Artificial Intelligence at the service of Professional Training: examples of excellence
Author | Giulia Norcia, Fondazione CNOS-FAP ETS
Artificial Intelligence (AI), a long-standing field of study, is experiencing a phase of extraordinary vitality. Increasing funding and continuous technological innovations are accelerating its spread through the creation of multiple tools. The Salesians of Vocational Training have understood the importance of the possible applications of these tools in the field of education, thinking first and foremost of the professional development of their trainers. A significant step in this direction was the signing of an agreement between the CNOS-FAP ETS Foundation and the Italian Association for Artificial Intelligence (AIxIA) last January, to guarantee a qualified group of experts to support training and project initiatives.
A collaboration with Google Education was also launched, which enabled the training of 700 people from the CNOS-FAP ETS Foundation and teachers from schools in the Salesian North-East Province, on the use of Google GEMINI. The teachers/trainers then transferred the knowledge they had acquired to the classroom, adapting it to different professional sectors/cross-cutting areas.
AI: a resource for personalising teaching
The initiative was carried out at the San Marco Vocational Training Centre in Mestre. This experimental project sought to overcome the limitations of traditional teaching by recognising the diversity of each student’s learning pace and style. The aim was therefore to tailor training to individual needs. The starting point was the creation of detailed profiles of a sample class in the first year of vocational training. The information on the students were then collected from: aptitude tests (logical-mathematical, expressive, visuospatial); learning style tests; personality tests (MBTI); Moreno tests to understand collaborative dynamics.
The test results, which were rigorously anonymised to protect student privacy, were used to feed NotebookLM, a versatile and powerful tool capable of analysing them accurately. Subsequently, the AI was tasked with forming homogeneous groups based on learning styles and affinities, using specific prompts enriched by the teachers’ pedagogical experience of classroom dynamics. For each group formed, NotebookLM was asked to clarify the common traits of the students, regarding preferred communication channels and relationships.
The next step involved selecting a standard maths activity for the first-year class: an exercise on composite geometric figures (calculation of perimeter, area, etc.). The real innovation was asking NotebookLM to rework this activity, adapting it to the styles of the different groups while maintaining the educational objectives.
NotebookLM proposed detailed plans
- Visual Groups: Use of tools to digitally represent the problem with coloured figures;
- Auditory Groups: Storytelling activity in which the geometric figure is described verbally, recording audio […] to reconstruct the figure as a game;
- Kinaesthetic Groups: Practical “tinkering” activity to create a geometric model with concrete materials (paper, string, cardboard).
The initial results were an increase in engagement, especially among students in the kinaesthetic group, who are often more prone to distraction in traditional learning contexts.
A timeless muse: AI meets art and education
The second exciting initiativeactively involved students and teachers in an experimental teaching experience focused on the use of generative artificial intelligence to create 13 paintings inspired by Venice, imagined as if they had been created by 20th-century painters.
The generated paintings gave rise to an artistic calendar that celebrates Venice through the virtual gaze of the great names of the last century.
The “A Timeless Muse” project required students to develop a wide range of skills, ranging from historical and artistic knowledge to stylistic analysis, project management, visual communication and the use of advanced digital technologies. Research and study were carried out to identify the most famous 20th-century artists (who had not already represented Venice) and their styles: from Dalí to Klimt, from Picasso to Miró, the students analysed visual languages, individual poetics and historical contexts.
This theoretical knowledge was then used to train artificial intelligence models. In a dynamic that reversed traditional roles, the students found themselves becoming real “teachers” of the machine, a tool to be trained and guided. They learned that the quality of the image generated depends largely on the accuracy, relevance and completeness of the initial command, and that creativity, even in the presence of such advanced tools, remains the central element of the process.
Both examples show how AI works when incorporated into a structured programme guided by well-defined educational objectives. It is not a question of replacing knowledge, but of amplifying it; not of reducing complexity, but of providing new tools to understand and manage it.
