With Ital.IA Lab for School, literature becomes a laboratory for analysis
(…) il tormentato esaminator di sè stesso, per rendersi ragione d’un sol fatto, si trovò ingolfato nell’esame di tutta la sua vita. Indietro, indietro, d’anno in anno, d’impegno in impegno, di sangue in sangue, di scelleratezza in scelleratezza: ognuna ricompariva all’animo consapevole e nuovo, separata da’ sentimenti che l’avevan fatta volere e commettere; ricompariva con una mostruosità che que’ sentimenti non avevano allora lasciato scorgere in essa. Eran tutte sue, eran lui: l’orrore di questo pensiero, rinascente a ognuna di quell’immagini, attaccato a tutte, crebbe fino alla disperazione.
Come si misura il tormento di una coscienza? È possibile trasformare la notte dell’Innominato in un grafico? E soprattutto: cosa succede quando a leggere Manzoni, insieme agli studenti, è anche un’intelligenza artificiale?
Sono le domande al centro di un nuovo percorso didattico sviluppato dalla docente Francesca Sabatini nell’ambito di Ital.IA Lab for School, che trasforma I Promessi Sposi in un laboratorio di analisi del sentimento, dati e pensiero critico.
Nel modulo “Il cuore sdoppiato: l’Innominato tra umano e IA”, il testo non è solo oggetto di interpretazione, ma diventa un sistema da analizzare. Gli studenti lavorano sulla crisi morale dell’Innominato usando due categorie chiave:
- Valenza (emozione positiva o negativa)
- Attivazione (intensità emotiva)
Parole come vergogna, rimorso, paura, speranza vengono isolate, discusse, interpretate. E poi trasformate in dati. In classe entra l’intelligenza artificiale, ma con un ruolo preciso: non sostituire l’interpretazione, ma metterla alla prova. Gli studenti utilizzano strumenti come Microsoft Copilot per:
- analizzare automaticamente il sentiment del testo
- classificare le emozioni
- confrontare i risultati con la propria lettura
Il risultato è un vero e proprio esperimento: analisi umana vs analisi algoritmica. E spesso emerge una differenza decisiva. L’IA individua la paura. Gli studenti riconoscono la redenzione. Uno degli elementi più potenti del percorso è il confronto tra prospettive diverse. Come emerge dal lavoro in classe, l’analisi si sviluppa attraverso tre “lenti”:
- La lente umana. Lenta, filologica, attenta alle sfumature. Coglie ironia, ambiguità, contesto.
- La lente artificiale. Rapida, sintetica, capace di individuare pattern e ricorrenze.
- La lente computazionale. Trasforma le parole in numeri, le emozioni in dati, rendendo visibile l’andamento del personaggio.
(…) the tormented examiner of himself, in order to make sense of a single event, found himself engulfed in an examination of his entire life. Backwards, backwards, year by year, endeavour by endeavour, blood by blood, wickedness by wickedness: each reappeared to his conscious and renewed mind, separated from the feelings that had made him desire and commit them; it reappeared with a monstrosity that those feelings had not then allowed him to perceive in it. They were all his, they were him: thehorror of this thought, reborn with each of those images, attached to them all,grew to the point of despair.
How does one measure the torment of a conscience? Is it possible to transform the Unnamed’s night into a graph? And above all: what happens when, alongside the students, an artificial intelligence is also reading Manzoni?
These are the questions at the heart of a new educational programme developed by lecturer Francesca Sabatini as part of Ital.IA Lab for School, which transforms The Betrothed into a workshop on sentiment analysis, data and critical thinking.
In the module “The split heart: the Unnamed between human and AI”, the text is not merely the subject of interpretation, but becomes a system to be analysed. Students explore the Unnamed’s moral crisis using two key categories:
- Valence (positive or negative emotion)
- Arousal (emotional intensity)
Words such as shame, remorse, fear, hope are isolated, discussed and interpreted. And then transformed into data. Artificial intelligence enters the classroom, but with a specific role: not to replace interpretation, but to put it to the test. Students use tools such as Microsoft Copilot to:
- automatically analyse the sentiment of the text
- classify emotions
- compare the results with their own reading
The result is a genuine experiment: human analysis vs algorithmic analysis. And often a decisive difference emerges. The AI identifies fear. The students recognise redemption. One of the most powerful elements of the course is the comparison of different perspectives. As the classroom work reveals, the analysis unfolds through three ‘lenses’:
- The human lens. Slow, philological, attentive to nuances. It captures irony, ambiguity and context.
- The artificial lens. Rapid, concise, capable of identifying patterns and recurrences.
- The computational lens. It transforms words into numbers, emotions into data, making the character’s development visible.
The point is not to choose the best method. The value lies in the comparison. From the dialogue between these perspectives emerges a richer and more informed understanding. Literature thus also becomes an exercise in data literacy and data storytelling. The heart of the course is learning to recognise emotional ambiguity, to question the results of AI, and to argue for a well-founded interpretation. Because, whilst the algorithm is quick to read the words, only a human being can grasp their moral significance.
A replicable model
The course, lasting approximately 120 minutes, is structured in four phases:
- introduction to the crisis of the Unnamed
- group philological analysis
- experiment with AI and construction of prompts
- critical comparison and final discussion
A model that can also be replicated in other contexts:
- in scientific disciplines
- in primary school (with simplified narrative texts)
- in interdisciplinary courses combining literature, data and technology
A comprehensive ecosystem for teachers
DOWNLOAD THE FULL TOOLKIT FROM THE FMD ACADEMY
The module is part of a wider system that provides:
- ready-made teaching units
- worksheets for students
- guides for the critical use of AI
- assessment rubrics and monitoring tools
- examples of real-world projects
Not an isolated activity, but a structured teaching model, ready to be adapted and brought into the classroom. Unexpected questions emerge during the work. Students realise that:
- AI simplifies what is complex
- emotions are not always classifiable
- context changes the meaning of words
And above all, they understand that reading a text does not just mean understanding it, but interpreting it, discussing it, relating it to the present.
