Conference Program

The rapid integration of generative AI into educational contexts raises a fundamental pedagogical question: how can schools prevent students from delegating thinking to machines and instead cultivate the critical agency that democratic education requires? This contribution presents an empirical case study developed in a secondary vocational school (Servizi Socio-Sanitari, IISS Don Milani Pertini Morante, Grottaglie, Italy), exploring how a deliberately designed pedagogical framework — the AI-Resistant Debate — can transform AI interaction into a site of metacognitive practice.

The framework rests on a core assumption aligned with Vygotsky’s Zone of Proximal Development: AI does not replace human mediation but can function as a challenging dialogical partner (Bakhtin) whose outputs demand critical scrutiny. In the AI-Resistant Debate, student teams are invited to use generative AI tools (ChatGPT, Gemini) during the preparation phase, but with a crucial constraint: they must keep an AI-Log — a reflective diary documenting every AI suggestion accepted, every one rejected, and the reasoning behind each decision. This protocol becomes a powerful metacognitive mirror (Flavell, 1979): by externalising their decision-making process, students learn to distinguish their own reasoning from automated output, to identify hallucinations, and to exercise what the framework terms “critical prompting” — the capacity to interrogate AI rather than accept it as an oracular authority.

Two complementary activities enrich this core design. In the augmented storytelling modules, students used NotebookLM and Gemini to reinterpret canonical literary texts (Dante, D’Annunzio, Verga) and historical sources (Magellan’s circumnavigation) in multimodal formats: podcasts, infographics, video scripts, and vision boards. Here, the AI-Log evolved into a production diary tracking creative agency — which ideas originated with the student, which were AI-generated, and how human and machine authorship were negotiated. A complementary Prompt-Book for Authentic Assessment provides teachers with structured prompts for metacognitive evaluation, including a rubric specifically designed to assess the quality of students’ AI dialogue — distinguishing passive consumption from critical co-creation.

The debriefing session concluding each activity foregrounds the democratic dimension of the framework. Guided by questions such as “Who was controlling whom?” and “Where did your thinking end and the machine’s begin?”, students reflect collectively on epistemic autonomy, the risks of automation bias, and the civic responsibilities entailed in using AI-generated content in public discourse.

Qualitative data drawn from AI-Logs, self-assessment checklists, and post-activity reflections suggest that the framework effectively nurtures higher-order thinking skills — analysis, evaluation, and creation in the revised Bloom’s taxonomy (Krathwohl, 2002) — while developing a practised scepticism toward AI outputs. Students who engaged most rigorously with the AI-Log demonstrated stronger argumentative coherence and greater ownership of their final products.

This case study contributes to the panel’s inquiry by demonstrating that the critical potential of AI in schools is not inherent in the technology itself, but in the pedagogical scaffolding that surrounds its use. The AI-Resistant Debate and AI-Log offer a replicable framework for ensuring that AI amplifies, rather than erodes, the conditions for democratic learning.