AI in the Classroom - Daily

In this episode we explore the debate around a Georgia school marketed as the nation’s first AI-themed high school, and what its story reveals about the gap between AI branding and actual classroom practice. Topics covered: The Seckinger High School debate and the risks of branding a school around AI Larry Cuban’s “oversold and underused” pattern in education technology Why AI may create a harder...

In this episode we explore a live “AI usage teardown” of a reflective tool created by educator Amelia King, designed to help students think more clearly about how they are using AI in academic work. Topics covered: How students can reflect on whether their work is genuinely their own The difference between AI assistance and cognitive surrender Why “how much AI did you use?” is often harder to answ...

In this episode, we explore a fascinating (and counterintuitive) finding from a large-scale study of AI writing tools in Brazilian high schools: adding human graders to AI feedback didn’t improve student outcomes—but that’s not the real story. We challenge the common narrative about AI “doing the teaching” and instead ask a more important question: what happens when AI handles the routine work so...

In this episode we explore the idea of cognitive surrender in AI education: what happens when students, teachers, or professionals begin relying on AI not just for support, but for the thinking itself. How do we use AI as a thinking partner without gradually losing our own voice, judgment, and generative ability? Topics covered: What “cognitive surrender” means in the context of AI and education W...

In this episode we explore a sharper way to think about AI in literacy instruction: not as a shortcut that makes texts easier for students, but as a teacher’s assistant that helps educators identify where complex texts may challenge readers. Topics covered: Tim Shanahan’s argument for using AI as a teacher-facing tool How AI can identify complex sentences and vocabulary in classroom texts The diff...

In this episode we explore what eighth-grade students in California are asking about AI. We reflect on a recent classroom visit and use students’ own questions to examine what young people already understand about AI, what they are unsure about, and why their concerns about fairness, cheating, fake work, and feedback matter for educators and district leaders. Topics covered: How students are exper...

In this episode we explore the debate around Khanmigo, Khan Academy’s AI tutor, and what its struggles reveal about the difference between explaining content and actually supporting learning. Topics covered: Why Khanmigo was described as “a non-event for most students” The difference between a great explainer and a true tutor How Sal Khan learns Why students often need more than prompts and explan...

In this episode we examine a published analysis comparing civilian casualties at Gettysburg with civilian casualties in Gaza in 2024, and explain why the comparison is historically incoherent.  Topics covered: Why AI-generated comparisons can sound plausible while being misleading The difference between factual accuracy and content-area coherence What the Gettysburg/Gaza analogy gets wrong Why tea...

In this episode we explore why AI is increasingly showing up in education as a tool for coaching and feedback. We look at Renaissance Philanthropy’s discussion of the Gates Foundation’s AI initiative, which is exploring whether AI can help support teacher coaching in primary education in sub-Saharan Africa. Topics covered: Why teacher coaching and feedback are emerging as a major role for AI in ed...

In this episode we explore a federal lawsuit involving Palo Alto Unified School District, a student essay flagged by Turnitin’s AI detector, and the much larger question underneath the case: what should schools actually do when an AI-detection tool raises a red flag? Topics covered: The Palo Alto lawsuit over a student essay flagged as AI-generated The workload problem for teachers managing repeat...

In this episode we explore four practical questions educators and district leaders can ask before adopting AI tools in classrooms. Drawing on Daniel Willingham’s framework for evaluating educational technology, we look at how schools can move beyond “we can’t be left behind” thinking and make more deliberate decisions about when AI helps learning—and when it may quietly replace something important...

In this episode we explore what it might take to design writing assignments that students are less likely to outsource to AI. We look at a college philosophy assignment called “My Apologies” and use it as a lens for thinking about AI-resistant assignment design—not because every teacher should copy it, but because it reveals some useful principles for K–12 classrooms. Topics covered: Why many trad...

