Application of Deep Learning for Discourse Expression Recognition in Ideological and Political Education

Abstract

The subject context in consideration with discourse expression recognition (DER) provides a communication bridge between ideological and political education (IPE) for budding college students. This paper introduces a novel method for integrating the deep-learning-based approach to ideological and political education in consideration of the discourse expression of subject context. Initially, the relation between ideological and political education is analyzed. Then, the efficiency of teaching is enhanced with the help of deep learning mechanisms; in addition to the flipped classroom and online education, an innovative model of education is proposed using deep learning methods. To perform the experiment, 236 subjects were randomly selected from Hohai University, and the analysis was performed with the help of surveys conducted using a questionnaire. The statistical results prove that the selected questionnaire has a high degree of validity and reliability. Thus, from the analysis, it is observed that most of the students have a better understanding of the subject context in discourse expression of ideological and political education. Moreover, about 50% of the students have a positive approach to the subject contexts and the education methods, making them active in reaching a satisfactory learning effect. The obtained results indicate that the benefits of deep learning in ideological and political education enhance the interest of the students in pursuing this with renowned subject context.