Justin Baeder, PhD

I’m thrilled to announce that my new book with Keith Fickel is available for pre-order! Cultivate & Activate: Building Teacher Capacity for Instructional Leadership Ships May 2026 a.co/d/09pc4IKs

Massive respect for a proposal that actually states a bold, falsifiable hypothesis! I’d take a testable proposal I believe is incorrect over a vague study that can prove nothing—any day of the week.

@teachthemx3 Congrats! My prediction is that: ~5% of students will move faster and learn more; ~5% will move slower and learn more, because they’re getting it all; and ~90% will learn less because of the loss of teacher pacing. Watch out for selection & attrition. Good luck!

Met with my doctoral advisor to discuss my dissertation topic. He asked, “What problem in education do you want to solve?” I said: “Students should be able to move through curriculum at their own pace (with a required minimum).” He replied, “That’s not possible. It’s too expensive to individualize education. Why not focus on improving test scores or student engagement?” I said, “If you individualize instruction, those issues improve naturally.” (20 minutes later) He said, “I’m not sure I agree, but it’s clear you care deeply about this. I’ll approve it.”

@kendallbaker Small town resident here. Never much wait, especially if you have an appointment. The DMV is fast and competent plenty of places.

Was just at the DMV (kill me) and it got me wondering… Does LeBron James have to go to the DMV? Does Jeff Bezos have to stand in line for 2 hours to renew his license?

@ProfArbel Doesn’t seem like you’ve really thought about what makes it bad pedagogy, and the direction of the influence AI might have on pedagogy. I’d contend it’s always worse. If you’re struggling to understand a concept from the book, read more closely. Read more books. Ask a human.

This is a bad policy. Lots of people are calling it unenforceable. They're almost right, but that's not the real issue. It's a bad policy because it's bad pedagogy. First, a prediction: Berkeley walks this back within three years. If you disagree, be brave enough to stake your position now. On enforceability. Technically it's enforceable, in the same way prohibitions on apostasy are enforceable: you collect testimony and you punish people. Detection here hinges on the professor's gut. Too many em dashes? F. You don't have the occasional typo? Sus! The pro-enforcement camp implicitly assumes professors possess some innate AI-detection power. They don't. The result is a regime saturated with Type 1 and Type 2 errors. oh, and if you mess up your bluebooking? a citation to a non-existent source automatically "raise[s] a presumption of prohibited AI use." But I care more about the pedagogy. Tucked into the rule is a prohibition on uploading "course materials, including assignments, readings, slides, class recordings, or other class content" into generative AI systems. That means a Berkeley student can't ask ChatGPT to quiz them before an exam. Can't ask it to explain voir dire at a tractable level. Can't use it as a patient, infinite, on-demand tutor on the vagaries of the rule against perpetuities These are extraordinary tools, and we're building more of them (wait for it). Students at competing schools will have them. Berkeley students won't. Beyond the competitive disadvantage, the harder question is this: how do faculty explain that this isn't about protecting professorial IP, real or imagined, but about serving students? The motte defenders retreat to is this: we need to build Core Competencies(TM), and you can't do that by letting students reach for AI on day one. The motte's true. But it is vastly narrower than the bailey that the policy creates. The policy rests on the assumption that the core competencies of a 1990 lawyer will remain the core competencies of a 2029 lawyer, that the AI revolution will be no bigger than the move from print reporters to Boolean searching on Westlaw. That's wild! Practice is already changing. If you don't have an agentic swarm running in the background right now, you're behind. Push defenders on which competencies, exactly, and the answers fall into three buckets. First, skills heading for obsolescence: manual bluebooking, drafting boilerplate from scratch, first-pass document review, summarizing depositions by hand. Second, skills that are real but almost certainly better trained with AI than against it: issue spotting drilled against an infinite supply of hypotheticals, brief feedback in seconds rather than weeks, writing improved through structured iteration with a tireless reader. Third, skills so vague they can't be measured. "Thinking like a lawyer." "Professional judgment." For these we have no way to know whether AI helps or hurts, yet the policy assumes it must hurt. But it's only a default, right? Well defaults matter, and this one's sticky. Professors have to opt out in writing. Even when they do, students *must* disclose every instance of AI use, which today already implicates using Google. Any ambiguity resolves against the student. The structural message is legible and loud: AI use is presumptively cheating. That message is wrong about almost everything. It's wrong about the technology, which isn't a shortcut but a new kind of cognitive partner. It's wrong about practice, where AI is already pervasive in the firms students are about to enter. It's wrong about teaching, by suggesting pedagogy needs no innovation in the face of the most powerful educational tool in a generation. And it's wrong about students, by casting those who use AI thoughtfully as people who lack fundamental skills, rather than as the lawyers Berkeley should be proudest to graduate. The best legal careers of the next decade will belong to lawyers who know when to use AI, when not to, how to verify it, how to weave it into legal reasoning, and how to supervise it in client matters. Policies like this one belong to those who resigned themselves to sit out this future.

