The Enriched Twin: An Updated Ethical-Pedagogical Framework for K-12 Digital Heritage Education in the Agentic AI Era

Abstract

The rapid evolution of agentic artificial intelligence (Agentic AI) and digital twin technologies has profoundly transformed cultural heritage preservation and education. These tools enable immersive, interactive reconstructions of historical sites and artifacts, fostering deeper engagement with the past. However, they also pose significant risks, including the amplification of biases, perpetuation of colonial narratives, and erosion of community data sovereignty if applied without critical oversight. This updated framework revisits the ‘Enriched Twin’ project-based learning (PBL) program within a STEAM (Science, Technology, Engineering, Arts, and Mathematics) context, incorporating advancements in Agentic AI from 2024–2025. It interweaves three core conceptual threads: (1) the progression from static digital twins to semantically enriched, Agentic AI-augmented knowledge ecosystems; (2) a critical hermeneutics of AI, scrutinizing Agentic AI’s dual capacity as an analytical instrument and a propagator of cognitive biases; and (3) decolonizing methodologies that prioritize community data sovereignty and ethical co-creation. Practical modules encompass drone-based data capture and Agentic AI-assisted 3D modeling, culminating in collaborative development of ‘enriched’ digital twins for local heritage sites. This model cultivates technical proficiency alongside digital literacy, critical judgment, and ethical responsibility, aligning with UNESCO’s 2021 Recommendation on the Ethics of Artificial Intelligence and recent Agentic AI guidelines for education (UNESCO, 2025a). By embedding these principles, the framework extends beyond technical instruction to promote holistic development, preparing K-12 students as responsible digital stewards. Future research trajectories include cognitive-affective evaluations, design-based iterations, and action research on community partnerships to validate and refine this approach for broader applicability in digital humanities education.