A Study on the Precision Implementation Path and Effectiveness Evaluation of Ideological and Political Education in Higher Education Based on Big Data
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Abstract
The integration of big data technologies provides new opportunities for improving the precision and effectiveness of higher education management. This study proposes a big-data-driven framework for the precise implementation and effectiveness evaluation of ideological and political education in universities. A three-layer architecture consisting of data acquisition, intelligent analysis, and decision support is established, while an evaluation system covering knowledge acquisition, value identification, and behavioral transformation is developed. Through a one-year empirical study involving multiple universities, learning behavior records, participation data, and practical activity outcomes are analyzed using association rule mining, clustering analysis, and propensity score matching. The results reveal distinct student profiles and demonstrate that personalized intervention strategies significantly improve educational effectiveness. The proposed framework contributes to data-driven educational governance and provides methodological references for behavior analysis, information processing, and intelligent decision-support systems.
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