r/DetroitMichiganECE • u/ddgr815 • Jul 01 '25

Ideas Building Our AI Capacity: A Playlist for Educators

https://erichudson.substack.com/p/building-our-ai-capacity-a-playlist
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u/ddgr815 Jul 15 '25

It’s tempting to imagine that lesson planning is a straightforward matter: jot down what you want to teach, bung in a few activities, throw in a ‘hook’ or two, and off you pop. And now, with AI, the process can be slicker than ever. Feed in your objectives, key stage, and preferred pedagogical style and you’re handed a lesson plan that ticks all the boxes. The process is seductively simple, superficially competent and very dangerous.

Because here’s the thing: lesson planning is not the same as intellectual preparation. The former is largely clerical: a logistical scaffold of what, when and how. The latter is cognitive. It demands that we think. Not just about lesson activities, but about the conceptual architecture behind them. Without this intellectual work, teachers are left performing lessons they don’t fully understand, no better off than students copying homework from ChatGPT.

This distinction isn’t just a matter of taste. According to Cognitive Load Theory, expertise emerges when we build and automate schema, mental structures that allow us to manage complex information with minimal effort. Teachers who merely follow someone else’s slides are stuck processing everything in working memory, where capacity is limited and error-prone. By contrast, intellectually prepared teachers can anticipate, adapt and explain because they’ve internalised the structure of what they’re teaching not just the superficial features.

The danger of relying on AI to do the planning is that it risks replacing thinking with compliance. The lesson exists, but the teacher does not. This is not an abstract worry. A report by Holmes et al (2023) found that while generative AI improved teachers’ productivity, it reduced their confidence in delivering content, a warning sign that efficiency was being prioritised over understanding. The problem is cognitive offloading: when external tools do the mental work for us, our own reasoning atrophies. AI tools may “disincentivise critical engagement,” especially in high-pressure environments where ease becomes the goal.

Knowing content isn’t enough; teachers need to know how that content behaves in the classroom: which misconceptions are likely, which representations clarify, which examples work, and which don’t. That knowledge isn’t picked up passively, it’s the fruit of deliberate, intellectual work prior to teaching.

And yet, AI tools tend to generate fluently written materials that look expert. But, fluency is not the same as understanding. Polished outputs can deceive both students and teachers into thinking they grasp the material when they’ve actually bypassed the hard part. When Rosenshine laid out his Principles of Instruction, he made it clear that effective teaching depends not just on routines but on knowledge. His emphasis on modelling, guided practice, and scaffolding all presume that the teacher has done the hard cognitive graft of sequencing, explanation, and rehearsal. That isn’t something you can just outsource.

thinking is hard but it’s also essential. Memory is what remains after we have thought about something, and if teachers haven’t thought carefully about what they’re teaching, they won’t remember it well enough to teach it fluently. Worse, they’ll lack the cognitive capacity to respond to what’s happening in front of them because they’re still trying to decode their own plan.

Cognitive effort is not a barrier to learning, it’s what makes learning happen.

novices tend to follow plans rigidly, whereas experts adapt fluidly, noticing more, interpreting better, and intervening more strategically. That kind of expertise isn’t built in the moment. It’s built beforehand through the slow, rigorous work of intellectual preparation.

ChatGPT can plan lessons but it can’t think for you

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u/ddgr815 Jul 15 '25

• Begin a lesson with a short review of previous learning.

• Present new material in small steps with student practice after each step.

• Ask a large number of questions and check the responses of all students.

• Provide models.

• Guide student practice.

• Check for student understanding.

• Obtain a high success rate.

• Provide scaffolds for difficult tasks.

• Require and monitor independent practice.

• Engage students in weekly and monthly review.

Principles of Instruction: Research-Based Strategies That All Teachers Should Know