08/08/2026
We keep saying that students need AI literacy. But who will teach it, and how prepared are teachers to explain what happens behind the screen?
Teaching students how to use an AI tool is one thing. Helping them understand how a machine learns, why it makes mistakes, what overfitting means, or how a neural network improves through feedback is something quite different. These ideas can feel abstract even to adults, let alone primary and junior secondary students.
This study by Yin Yang and Siu Cheung Kong offers an interesting example of how teacher professional development can make these concepts more approachable.
Thirty-six teachers in Hong Kong participated in six hours of hands-on training using learning robots. Instead of only hearing about machine learning, they watched the robots respond to data, make errors, adjust, and try again.
The workshops followed the AEER framework: Attention, Engagement, Error-feedback, and Reflection. I particularly like the place given to error here. When a robot hit a wall or became stuck, the mistake was not treated as a failure to hide. It became something teachers could examine, discuss, and use to explain how machine learning works.
Following the workshops, teachers demonstrated stronger understanding of machine learning concepts and greater confidence in teaching them. They also valued having a pedagogical framework that helped them move from knowing the technology to making it understandable for younger learners.
There is an important lesson here for teacher professional development. A presentation about AI will not necessarily prepare teachers to teach it. Teachers need opportunities to touch, test, question, discuss, make mistakes, and translate difficult technical ideas into meaningful classroom experiences.
If we want students to understand AI rather than simply consume it, we must first give teachers the time, resources, and practical experiences needed to open up its “black box.”
Reference:
Yang, Y., & Kong, S. C. (2025). Professional development for teachers in AI literacy education: Teaching machine learning to senior primary and junior secondary students. In *Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025)* (Vol. 2, pp. 35–42). SCITEPRESS.