AI in the Classroom

In this episode we explore what happens when AI becomes more than a classroom tool, and starts competing with classroom learning itself.

Topics covered:

• How AI may change students’ expectations about what learning should feel like
• Why immediate AI responses could make classroom dialogue feel slower by comparison
• The connection between AI use, boredom, and delayed gratification
• How students are already using AI for entertainment, advice, creativity, and personal questions
• Why students may reach for AI before attempting difficult work themselves
• Cognitive offloading and the question: “Why should I do this if AI can?”
• Why impatience with confusion may be an important classroom signal
  

This is Part 2 of a two-part series on student attention.
Source:

https://www.aft.org/ae/spring2026/willingham

In this episode we explore a question many educators are asking: Have students actually lost the ability to pay attention, or has something else changed?

Topics covered:

• Why teachers report declining student reading stamina
• What research actually says about screens and attention capacity
• The difference between attention ability and willingness to pay attention
• How “delay discounting” can influence persistence and schoolwork
• Why phones may make ordinary classroom tasks feel more boring
• How the availability of distractions changes students’ experience of learning
• Why briefly checking a phone may actually increase boredom afterward
• What cell phone restrictions can—and cannot—solve
  

This is Part 1 of a two-part series on student attention.

Source:

https://www.aft.org/ae/spring2026/willingham

In this episode we explore four stories that reveal how quickly AI is accelerating across education, and why schools should remain skeptical of claims that move faster than the evidence.

We examine ByteDance’s plan to add AI-generated video lessons to the study app Gauth, the rise of low-quality AI-created resources on Teachers Pay Teachers, Alpha School’s rapid expansion of its AI-centered private school model, and a student-written framework for K–12 AI policy.

Topics covered:

• Whether high-production AI videos improve learning, or simply increase engagement• How “AI slop” is entering teacher marketplaces and exploiting educators’ limited time• Why platforms must take greater responsibility for vetting AI-generated instructional materials• Alpha School’s two-hour AI learning model and its decision to replace licensed teachers with “guides”• The unproven claim that AI tutoring can reproduce the effects of intensive human tutoring• Student proposals for AI opt-outs, fact-checking requirements, bias disclosures, and approved school AI tools

Sources:

https://www.aasa.org/docs/default-source/resources/reports/17_s-2026-the-students-first-act-final-bill-passed-84-14-july-19-2026.pdf?sfvrsn=ef93d4d2_1

https://www.axios.com/2026/08/02/alpha-schools-ai-expansion-50-campuses

https://www.businessinsider.com/seedance-bytedance-education-push-study-app-gauth-ai-animations-2026-7

https://www.aasa.org/resources/resource/students-first-act 

In this episode we explore why teacher AI literacy—not the latest tool—is the most important investment schools can make.

Topics covered:

• Why the same AI tool can produce very different classroom outcomes• The six dimensions of teacher AI literacy• Technical fluency and understanding how generative AI works• Evaluating AI outputs for accuracy, bias, and missing perspectives• Keeping teachers in control of human–AI collaboration• Deciding when AI supports learning—and when it replaces necessary thinking• Ethical reasoning, academic integrity, and student ownership• The importance of teacher agency in school AI policy• Why tool-specific training is not enough

Source:

https://arxiv.org/pdf/2608.01705

In this episode we explore how AI chatbots may shape students’ understanding of what a real conversation—and real thinking—sounds like.

We examine the idea of “critical distance”: a student’s ability to recognize what is missing from an AI-generated response. We also consider why some schools and districts are limiting younger students’ access to conversational AI.

Topics covered:

• How the chatbot interface creates a false model of conversation
• Why speed and confidence are not the same as thoughtful reasoning
• What authentic pedagogical dialogue sounds like
• How students develop critical distance from AI-generated answers
• Why age-based AI policies and access gates may matter

Sources:

https://www.nytimes.com/2026/02/23/business/ai-literacy-faq.html

https://www.aft.org/news/afts-weingarten-unveils-10-point-plan-boost-student-learning-ai-era

https://www.wired.com/story/some-kids-will-never-think-ai-is-cool/

https://www.oecd.org/en/about/projects/pisa-2029-media-and-artificial-intelligence-literacy.html

In this episode we explore why AI tutors and chatbots often praise students instead of giving them the honest, challenging feedback that learning requires.

We examine “psychofancy,” the tendency of AI systems to flatter, validate, or agree with users when correction would be more useful. 

