基于眼动追踪技术的VR学习环境优化设计OA

To systematically evaluate the optimization effects of different interaction methods on learners' cognitive load in a virtual reality(VR)learning environment,this study designed an eye-tracking data visualization pipeline suitable for VR learning environments.Thirty non-history major undergraduates were recruited to conduct a randomized controlled experiment in a virtual museum learning environment.The visual guidance and feedback mechanism based on eye-tracking was validated using pre-and post-test knowledge questionnaires and 1 128 378 pupil diameter data points.The results showed that in terms of knowledge acquisition,the post-test scores of the experimental group were significantly higher than those of the control group(P＜0.05).In terms of cognitive load and attention performance,there were extremely significant differences in both the mean pupil diameter and the amplitude of change between the two groups(P＜0.001),indicating that the optimized interaction design can effectively regulate learners' cognitive effort.Thus,the optimization design of VR learning environments based on eye-tracking can significantly enhance knowledge acquisition efficiency and improve cognitive experience,providing practical evidence for the design and instructional application of immersive learning environments.