Constructing a Data-Driven Evaluation System for Ideological and Political Education in Foreign Language Courses: A Digital Intelligence-Empowered Framework for Higher Vocational Colleges

Abstract

The integration of ideological and political education (IPE) into foreign language teaching at higher vocational colleges faces persistent challenges in evaluation, including subjective judgment, lack of multidimensional data support, and the difficulty of quantifying internalized values such as patriotism, cultural confidence, and professional ethics. This paper proposes a comprehensive evaluation framework empowered by digital intelligence technologies—including big data analytics, artificial intelligence, and learning analytics—to address these limitations. Drawing upon curriculum ideology theory, educational evaluation theory, and learning analytics research, the study constructs a three-dimensional evaluation model encompassing value shaping, knowledge transmission, and competency development. The framework operationalizes abstract ideological goals into measurable indicators through Delphi method and analytic hierarchy process (AHP), enabling multidimensional, process-oriented, and dynamic assessment. A technical pathway for multimodal data collection and analysis is also presented, covering classroom interactions, online discussion content, project-based assignments, and speech recordings. This framework aims to bridge the gap between technology and value education, shifting the evaluation paradigm from experience-based perception to evidence-based precision diagnosis, thereby enhancing the quality and effectiveness of foreign language education with embedded moral and civic values.