In this paper, we present LogiIQ, a VR-based logistics training platform designed to support repetitive learning and self-directed training to address the growing demand for skilled logistics personnel due to increasing industrial automation. We built LogiIQ on a Unity-based WebGL 3D environment to simulate the operation of key logistics equipment—robotic arms, AGVs, and forklifts. Furthermore, we implemented a system for continuous tracking of individual progress based on learning history by integrating a React and Spring Boot-based web dashboard to collect and visualize learner’s performance data in real time. In a pilot study involving novice users, we confirmed that average scores across all modules nearly doubled while the standard deviation decreased, thereby demonstrating that LogiIQ is effective in enhancing learner proficiency and reducing skill gaps among learners. By organically combining simulation, data analytics, and adaptive feedback, we have established a self-directed, data-driven learning environment that goes beyond simple virtual training. Through this research, we aim to lay a foundation for more consistent and effective practical training in logistics education.
목차
Abstract 1. Introduction 2. Related Work 2.1 VR and Metaverse-Based Education 2.2 Digital Twin-Based Training 2.3 Learning Analytics and Personalized Feedback 2.4 Distinctiveness of This Study 3. Method 3.1 Platform Overview 3.2 Development and Implementation Environment 3.3 Unity-based Metaverse Environment 3.4 Learning Module and Mission Structure 3.5 Real-time Learning History Management Web System 3.6 Interactive Guide Character (RO:RO) 4. Experiments and Results 4.1 Experimental Design 4.2 System Implementation Results 4.3 Learning Outcomes Analysis 5. Discussion 6. Conclusion References