Immersive Learning Model for University (ILMU): Conceptualizing VR-Based Model Distance Learning in Higher Education

The rapid adoption of immersive virtual reality (IVR) in higher education necessitates cohesive frameworks to guide its effective implementation. However, existing models remain fragmented, lacking integration of pedagogical, technological, and institutional components. This study addresses this gap by proposing the Immersive Learning Model for University (ILMU), a model tailored for higher education institutions adopting IVR-based distance learning, developed through the Design Research Methodology (DRM). The research systematically identifies critical success components via a scoping review of 227 studies, revealing six clusters: Learning Design, Technology, Immersion, Engagement, Interactivity, and Usability. These components were refined through Delphi verification with stakeholders (academics, developers, and users), resulting in 17 validated components. The ILMU model integrates these components into a layered structure, emphasizing institutional alignment (Standard, Policy & Curriculum), adaptive pedagogy, and immersive technological synergy. A quasi-experiment involving 80 students compared IVR-based learning (Nusameta apps) against traditional Zoom instruction. Results demonstrated significant learning gains for the IVR group (mean post-test: 77.75 vs 72.00; p = 0.042), validated by non-parametric tests (Mann–Whitney U = 592.50). The study highlights ILMU’s capacity to increase learning effectiveness, reduce cognitive load, enhance engagement, and align with institutional policies while addressing challenges such as hardware limitations and ergonomic design. By bridging theoretical rigour with empirical validation, ILMU offers a scalable framework for universities transitioning to immersive, technology-enhanced education. This work contributes to the evolving discourse on IVR in academia, providing actionable insights for educators, policymakers, and developers to optimize immersive learning ecosystems.