Inheritance and Innovation Mode of Red Culture in Civic Education of Colleges and Universities in the Digital Era

Abstract

This paper constructs an immersive red culture learning interactive system, clarifies the architecture and its function of ideological education. With the help of 3D high-precision scene modeling and Leap Motion gesture recognition technology, key methods including vector data acquisition and error correction, hierarchical feature gesture recognition are proposed. Through digital twin, multimodal interaction and adaptive adjustment algorithm, the intelligent and personalized red culture education process is realized. Simulation experiments and system application practices are designed to verify the significant advantages of the proposed system in terms of interactive performance and educational effectiveness. In the 3D high-precision scene construction virtual reality modeling experiment, the proposed method tests the highest scene resolution among the three methods. When the number of scene images is 200, the proposed method still achieves a resolution of 1323.53ppi, which is much higher than the control method. The proposed method also performs optimally in terms of construction time and construction effect, and the scores of all the evaluation dimensions of interactive performance are above 4.0. In teaching practice, the total score of the experimental group class reached 84.26±3.05, far exceeding the 77.12±4.11 of the control group class.