Design of a virtual simulation enhanced OBE teaching model for continuing education

Abstract

To address the shortage of practical teaching resources in continuing education, this study introduces a virtual simulation-enhanced Outcome-Based Education (OBE) model, termed VS-OBE. By integrating high-fidelity 3D scenes with multimodal perception, the system employs a four-layer closed-loop architecture (perception, data, evaluation, and feedback). Utilizing Unity 3D, SteamVR, and physiological sensors, the model synchronously acquires operation trajectories, gaze behavior, and physiological responses. The system applies Dynamic Time Warping (DTW) and data fusion strategies to map sensor signals to OBE capability indicators, evaluating achievement levels through product forms that highlight "short board effects." Experimental results demonstrate that the VS-OBE model significantly outperforms traditional methods, improving comprehensive ability attainment (91.3 vs. 72.5), operational standardization (0.92 vs. 0.71), and task timeliness (258.4s vs. 342.5s), while reducing cognitive load (NASA-TLX 8.7 vs. 12.4). Furthermore, adaptive difficulty adjustments and visual feedback effectively promote long-term knowledge retention. This research confirms the value of virtual simulation and multi-sensor fusion in high-risk training, offering a novel pathway for innovating continuing education.