Digital Technology-Driven Real-Time Data Processing and Visualization for Virtual Simulation Laboratories

Abstract

Virtual simulation laboratories have emerged as a critical component in modern STEM education, offering immersive and safe platforms for experiential learning. However, existing systems often lack cohesive frameworks for integrating real-time data processing, multimodal visualization, and adaptive instructional feedback—resulting in limited responsiveness and pedagogical value. To address these limitations, the authors propose the Integration–Real-time–Visualization with Feedback and Learning (IRV-FL) framework, a layered framework that semantically fuses heterogeneous sensor streams, performs real-time rendering, and delivers context-aware feedback to enhance learner engagement and accuracy. The system unifies physical and virtual environments through synchronous signal alignment, adaptive visualization pipelines, and dynamic feedback loops. Extensive experiments were conducted across eight dimensions, comparing IRV-FL against traditional virtual laboratories and six representative baseline models.