Conference Program

When students use generative AI to translate Latin and Ancient Greek, are they thinking more—or thinking less? This paper presents findings from an exploratory qualitative case study conducted in an Italian classical high school, examining how AI reshapes interpretative practices in subjects traditionally centred on judgement, ambiguity, and linguistic precision. Data were collected through structured classroom observations, analysis of student translations, and guided reflective discussions during AI-supported activities.

Two contrasting patterns emerge. Some students fully delegate the task to AI systems, reproducing translations without engaging in grammatical analysis or interpretative reasoning. In these cases, AI functions as a form of cognitive substitution, weakening agency and displacing responsibility for judgement. Other students, however, use AI as a cognitive scaffold: they compare outputs with their own attempts, question lexical and syntactic choices, and refine their understanding in preparation for oral examinations. Here, AI becomes a mediating tool that can potentially extend the learner’s zone of development.

These findings suggest that the educational impact of generative AI does not depend on the technology itself but on the pedagogical structure framing its use. As algorithmic systems trained on vast datasets, generative models embed implicit linguistic and cultural assumptions that shape the interpretative options presented to learners. Without explicit critical mediation, such systems risk becoming oracular authorities.

In response, the paper proposes a three-step instructional protocol designed to foster metacognitive awareness and dialogical engagement: (1) independent translation attempt; (2) systematic comparison with AI output; and (3) guided reflection on divergences, interpretative criteria, and underlying assumptions. By making algorithmic mediation itself an object of inquiry, students learn to interrogate digital power rather than passively absorb it. Such practices cultivate habits of justification, responsibility, and reflective judgement—capacities essential to democratic learning in an age of datafication.