AI in the Classroom - Daily

In this episode we explore why schools, districts, governments, and families are beginning to slow down AI adoption in education. From Norway’s restrictions on generative AI for younger students to policy delays in New York City, governance concerns in Portland, safety questions in Broward County, and parent-led calls for a pause across the Washington, D.C. region, a broader pattern is emerging: e...

In this episode we explore “the magenta line of learning” — a powerful metaphor borrowed from aviation to understand what happens when students become too dependent on AI tools before they have built real expertise. Topics covered: The “Children of the Magenta Line” aviation metaphor What Air France Flight 447 can teach us about automation dependency Why students may feel confident without actuall...

In this episode we explore what happens when teachers ask students directly whether AI belongs in the classroom. We look at a classroom conversation led by English teacher Marcus Luther, who asked his students whether he should integrate AI tools into his teaching. Their responses were striking. Topics covered include: Why student voices are often missing from AI-in-education debates What one teac...

In this episode we explore what AI-generated fiction can teach us about human storytelling, student writing, and the value of literary messiness. We look at a new study on StoryScope from researchers at the University of Maryland and Google DeepMind, which compares the narrative structure of human-written short stories with stories generated by several major AI models. Topics covered: What the Sto...

In this episode we explore the surprising relationship between Wikipedia, AI chatbots, and the way students learn to trust information online. We look at how Wikipedia’s commitment to verifiability can actually make it more disciplined than many AI-generated responses. We also explore how teachers can use Wikipedia’s gaps as a powerful classroom demonstration of the difference between a grounded a...

In this episode we explore a surprising finding from Common Sense Media’s new census on AI use by tweens and teens. Topics covered: How tweens and teens are actually using AI Why entertainment use may matter more than cheating What students misunderstand about AI accuracy and truth Why AI literacy is a comprehension issue, not just a rules issue The role of teachers, librarians, and counselors in...

In this episode we explore how young people are using AI when adults are not watching — not just for homework help, but for emotional support, relationship advice, and navigating moments of loneliness, conflict, or uncertainty. We look at new research from The Rithm Project on youth, AI, and relationships, and ask what educators should understand before students return to school in the fall. Topic...

In this episode, we cover three timely AI-in-education stories that all point to the same challenge: schools are moving fast, but the systems around AI policy, teacher training, and academic integrity are still catching up. Topics Covered Why Wake County is moving to ban AI detectors in schools The case of Eleanor Canina and the risks of false AI accusations Why AI detection tools may unfairly fla...

In this episode we explore how students learn to spot AI-generated deepfakes, and why confidence may be one of the biggest risks in AI literacy. We look at a new study from researchers in Germany that used eye-tracking technology to examine where students look when trying to decide whether an image is real or AI-generated. Topics covered: How students visually inspect AI-generated images What eye-...

In this episode we explore how AI is changing one of the most important relationships in school: the trust between teachers and students. We look at emerging research on AI transparency, student surveillance, false accusations, AI detection tools, and the disproportionate risks for English learners and students with disabilities. Topics covered: How AI is changing trust between teachers and studen...

In this episode we explore the rise of AI cheating tools, and what they reveal about the future of writing instruction. We break down a recent New York Times investigation into “humanizers” and “autotypers,” tools designed to make AI-generated student writing harder to detect. But the episode goes beyond academic integrity panic. The real question is what teachers and school leaders can still do w...

In this episode we explore what classrooms can learn from athletics and the performing arts about practice, performance, and real learning in the age of AI. Topics covered: Why exams often reveal gaps between AI-assisted performance and independent learning What music, athletics, and theater can teach academic classrooms Transfer-appropriate processing and why practice conditions matter The differ...

In this episode we explore what happens when students appear to be participating, but may actually be outsourcing their thinking to AI. We look at a recent UC Berkeley story about unusually high failure rates in introductory computer science courses, alongside reporting from The New York Times about students using tools like Gemini and ChatGPT during class discussion.  Topics covered: How AI can c...

In this episode we explore what AI looks like from the inside: not as a shiny classroom tool, but as something real teams have to build, test, constrain, and question before it ever reaches teachers or students. We talk with Jon Landrigan, about what he is seeing from today’s college students as they learn, work, and think alongside AI. Topics covered: How college students are using AI today How A...

In this episode we explore the question: were the AI tools entering classrooms actually designed for learning? We look at a May 2026 preprint from Hassan Khosravi, Ryan Baker, and colleagues that argues many AI tools now being used in schools were originally built for work, not education. Topics covered: How does the tool handle cognitive effort? What does the tool do when students make errors? Wh...

In this episode we explore why student perceptions of AI cheating are far less settled than many school policies assume. We look at new survey data from Oxford University Press showing that students draw very different lines around AI use, from seeing any AI support as off-limits to not viewing full AI completion of homework as cheating.  Topics covered: Why students disagree about what counts as...

In this episode we explore the hidden human work that makes educational technology actually work. We look at a working paper on Khan Academy use in government boarding schools in Uttar Pradesh, India, where schools with dedicated “lab-in-charges” saw much stronger student learning gains than schools that had access to the same technology without that support. Topics covered: What the Khan Academy...

In this episode we explore whether AI should be used as a starting point for student writing, especially in ELA classrooms. Topics covered: The NCTE AI ELA Framework for grades 6–12 Why the “blank page” is such a real challenge in writing instruction The difference between AI as a starting point and AI as a thinking partner What research suggests about AI, brainstorming, and idea diversity How AI...

In this episode we explore why sequencing matters when AI enters reading instruction. Drawing on Student Achievement Partners’ argument to “keep text at the center,” we look at a practical question for teachers and district leaders: does AI arrive before students have wrestled with a complex text, or after they have made their own first attempt? Topics covered: Why “keeping text at the center” dep...

In this episode we explore what happens when students learn with AI or other cognitive supports, and then suddenly have to work without them. We look at a recent learning science study highlighted by Carl Hendrick in The Learning Dispatch , where students who had been using a simple planning tool saw their performance drop when that tool was removed.  Topics covered: Why introducing an AI tool als...

In this episode we explore a simple question for classrooms using AI: Should students think first and use ChatGPT later? We connect research to a seventh-grade poetry classroom where students drafted on paper before using AI-supported tools. Topics covered: Why “better work with AI” is not the same as learning The difference between performance and transferable skill What happens when students go...

In this episode we explore how AI tools can either preserve or undermine one of the most important parts of learning: productive struggle. We look at Student Achievement Partners’ recent piece on AI in literacy and math classrooms, with a focus on the caution that students may lose essential learning opportunities when AI does the thinking too early. Topics covered: What Student Achievement Partne...

In this episode we explore a practical classroom response to one of the hardest problems AI has created for teachers: how to know whether a student actually understands the work they submitted. Rather than relying on unreliable AI detectors, we look at an emerging approach from educators like AJ Giuliani: using a student’s submitted paper to generate a short comprehension quiz that helps reveal wh...

In this episode we explore California State University’s large-scale AI licensing deal with OpenAI, and what it reveals about the tension between institutional policy, classroom practice, and pedagogical purpose. CSU set out to become the nation’s first “AI-powered university system,” offering ChatGPT enterprise access across its campuses. But a year later, many licenses went unused, faculty pushe...

In this episode we explore what effective feedback looks like in AI-assisted classrooms, and why the design of that feedback matters more than the novelty of the tool. Topics covered: Why many teachers are still receiving little guidance on classroom AI use What new research suggests about metacognitive feedback and student learning The difference between feedback that supports transfer and feedba...