford 2.0 that’s globally affordable and genuinely meritocratic. So, I’ll be on campus full time. Bryan Johnson and I are supervising the setup of everything from bench press to French press. And we’ll eventually be recruiting faculty in the form of content creators, fitness influencers, and angel investors for the learn, burn, and earn portions of our program respectively. But all that in due time. APPLYING TO THE NETWORK SCHOOL Ok, so how do you apply to the Network School? Just go to ns dot com and click "apply." We’ve set up a simple Luma page where you can apply in a few minutes. Then, if you pass review, we’ll send a second application where you pay rent. As mentioned, our monthly rent is $1000 (with roommates) and $2000 (solo). We also have daily and weekly rates too, but short-term visitors still need to apply. The rent gets you an air-conditioned room on a beautiful island, with internet, gym, and access to all courses and community services. You’ll still need to handle your flights and pay for your food, but we think the overall package is extremely affordable. And so the Network School could be an amazing option for individuals or small teams looking to save money, get fit, and level up while living in paradise. I’m looking forward to seeing you there! Just fill out the application at ns dot com, also linked in the tweet below.

It actually makes perfect sense to have a team of cracked zoomers on DOGE. You want people who look at a system and say “this sucks, let’s start from scratch” - not “how can I work in this bureaucracy to further my career?” Can you imagine if it were Google employees instead?

The legacy media is pure propaganda. You are the media now.

Do you think the Department of Education be abolished?

@HindenburgRes so based