In this episode we explore what happens when AI helps students produce “better” writing, but makes that writing feel less like their own. Drawing on a recent essay by Nurul Hassan Mohammad about AI use in STEM classrooms, we look at a subtle but important risk: when students use AI to polish lab reports, methods sections, and research writing, the work may become clearer and more polished while al...

In this episode we explore a new kind of objection emerging in classrooms: students and teachers questioning whether AI tools belong in school because of their environmental costs. We look at real examples from classrooms, professional learning sessions, and student writing to unpack why this concern is gaining traction. We examine what educators should say when students raise ethical objections t...

In this episode we explore how AI could reshape state assessment, and why that shift matters for teachers, coaches, and district leaders. W We look at two recent pieces: Jane Swift’s argument that AI-enabled assessment can turn testing from an “autopsy” into a “compass,” and Transcend’s policy paper calling for a more careful bridge to the future of state assessment. Topics covered: Why state asse...

In this episode we explore a question schools are only beginning to confront: how should students speak to AI? As AI chatbots become more common in classrooms, the conversation often focuses on cheating, plagiarism, citation, and academic integrity. But there is another layer worth paying attention to: the interaction itself. When students talk to AI, are they respectful, dismissive, abusive, curi...

In this episode we explore the rise of AI-powered coaching tools for teachers and what happens when feedback on classroom instruction starts coming from software instead of a human observer. We look at the promise and risk of AI tools that analyze classroom video, generate feedback, and shape how teachers talk about their own practice. Topics covered: How AI coaching tools are being used to analyz...

In this episode we explore what happens when AI changes the basic conditions of student writing, and why some teachers are bringing pencils, notebooks, and in-class writing back into the center of English instruction. Drawing on a recent New York Times piece about AI and student writing, we look at the growing move away from take-home essays and toward handwritten, in-class work. The real question...

In this episode we explore a new Stanford study showing that AI writing feedback tools can respond differently to the same student work depending on demographic cues like race, gender, motivation level, English learner status, or learning disability status. We break down why this matters for classrooms and districts, especially as schools adopt AI feedback tools that promise personalization. The c...

In this episode we explore the promise, and the limits, of “closed loops” in AI-enhanced classrooms. We talk about whether AI can really give teachers and school systems a complete picture of a student’s learning journey: where they are, what they need next, and how best to support them. Topics covered: What “closed loop” means in AI-supported teaching and learning The appeal of real-time insight...

In this episode we explore what Khanmigo’s uneven rollout reveals about AI tutoring, student motivation, and the limits of chatbot-based learning tools. When students do not use an AI tutor, is that a student motivation problem, a product design problem, or a teaching design problem? Topics covered: What Khanmigo’s rollout tells us about AI tutoring in real classrooms Why low student usage matters...

In this episode we explore what happens when school districts begin using “vibe coding” to build their own software tools with generative AI. We look at Peninsula School District in Washington State, where administrators are using AI coding tools to create internal apps and potentially save hundreds of thousands of dollars in EdTech contracts. We examine why this is promising, why it is risky, and...

In this first Teacher Tuesday episode of AI in the Classroom – Daily , we explore what AI looks like from inside a real elementary classroom. Dan Cogan-Drew talks with educator Diana Betancourt of Neabsco Elementary School in Prince William County, Virginia, about how AI-supported writing tools are helping her students—especially multilingual learners and students with disabilities—build confidenc...

In this episode we explore whether AI translation tools are making language learning obsolete, and why the answer is more complicated than it first appears. Using a recent essay from The Conversation as a starting point, we look at the difference between using AI for quick transactional communication and using language to build identity, relationships, and cultural understanding. Topics covered: A...

In this episode we explore the increasingly heated debate over technology in schools — from state-level efforts to restrict devices to the growing pressure on districts to adopt AI tools. Using recent arguments about EdTech, screen bans, handwriting, typing, and classroom technology, we look at why the real question is not simply “screens or no screens,” but what specific learning task students ar...