Despite the rapid advancement of virtual reality (VR) and its integration into educational settings, the adoption of metaverse learning platforms often encounters challenges. These include technical limitations and a lack of understanding of how these platforms impact learning effectiveness and user engagement. Previous studies have revealed mixed outcomes regarding the effectiveness of VR in education, with many platforms failing to meet user expectations in terms of usability and learning outcomes. This uncertainty hampers the broader adoption of immersive learning technologies. Thus, this study aims to investigate what factors contribute most significantly to the effectiveness and user adoption of metaverse learning platforms. Specifically, it examines how perceived usefulness and efficiency influence learners' intentions to use these platforms. Utilizing a Technology Adoption Model specifically adapted for VR in the metaverse, the study conducted a comprehensive survey assessing various constructs such as immersive quality, intuitiveness of the user interface, and functionality of interactive elements in food science education. Linear regression analysis was employed to analyze the data, revealing that perceived usefulness (USE) and perceived efficiency (PERF2) are significant predictors of learners' intent to use the platform, explaining 62.6% of the variance in intent scores. The findings suggest that enhancing the practical utility and optimizing the efficiency of metaverse learning platforms are crucial for improving their adoption and effectiveness. Based on these insights, recommendations for platform developers include focusing on real-world applicability and connectivity with lecture content, improving technical performance, and enhancing user support mechanisms within the platform. [For the complete proceedings, see ED672804.]