Last week I was sharing with a colleague about a Year 7 lesson that, on the surface, looked like chaos.
Students were working on design challenges. Each had chosen a problem they cared about and were exploring possible solutions. The brief was simple: understand the problem, empathise with the people involved, and begin prototyping ideas. Around the room they were experimenting with different tools, including Google Gemini and a handful of other AI systems.
There was very little direct instruction. Just enough to get them moving.
As often happens in these kinds of classes, one student stumbled onto something interesting. They had discovered a way Gemini could help prototype a simple digital product. Naturally, they called a few classmates over. Soon the whole class was discussing how they had done it and whether the same idea could help someone else's project.
Within minutes, a group had built a working prototype.
The Idea
Their idea was simple but thoughtful. Imagine a refugee family arriving in Australia and trying to make sense of everyday language. Not formal English, but the slang and cultural shorthand we use without thinking. "Arvo." "Servo." "Flat out like a lizard drinking."
Using Gemini, they quickly generated a small website. A user could enter common Australian slang and hear it spoken aloud. The site explained the meaning and automatically translated the explanation into fifteen different languages.
Eighty minutes earlier it had not existed.
What Mattered
What struck me was not the technology. It was the learning. Students moving from empathy to design, from curiosity to building, and sharing discoveries with one another along the way.
Ken Kahn describes AI as the learner's apprentice — a tool that amplifies human creativity and supports the act of making.
That is exactly what it looked like in that room. Students thinking about people, problems, language, and culture, and then building something to help.
Messy. Loud. Collaborative.
And deeply human learning unfolding in real time.