M{AI}L brings Artificial Intelligence into everyday learning in Italian classrooms

How Italian students moved from learning about AI to creating and testing their own Machine Learning models

Artificial Intelligence and Machine Learning became part of everyday classroom learning in Italy through the M{AI}L project. At ITET G. Caruso, students explored how AI systems are trained and tested, using practical activities designed to connect emerging technologies with subjects they were already studying.

The Italian implementation involved 200 students, 13 teachers and 48 classroom sessions. Students were around 14 years old and participated in activities connected to a wide range of subjects, including Mathematics, Physics, Chemistry, Computer Science, English, Italian Language and Literature, History, Catholic Religion and Special Educational Needs support.

Learning AI by doing

The activities focused on practical, hands-on learning using Teachable Machine and the M{AI}L project handbook. Rather than simply learning about Artificial Intelligence as a theoretical concept, students explored how Machine Learning models are actually trained.

After an introduction to the basic principles of Machine Learning and supervised training, students worked in small groups to create and test their own AI models. They collected multimedia data, trained models and experimented with their performance. As they became more familiar with the platform, many students continued experimenting independently at home, developing additional projects and testing new ideas.

Connecting AI with different school subjects

One of the key aspects of the Italian implementation was its interdisciplinary approach. Students developed image, sound and pose recognition models connected to topics from their regular curriculum.

This allowed them to explore AI while simultaneously applying knowledge from different subjects. The approach supported the development of digital competence, computational thinking and creativity, while helping students gain a more informed understanding of how AI-based systems work.

From experimenting to creating

Teachers reported consistently high levels of student engagement. The visual and intuitive nature of Teachable Machine allowed students to become increasingly autonomous after an initial introduction, while the practical activities encouraged curiosity, collaboration and creativity.

Students began proposing their own project ideas and real-life applications of AI, with collaborative work sometimes developing into friendly challenges between groups as they compared the performance of their models and experimented with different datasets.

The experience showed how practical, project-based activities can bring Artificial Intelligence closer to students’ everyday learning and create opportunities for them to move from AI users to active explorers of how AI works.

The Italian classroom experience is part of the wider M{AI}L implementation carried out across Greece, Italy, Portugal and Türkiye, where teachers and students explored practical approaches to bringing AI and Machine Learning into education.