Optimization of Higher Education Teaching Method System Based on Edge Intelligence

Abstract

Abstract Nowadays, educational information technology is widely used in higher education teaching, but various teaching resources are not reasonably utilized and effectively managed. In order to solve such problems, this paper introduces edge computing in the basic cloud computing environment to innovate and optimize the multimedia teaching mode of higher education, proposes a VR edge cloud classroom teaching mode, and proposes a collaborative transmission and resource allocation strategy based on DIBR vision synthesis technology to optimize the teaching experience. The VR Edge Cloud Classroom teaching model is designed from three aspects: teaching methods, teaching content, and teaching evaluation. Through practical teaching, students believe that the advantages of this teaching mode are mainly rich in learning resources, conducive to learning-related knowledge and that they will achieve gains in expanding their knowledge, improving their independent learning ability and cultivating their analytical and problem-solving ability. Comparing and analyzing the teaching effect of VR edge cloud classrooms with the traditional teaching effect, there is a significant difference between the two in terms of the achievement of the total objectives (P=0.015<0.05). The teaching effect of a VR edge cloud classroom is significantly better than that of a traditional classroom.