This paper advances a cautiously framed research-and-practice programme for integrating Artificial Intelligence (AI) into inclusive education. We read AI through a threefold lens—AI as tool, mediator, and environment—and align these roles with neurocognitive, technological, and methodological–didactic dimensions of design, drawing on Universal Design for Learning (UDL) and special pedagogy. We argue that AI differs in kind from earlier digital media and, accordingly, calls for teacher orchestration competences attentive to neurodiversity, ethics and institutional governance. Bringing together reviews of AI in education and inclusive contexts, studies of perceptions among learners and teachers, and policy/ethical frameworks, we sketch an implementation-science-informed action-research design that couples AI literacy for teachers with in-situ mini-pilots and feasibility-oriented evaluation (feasibility, acceptability, appropriateness, fidelity). This paper introduces a nascent orchestration framework and a measurement toolkit to support ethically robust, context-aware implementation; both are presented for iterative refinement and empirical testing.

Orchestrating Artificial Intelligence as Tool, Mediator, and Environment: Towards Inclusive Learning Ecosystems

Pagliara, Silvio Marcello
;
Bonavolonta, Gianmarco;Mura, Antonello
2026-01-01

Abstract

This paper advances a cautiously framed research-and-practice programme for integrating Artificial Intelligence (AI) into inclusive education. We read AI through a threefold lens—AI as tool, mediator, and environment—and align these roles with neurocognitive, technological, and methodological–didactic dimensions of design, drawing on Universal Design for Learning (UDL) and special pedagogy. We argue that AI differs in kind from earlier digital media and, accordingly, calls for teacher orchestration competences attentive to neurodiversity, ethics and institutional governance. Bringing together reviews of AI in education and inclusive contexts, studies of perceptions among learners and teachers, and policy/ethical frameworks, we sketch an implementation-science-informed action-research design that couples AI literacy for teachers with in-situ mini-pilots and feasibility-oriented evaluation (feasibility, acceptability, appropriateness, fidelity). This paper introduces a nascent orchestration framework and a measurement toolkit to support ethically robust, context-aware implementation; both are presented for iterative refinement and empirical testing.
2026
9783032176035
9783032176042
Artificial Intelligence in Education· Inclusive Pedagogy· Universal Design for Learning (UDL)· Teacher Orchestration · Implementation Science (Action Research)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/473990
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