Four planning decisions grounded in cognitive science: Cut extraneous load, Match the visual to the meaning, Show through faded worked examples, and Again through formative checks with spacing and interleaving. With walkthrough look-fors for coaches and worked examples across science, ELA, and math.
Beyond Logins: What the Department of Education’s New Edtech Guidance Gets Right and What It Misses
The U.S. Department of Education just released its long-awaited guidance on education technology in schools. The Dear Colleague Letter, authored by Assistant Secretary Kirsten Baesler, tells states and districts to stop evaluating edtech by screen time and engagement metrics and start asking whether tools actually improve learning. This is the right direction, but the guidanceContinue reading "Beyond Logins: What the Department of Education’s New Edtech Guidance Gets Right and What It Misses"
The Science Edtech Forgot
This week, the U.S. Department of Education released guidance that reframes how states and school districts should evaluate educational technology. In a Dear Colleague Letter signed by Assistant Secretary Kirsten Baesler, the Department made the case that edtech should be judged on evidence of learning gains, not on screen time or raw usage. Responsible designContinue reading "The Science Edtech Forgot"
Your AI Lesson Plan Passed the Read-Through. It Still Might Fail These Two Tests.
Teachers are told to review AI output before using it. But what does review actually mean? Most teachers check three things. Is the material accurate? Is it aligned to the standard? Is the tone appropriate? If all three pass, the material goes into the lesson. That is a read-through, not an audit. A read-through catchesContinue reading "Your AI Lesson Plan Passed the Read-Through. It Still Might Fail These Two Tests."
The Measurement Problem: Why Districts Are Tracking the Wrong AI Metrics
The Stanford SCALE review screened 818 papers and found zero high-quality causal studies of AI's impact on K-12 students in U.S. schools. Most districts track engagement metrics, not learning metrics. Here is what to track instead.
The Offloading Trap: Why You Must Audit Every AI-Generated Instructional Output
Claude for Teachers launched this month. Teachers can pull in assessment data, lesson plans, and standards from all 50 states, then ask an AI to build personalized instruction overnight. That’s powerful. It’s also the exact moment to be honest about what happens between the prompt and the classroom. I’ve written about this distinction from theContinue reading "The Offloading Trap: Why You Must Audit Every AI-Generated Instructional Output"
Cognitive Offloading vs. Cognitive Outsourcing: The Distinction That Determines Whether AI Helps or Harms Learning
A calculator offloads arithmetic so a student can focus on problem-solving. That’s cognitive offloading: the tool handles the mechanical work so the learner can focus on the cognitive work. Now imagine a student who types a word problem into an AI tool, copies the answer, and moves on. The tool did the thinking. The studentContinue reading "Cognitive Offloading vs. Cognitive Outsourcing: The Distinction That Determines Whether AI Helps or Harms Learning"
Two Roads: What China and the U.S. Are Actually Doing With AI in Schools
A side-by-side reading of primary-source AI-in-education policy from both countries reveals a structural difference with real consequences for practice: China has a binding K-9 AI curriculum standard, prescriptive classroom guardrails, and explicit rural-equity funding. The U.S. has a state patchwork and federal encouragement. Both bets are uncertain. Both could learn from the other.
The Laptop on the Desk Already Runs a Model
Open-source models can run on school laptops today. Free, private, controllable. The technology is ready. The barrier is institutional, not technical.
Beyond the Hype: An Evidence-First Framework for AI Literacy in Education
An evidence-first framework for how educators should think about AI in the classroom — anchored in cognitive science, grounded in real research, and committed to pedagogy preceding tooling.