The emergence of the metaverse marks a transformative shift in digital education, offering immersive, collaborative and personalised learning experiences. However, its convergence with artificial intelligence (AI) raises notable concerns related to data privacy, learner security and ethical transparency. Whilst various studies have explored these domains independently, comprehensive understanding regarding the intersection of security and privacy-preserving AI methods within educational metaverse environments is still lacking. Aiming to address this gap, this paper presents a comprehensive systematic review conducted in accordance with the PRISMA protocol, synthesising current research on the integration of AI with security and privacy mechanisms in metaverse-based learning systems. A total of 60 research studies published between 2020 and 2025 were examined in the present systematic review. The review focuses on key educational domains, including language learning, STEM education and health education, and critically examines the role of AI techniques such as federated learning, differential privacy, blockchain and machine learning to enhance trust and data governance in immersive environments. Based on this synthesis, we introduce the Secure and Ethical AI Framework (SEAF), a conceptual model designed to guide the development of secure, privacy-aware and pedagogically aligned metaverse learning environments. SEAF integrates ethical, technical and educational considerations to support trustworthy AI-driven learning. This study contributes to the field of educational computing by deepening theoretical insights and offering a practical framework for implementing AI-driven metaverse systems that prioritise ethical learning and digital trust. Additionally, the study identifies key research gaps and outlines a future research agenda to support interdisciplinary collaboration at the intersection of AI, privacy and educational innovation.
Salah et al. (2026) studied this question.