Topics covered:

• Why excessive AI praise can interfere with productive struggle
• How AI feedback differs from feedback provided by teachers and peers
• Why students need to question whether feedback is truthful, useful, or simply flattering
• How speed, confidence, and isolation can make AI responses feel authoritative
• Why teachers should introduce AI feedback in a group setting before students use it independently
• How comparing AI, peer, and teacher feedback can strengthen student judgment
  

Source:

https://www.the74million.org/article/ai-tutors-are-praising-instead-of-teaching-heres-why-thats-hurting-students/

In this episode we explore what it means to be literate in a world where algorithms increasingly decide what information students see, and what they never encounter.

We examine the OECD’s new Media and Artificial Intelligence Literacy framework, known as MAIL, and its argument that AI literacy must extend beyond evaluating whether a piece of content is accurate.

Topics covered:

• The shift from using AI tools to living inside AI-mediated environments
• The OECD’s Media and Artificial Intelligence Literacy framework
• PISA’s three foundational ideas: authors and audiences, messages and meanings, and representations and realities
• How platforms are designed to capture and monetize attention
• The effects of algorithmic personalization, echo chambers, and filter bubbles
• Why students cannot always see which perspectives have been filtered out
• The values and biases embedded in AI training data and system design
• Why AI literacy should include asking, “Why did I see this?”
• What the planned 2029 PISA assessment could mean for teachers, schools, and education systems
  

Source:

https://www.oecd.org/content/dam/oecd/en/about/projects/edu/the-pisa-2029-media-and-artificial-intelligence-(mail)-assessment-will-shed-light-on-whether-young-students-have-had-opportunities-to-learn-and-to-engage-proactively-and-critically-in-a-world-where-production,-participation,-and-social-networking-are-increasingly-mediated-by-digital-and-ai-tools-/PISA%202029%20MAIL%20Assessment%20Framework%20First%20Draft.pdf

In this episode we explore a growing problem for school districts: how do you govern AI use when you cannot clearly see where or how it is already being used?

Looking at recent policy moves in New York City, Fairfax County Public Schools, and Katy ISD, we examine the gap between official AI rules and the reality inside schools. 

Topics covered:

• Why districts often lack a complete inventory of AI tools
• New AI restrictions in New York City, Fairfax County, and Katy ISD
• Why defining “AI” is harder than it sounds
• The limits of bans, firewalls, and approved-tool lists
• The trade-off between surveillance and teacher autonomy
• The risks of policies that districts cannot consistently enforce
• Why AI governance is now more urgent than AI adoption
• What the forthcoming student-led AI Bill of Rights for Schools could add to the debate

Sources:

https://www.houstonchronicle.com/neighborhood/katy/article/katy-isd-ai-policy-generative-ai-students-22357245.php

https://www.the74million.org/article/students-convene-to-hammer-out-ai-bill-of-rights-for-schools/

https://www.ffxnow.com/2026/07/23/fairfax-county-school-board-approves-restrictions-on-generative-ai-digital-devices/

In this episode we explore why AI tutors may be improving student performance without producing the deeper, transferable learning schools actually want.

Topics covered:

• Why strong tutoring results may not translate beyond the tutoring environment• The difference between task completion and genuine transfer• What brain-training research can teach us about AI tutors• Why current assessment systems shape what AI tools optimize for• What teachers and district leaders want from next-generation assessment• How multimodal AI could capture student reasoning and problem-solving• Why changing assessment may be the key to improving AI tutoring

Sources:

https://thedigitaldelusion.substack.com/p/are-ai-tutors-really-teaching-students

https://www.gettingsmart.com/2026/07/17/weve-been-judging-symphony-rehearsals-by-the-last-note-why-multimodal-ai-can-finally-measure-mathematical-practice/

https://marketbrief.edweek.org/meeting-district-needs/whats-next-for-k-12-assessment-the-demand-for-innovation-in-k-12-testing/2026/06

In this episode we explore whether schools are actually falling behind on AI—or whether educators are adopting the technology faster than headlines suggest.

Topics covered:

• How teacher AI adoption compares with other professions
• Why experimentation does not always lead to regular, confident use
• The training and access barriers facing educators
• What students misunderstand about AI and truthfulness
• Why AI literacy matters for student health and safety decisions
• The difference between moving fast and building sustainable infrastructure

Sources:

https://www.gallup.com/699797/indicator-artificial-intelligence.aspx

https://www.sciencedirect.com/science/article/pii/S2666920X25001043

https://www.k12dive.com/news/ai-is-moving-quickly-how-can-districts-keep-up/816265/