Designing Adaptive Interfaces in the Metaverse: Reducing Cognitive Load for Enhanced User Experience

Abstract

The increasing complexity of tasks in the metaverse often imposes high cognitive demands on users, hindering their performance and satisfaction. This study explores the development of adaptive interfaces designed to dynamically adjust to users' needs, reducing cognitive load in immersive environments. Using the NASA-TLX framework, we conducted controlled experiments to evaluate task completion times, error rates, and user-reported workload across adaptive and static interface designs. Results indicate that adaptive interfaces significantly improve user efficiency and satisfaction by minimizing mental and physical demands. These findings highlight the potential of adaptive human-computer interfaces in creating more intuitive, inclusive, and productive metaverse experiences.