Category: Pedagogy
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IYKYK Part 4: From Knowing to Doing
So far in this series I’ve argued that GenAI has a discoverability problem, shared some examples that broke my own mental model, and explored how access and equity shape who gets to discover what. In this post I’ll talk about what happens after discovery, because knowing that a capability exists and being able to use…
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Case Study: Saskatoon Public Schools and AI Assessment
The AI Assessment Scale (AIAS) has been successfully adapted by Saskatoon Public Schools to enhance conversations around AI in education. By reimagining its structure, the team shifted focus from binary use to a framework that supports different learning purposes, fostering transparency and student ownership of their learning process. Their approach sets a precedent for future…
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Resistance Training Toolkit: Expertise
This is the first post in a series article articles introducing the Resistance Training Toolkit: evidence informed strategies for working with (and against) AI.
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Gradually Reclaiming Responsibility
The article explores the concept of resistance in educational contexts, especially with the rise of GenAI technology. It examines how students must actively maintain ownership of their learning and critical thinking, especially as AI takes on more responsibility in the learning process. The traditional gradual release of responsibility model is adapted to consider AI’s impact,…
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Resistance as a Framework for Combating Cognitive Offload
This post discusses the necessity of resistance in using AI for education, comparing it to physical training. While generative AI can lead to cognitive laziness, integrating resistance can help maintain learning integrity. Here’s a framework exploring expertise, evaluation, metacognition, cognitive stretch, and feedback to ensure beneficial AI usage.
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What Happens to Expertise When Students Skip the Struggle?
When students use GenAI to skip the hard parts of learning, they miss the productive struggle that builds genuine expertise. This post explores why the “AI is just like a calculator” argument falls short, and why novices are most at risk of outsourcing the thinking that matters most.
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Everything Educators Need to Know About GenAI in 2026
GenAI in education is a sprawling topic, so each January I try to distill it into a single post: what’s changed, what’s most important, and what you can actually do with the technology. This is 2026’s introduction to GenAI: I’ll dig deeper into each section throughout the year.
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Processes are More Important than Prompts
This post outlines five practical steps for using GenAI platforms. Applying expertise, selecting the right model, adding context, using the internet, and iterating and refining are useful skills for working with these technologies.
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What Do Educators Want to Learn About GenAI?
I recently asked a group of around 3000 educators from my mailing list what they’d like to learn about GenAI. I’m incredibly lucky to have feet in a couple of camps as both an early career researcher and a consultant/author. It means I have access to the training and skills for working with lots of…
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Professional Development for AI in Schools: A Three-Dimensional Approach
PD for GenAI isn’t a “one and done” event – it needs to fit with teachers’ existing disciplinary expertise and their deep, contextual understanding of what it means to teach.