A Study on the Construction of a Diversified Evaluation System for Ideological and Political Education in College English Courses Empowered by Digital Intelligence

As a required undergraduate course, College English carries the dual task of language training and value guidance. Against the backdrop of educational digitalization, the evaluation of its ideological and political component has long suffered from single evaluators, rigid indicators and unquantifiable value outcomes. This paper reports an empirical case study that implemented, over a sixteen-week semester at Qilu Normal University, a digitally empowered diversified evaluation system built on the CIPP model and learning analytics. The system integrated a multi-modal intelligent evaluation platform, a four-dimensional indicator system whose weights were determined through expert consultation and the Analytic Hierarchy Process (AHP), and a four-subject scoring mechanism. Data were collected from 216 non-English-major freshmen in four intact classes, covering online discussion posts, cross-cultural reflection journals, oral presentation audio and cross-cultural writing tasks. Algorithmic scores showed strong agreement with teacher ratings (Pearson r = 0.83), and a pre-post comparison indicated a significant improvement in students’ cultural identity and cross-cultural confidence (p < 0.01). The study specifies the observable variables feeding each CIPP dimension, justifies the weight allocation, describes how algorithmic scoring is validated and corrected, and discusses the boundaries and limitations of semantic and emotional analysis in capturing ideological growth. The findings offer an evidence-based reference for local normal universities seeking to reform their College English ideological and political evaluation.