Design Principles and Observable Indicators for AI-Enabled Pedagogical Accompaniment: Evidence from the Amico Dual-Mode Prototype in Italy and China
Pier Paolo Benedetti

TL;DR
This paper presents a framework for designing AI-enabled pedagogical tools emphasizing human responsibility, transparency, and relational micro-mediations, demonstrated through the Amico prototype in Italy and China.
Contribution
It introduces a set of design principles and observable indicators for AI pedagogical accompaniment, grounded in a human-in-command approach and tested across two cultural contexts.
Findings
Feasibility and usefulness of the prototype in vocational education contexts.
Effective micro-mediations facilitate access and transition to human interactions.
Design principles enhance transparency, scaffolding, and ethical considerations in AI education.
Abstract
AI-enabled systems are increasingly introduced into educational contexts, yet their effectiveness depends less on technological sophistication than on the quality of pedagogical mediation, ethical constraints, and context-sensitive design. This paper proposes a replicable framework for AI-enabled pedagogical accompaniment, grounded in a human-in-command approach in which adult responsibility remains central and AI functions as an enabling, non-substitutive infrastructure. Building on the Amico project, we operationalize the concept of a relational bridge as a sequence of micro-mediations that lower the threshold of access to educational relationships and facilitate transitions toward meaningful human interaction with teachers, peers, and communities of practice. The contribution synthesizes a set of design principles, including transparency of system identity and limits, scaffolding…
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