The Construction of a Multimodal Teaching Content Analysis System for English in Colleges and Universities

Abstract

Based on multimodal theory, this paper constructs a multimodal content analysis system for college English with the digital model of teaching content, teaching interactive technology, and virtual reality technology as the main functional modules. The digital transformation of teaching content is done through the use of the particle swarm optimization algorithm and Wiki collaboration, and the learning objects in the learning content library are processed and transformed. The main technical aspects of shot detection, key frame determination, feature extraction, and feature matching are improved to establish the interactive function of English teaching videos. The quadratic error measurement algorithm enhances the edge folding algorithm and streamlines the 3D model to realize the virtual teaching simulation function. Students majoring in business English at a university in Kunming, Yunnan Province, China, are used as research objects to carry out the teaching application practice of this paper’s system. The total average English unit scores of the experimental class increased from 68.2 to 72.1 in the pre-test, and the recognition, comprehension, and utilization dimensions of the learning effect were higher than those of the control class by 0.46, 0.66, and 0.51, respectively, which showed a significant difference (P<0.05). The experimental group of subject students also had a better experience using the system in this paper.