Exploring the Reform of College English Teaching from the Perspective of New Liberal Arts

Abstract

The construction of new liberal arts requires college English teaching to introduce new concepts, utilize new technologies, and promote students’ effective learning through the intersection of disciplines and curricula, to cultivate integrative talents with innovative and practical abilities. Under the perspective of new liberal arts, this paper integrates deep commonality and uniqueness knowledge mining multimodal clustering, DCUMC algorithmic model and multimodal teaching means to construct a multimodal analysis model framework and reform the English teaching model in colleges and universities. In addition, the information entropy is used to improve the ID3 algorithm to construct multidimensional evaluation indexes for college English teaching, and the improved ID3 algorithm is used for data mining of multidimensional evaluation so that teachers can adjust the teaching progress and difficulty according to real-time and accurate feedback information. Experiments are conducted on multimodal teaching mode and teaching evaluation, and the experimental results show that compared with the traditional teaching mode, the average scores of multimodal English teaching mode after five months are 96 and 85, which is an improvement of 11 points, 69.58%, 67.93%, 56.25%, and 53.79% higher in the ratio of excellent and good evaluations, respectively. Compared to the single teaching evaluation, the multidimensional evaluation points out that the traditional teaching mode needs more designer-student interaction as well as a reduction in the difficulty of the teaching content. In conclusion, the multimodal English teaching model can effectively improve teaching effectiveness and is implementable.

Keywords

• dcumc algorithm
• id3 algorithm
• multimodal clustering
• teaching reform
• 97m80