Abstract
Monitoring and evaluating teachers’ ideological and political work in Chinese universities is critical, but there are practical challenges in evaluating it scientifically and efficiently. Big data and artificial intelligence technologies provide new ideas and methodologies to address these challenges. This study proposes a technical path empowered by data intelligence for evaluating university teachers’ ideological and political work. It conducted comprehensive profiling and assessment based on data by establishing an evaluation framework through Large Language Model (LLM) technology, data analysis, and visualization methods. This study provides references for the implementation path and methodological strategies to enable quality monitoring and evaluation of university teachers’ ideological and political work in the era of digital intelligence.
Published Version
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