Conference Program

The rapid diffusion of artificial intelligence in educational contexts is reshaping the epistemic conditions of teaching and learning, particularly in mathematics education, where generative systems provide immediate solutions and procedural explanations. While such tools offer new forms of cognitive support, they also raise critical concerns regarding student agency, pedagogical judgment, and the preservation of democratic learning spaces within increasingly datafied environments (Williamson, 2017). The challenge, therefore, extends beyond technological adoption to the cultivation of critical AI literacy, understood as the capacity to question, interpret, and responsibly engage with algorithmically generated knowledge (Long & Magerko, 2020).

This paper presents a classroom-based study conducted in a classical high school in Bagheria (Sicily, Italy), where AI-powered mathematical applications were integrated through structured pedagogical mediation. Drawing on Vygotsky’s sociocultural framework (1978), AI is conceptualized as a mediating artifact operating within the learner’s Zone of Proximal Development rather than as an autonomous authority. Metacognition (Flavell, 1979) and dialogism (Bakhtin, 1981) provide the theoretical lens through which student–AI interaction is analyzed.

The study adopts a mixed-method case-study design. A structured questionnaire administered to the entire course provided descriptive data on students’ patterns of AI use, while qualitative thematic analysis of student narratives examined processes of cognitive support, cognitive delegation, metacognitive engagement, and teacher mediation. Questionnaire findings indicate that most students initially approached AI as a procedural support tool, whereas a smaller group demonstrated explicit metacognitive monitoring and systematic comparison between AI outputs and classroom reasoning. Qualitative analysis further revealed differentiated trajectories of instrumental use and reflective appropriation.

Rather than interpreting instrumental engagement as failure, the study frames such variability as part of a process of instrumental genesis (Rabardel, 1995), through which learners progressively appropriate new cognitive tools. Sustained teacher mediation functioned as an epistemic anchor, ensuring that AI outputs remained embedded within disciplinary mathematical reasoning rather than substituting it.

The findings suggest that AI integration, when embedded within dialogical pedagogy and supported by metacognitive scaffolding, can strengthen student agency and sustain democratic learning environments. In this perspective, critical dialogue with AI emerges as foundational to preserving mathematics education as a space of reflective judgment, disciplinary rigor, and responsible technological engagement.