RAND is a rigorous enough shop report the data honestly, but not familiar enough with education to interpret it correctly.

My prime example is the many RAND studies on school discipline, which are commissioned to provide evidence for restorative justice and similar practices. fordhaminstitute.org/national/comme…

It’s worth pointing out that *the authors themselves* sometimes draw the wrong conclusion from their data.

Letting students use AI is pulling the ladder up behind you.

@mathillustrated You, Ralph from New Jersey, are an ignorant, jealous hack, and Dr. Anna Stokke is a true expert in mathematics education. Hope this clears things up. Now shut your stupid mouth and show some respect. —Justin from New Jersey

Article claims Anna Stokke is “expert in math education”. Debatable. As she has posted frequently, she is a mathematician, and makes a clear distinction between math education and mathematics. Be curious about who is positioned as an “expert” and why.

Fads, influential academics with misguided ideas, and poor standards around what constitutes ‘evidence-based’ maths teaching have derailed student outcomes for years, leading expert in maths education @rastokke says. educationhq.com/news/maths-tea…

Oh boy

@edudissenter I mean, under Library Card Theory, there’s nothing to stop a student from getting their explanation somewhere else while remaining within the accountability and motivation structure of the class.

@eduleadership Well, bad explanations are a bit of an impediment, no?

Freddie articulates perfectly what I’ve been struggling to say for a while: learning is not about explanations. It’s about motivation.

@alz_zyd_ Yes you can write up new findings with no citations, but writing up your findings with hallucinated citations outs you as a fabulist. It’s extremely reasonable to assume that if the references are fake, the data are fake too.

Normies think citations make or break a paper because normies have never created new knowledge. To a normie, a science paper is a pure interpolation of existing knowledge (that's what they did in college). Making up citations breaks the interpolation and makes the paper wrong

@lemire OpenClaw was definitive proof that AGI has arrived. People turned over the running of their day-to-day lives to an insecure, unproven tool because it was so obviously extremely capable. Yesterday it was an Erdos problem. Every day it’s something new.

I am getting tired of reading 'experts' like LeCun repeatedly claiming that our AIs are nowhere near human-level intelligence. Let us look at the evidence. US universities rank students based on standardized tests like the SAT. Current AIs achieve near-perfect SAT scores. They also beat tests like the GRE. A few years ago, it was notable when early ChatGPT scored ~120 on an IQ test, a common measure of human intelligence. An IQ of 120 is well above average. Current AIs reportedly have IQ scores similar to those of leading scientists. It is not just in tests. I can ask an AI to produce a science paper that looks undistinguishable from what a PhD level student could do. I just have to give it the data. Better yet, from a prompt, agents can run the experiments and collect the data, and then write the papers. Those of us who try to get work done with AI know what is possible. You can't possibly just say 'this is nowhere near human-level intelligence'. In software, good AIs show a greater mastery of, say, C++, than your average software engineering professor. You could just build a formal test to prove it. The difficulty is that the professors would refuse to take your tests. At this point point, someone will object 'yeah, but your AI can't do this simple thing that we can all do'. Fine. These AIs do not have *human* intelligence. They are very much not human beings. They are something like alien intelligence. They can code straight in assembly language, but have trouble counting characters in words. But that's the result of trade-offs. A dog or a monkey can solve some problems faster than you can. But let us be fair. As a species, these AIs have definitively 'human-level intelligence'. You can't spend decades setting up cognitive tests for human beings, have these AIs beat us in these tests and then say 'well, that's not real intelligence'. Come on !

FWIW you can install Claude Code on your computer, tell it to install itself on a VPS, and tell it to build a Slack bot. From there, it can do anything you want—controlled from your phone.

@eduleadership Right! It's not just that a hallucinated citation is off that slipped in. As a reader, for me that is a potential marker of the overall care and attention that the author gave to all stages of the research process. It casts doubt on every other claim, result, etc. Not good!

I agree that a lot of citations are driven by perverse incentives. But it’s also very common to cite related ideas and their sources, even if those ideas are not central to the argument, just to put everything in context. Nothing wrong with this.

This looks like a pretty cool and worthwhile project. A good use of AI.