Jim Bentley on AI, Curiosity, and the Classroom as a Laboratory

Jim Bentley on AI, Curiosity, and the Classroom as a Laboratory

In this episode we speak with Jim Bentley, a fifth- and sixth-grade teacher in Elk Grove, California, who is entering his 31st year in the classroom. We examine how Jim has begun using AI with students.  Topics covered: * The classroom as a laboratory for curiosity, experimentation, and productive mistakes * How project-based learning shaped Jim’s teaching philosophy * An AI image-generation project connected to Raymie Nightingale by Kate DiCamillo * Prompt writing, revision, and healthy skepticism toward AI-generated results * Media literacy, lateral reading, and fact-checking AI responses * The difference between using AI as a productivity tool and using it as a learning tool * What it means for students to do “real work,” not merely “schoolwork” * Rubric design, teacher judgment, and the risk of overvaluing polished final products

Early-Career Teachers and AI Habits

In this episode, part 3 of our series on the productive struggle for teachers, we explore how AI is shaping the habits of early-career teachers, and why the choices teachers make in their first five years could influence the rest of their careers. Topics covered: • Why early-career teachers may be especially vulnerable to passive AI use• How generic AI-generated materials can affect student engagement• The connection between teacher confidence, burnout, and retention• Why productive struggle matters when learning to teach• The importance of revising and personalizing AI-generated lessons• Why protected reflection time should be part of AI implementation• How early-career teacher support affects equity and the long-term teacher pipeline

Plan the Way You Want Them to Learn

In this episode we explore how teachers can use AI during lesson planning without outsourcing the thinking that helps them grow as educators. We look at why teachers should do the difficult thinking first, how AI can be used to pressure-test a lesson, and why revision and reflection are essential when evaluating AI suggestions.  Topics covered: • Why lesson planning is a learning process for teachers• The difference between using AI as a thinking partner and outsourcing the work• Productive struggle and its role in developing teacher expertise• How pedagogical content knowledge is built through planning• Why AI-generated lesson plans require substantial revision• Metacognitive reflection as an alternative to cognitive surrender Sources: https://www.nature.com/articles/s41539-025-00311-8#citeas https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646

The Claude Before the Storm

In this episode we explore two major developments shaping AI in K-12 education: Anthropic’s launch of Claude for Teachers and the fragmented policy environment surrounding AI adoption in schools. Claude for Teachers promises to reduce teacher workload, but the product’s integrations raise important questions about student data, classroom recordings, vendor agreements, and FERPA compliance. Topics covered: • What Claude for Teachers offers K–12 educators• How AI could support lesson planning and instructional coaching• The privacy risks of sharing classroom audio and student data• Why vendor integrations require district-level review• The difference between “FERPA-aligned” and FERPA-compliant use• New state laws governing student data and automated decisions Sources: https://www.chalkbeat.org/2026/07/14/anthropic-launches-claude-for-teachers-as-ai-companies-battle-for-classrooms/ https://www.youtube.com/watch?v=V-OOEC5RNaQ

The Cost of AI Shortcuts

In this episode we explore what happens when teachers use AI to save time, and whether those shortcuts can come at a cost for students. Drawing on a statewide survey of more than 13,000 Georgia teachers, we examine a troubling tension: Teachers often believe AI improves their work, while emerging evidence suggests that certain patterns of AI use may reduce student motivation, confidence, and, in some classrooms, academic performance. Topics covered: • Why teacher AI adoption is accelerating• The gap between perceived productivity and student outcomes• Findings from Georgia’s statewide teacher survey• What a randomized controlled trial found about student motivation and confidence• Cognitive offloading and the “skill substitution” problem• How generic AI-generated materials can weaken a teacher’s personal voice• The difference between using AI as a shortcut and using it as a thinking partner Sources: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7007339 https://www.the74million.org/article/more-than-half-of-georgia-teachers-now-use-artificial-intelligence-to-prepare-for-class/ https://www.anthropic.com/news/claude-for-teachers