Remote Sensing and AI in Archaeology Education: A Learning Experience on Early Neolithic Ditched Villages in Southern Italy

This paper presents an educational experience developed for archaeology and cultural heritage students of the University of Salerno. The course translated a specialized archaeological research topic, the ditched villages of the Early Neolithic in south-eastern Italy, into a learning environment combining archaeological interpretation, remote sensing, data organization, and an introductory engagement with AI-related methods. The educational design moved progressively from theoretical framing to image interpretation and dataset construction. In this context, machine learning was introduced not as a technical skill to be directly implemented by students, but as a methodological framework guiding the preparation of data for a real clustering task. Students organized the dataset, selected relevant features, and used NotebookLM both to reflect on data preparation and to become familiar with accessible AI tools, while the clustering phase was carried out by an expert. The experience shows that digital innovation in archaeology education is most effective when computational methods are embedded in critically grounded and disciplinarily coherent learning processes.