Rapid advances in Artificial Intelligence (AI), Digital Twin (DT) technology, and the Metaverse have created new opportunities for transforming STEM education and workforce preparation. However, existing learning systems remain fragmented and lack an integrated, human-centered framework capable of supporting high-fidelity simulations, adaptive learning, and real-time competence development aligned with Industry 5.0. This study addresses this gap by developing a unified AI-Based Digital Twins Metaverse (AI-DTM) framework aimed at strengthening STEM employability skills and fostering adaptive expertise in higher education. This research employed a conceptual–analytical design comprising three structured phases: (1) a systematic conceptual synthesis guided by PRISMA 2020 to identify technological, pedagogical, and human-centric mechanisms relevant to AI, DTs, and Metaverse-based learning; (2) construction of an integrated AI-DTM framework through theoretical mapping, concept modeling, and iterative refinement; and (3) expert validation involving specialists in AI systems, digital twins, immersive learning, and instructional design. Evidence from interdisciplinary literature across AI-enhanced learning, DT-enabled simulation, and XR-based experiential environments informed the development of the framework. The resulting AI-DTM framework integrates AI-driven learner modeling, real-time DT simulations, and immersive Metaverse environments to create a unified, adaptive ecosystem. Key outcomes include: (a) personalized learning pathways supported by intelligent analytics and automated feedback; (b) high-fidelity, risk-free simulations that replicate authentic STEM work processes; (c) immersive and collaborative virtual experiences that enhance engagement, problem-solving, and teamwork; and (d) continuous competence profiling enabling the development of adaptive expertise. The framework demonstrates strong alignment with Industry 5.0 principles, supporting human–AI collaboration, data-driven decision-making, and future workforce readiness. This study provides a novel, scalable model that advances the design of AI-enabled learning ecosystems by integrating AI, Digital Twins, and Metaverse technologies into a cohesive architecture. The AI-DTM framework offers theoretical and practical contributions for enhancing STEM employability skills, strengthening adaptive expertise, and guiding institutions.
Syarifuddin et al. (Mon,) studied this question.