Research on Intelligent Construction of NLP-Assisted Teaching Resources for Ideological and Political Education in College English Courses

Abstract

As a public foundation course combining instrumental and humanistic elements, the College English curriculum must not only fulfill its core mission of developing students' English language proficiency but also undertake the responsibility of ideological and political education through "value guidance". The quality of its ideological and political teaching resources directly impacts the effectiveness of moral education. Leveraging its powerful capabilities in text semantic understanding, sentiment analysis, and knowledge extraction, Natural Language Processing (NLP) technology provides a novel approach for intelligent construction of ideological and political teaching resources in College English education. Guided by the goal of "addressing the predicament of ideological and political (I&P) teaching resources in college English", this study explores the in-depth integration of Natural Language Processing (NLP) technology with I&P teaching resources. It clarifies the connotation and hierarchical needs of I&P teaching resources in college English, thereby constructing an NLP technology system for dual-dimensional mining of explicit and implicit I&P elements. The system enables the full lifecycle management of resources from generation to application, effectively supporting personalized learning and evaluation, and providing robust support for the integration of ideological and political education into college English courses.