The Application of Data Mining Technology in the Evaluation of the Integration of 'Four Histories' into Ideological and Political Courses in Colleges

Integrating "Four Histories" education into ideological and political courses in universities is a practical necessity for implementing the fundamental task of cultivating moral integrity. However, the assessment of integration effectiveness still faces challenges such as high subjectivity and difficulty in quantification. This paper proposes the use of data mining techniques to enhance the effectiveness of evaluating the integration of "Four Histories" into ideological and political courses. By applying methods such as clustering, classification, and sentiment analysis, this study offers an innovative and objective approach to assess educational outcomes. The results demonstrate that data mining can effectively reduce evaluation bias and provide valuable feedback for improving teaching strategies. This study contributes to optimizing the evaluation methods for integrating "Four Histories" into ideological and political courses through modern technological approaches.