What China’s Calligraphy Lessons Can Teach Us About AI — from linkedin.com by Rebecca Winthrop
He recalled visiting a primary school classroom in China several years ago where students were practicing calligraphy—the centuries-old art of writing Chinese characters with brush and ink. While the scene appeared entirely traditional, there was something innovative happening beneath the surface. Embedded in students’ desks was an AI system capable of providing immediate feedback on their brushwork, noting misplaced strokes and suggesting corrections.
The image is striking. Students were learning in much the same way generations before them had learned—brush in hand, immersed in a deeply human and cultural practice. Yet AI was quietly enhancing the experience by providing immediate, personalized feedback that would have been difficult for any teacher to provide to her whole class.
That example captures something important for me. The most promising uses of AI may not be the applications that place technology front and center, but those that support learners to do what they have always done: connect with educators, practice with concentration, and learn and grow.
AI Can Build Your Course, but Can it Design the Learning? — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, the current state of AI’s instructional design ability & what it means for L&D
So these models have learned design artefacts in extraordinary volume and design method barely at all. They know what e-learning looks like. They have very little access to why any of it looks that way and whether it actually works or not.
That produces a completely consistent behaviour: ask an LLM for an e-learning module and it generates the statistical centre of every e-learning module it has ever seen. What AI produces isn’t the output of a design process. It’s the output of a sampling process — the statistical centre of every e-learning module it has ever seen.
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So the honest conclusion isn’t that AI can design learning; it’s that AI executes design well when someone who already knows what to ask for is doing the asking and the checking.
This finding gives us a clearer division of labour than we’ve had before and with it a clearer picture of what the AI-enhanced workflow might look like:
The Pedagogy of Trading Places: Lessons from an Unexpected Role Reversal with AI — from facultyfocus.com by Sherrie Myers Bartell, PhD
These disruptions matter. They remind us that teaching is not a static identity but a dynamic posture. They show us that our pedagogical selves are not fixed; they are responsive to context, energy, and attention. They reveal that the qualities we value most in our teaching—curiosity, metaphor, play, and expansiveness—are not automatic. They require care and cultivation.
The AI didn’t “teach” me in the traditional sense. But it did something pedagogically adjacent: it surprised me back into myself.
