The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problemsin both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

中文翻译：

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基于人工智能的高校思想政治教育管理系统框架研究

高校思想政治理论课管理的重要性客观上体现了思想政治理论课的重要性。当前，高校思想政治理论课管理存在宏观和微观两方面的较大问题。本文结合人工智能技术，构建了基于人工智能的高校思想政治教育智能化管理系统，通过学籍智能识别进行课堂督导。提出了基于KD-Tree的KNN离群点检测算法来提取班级学生的状态信息。通过数据模拟，可知本文提出的KD-KNN离群点检测算法在保证KNN算法分类精度的同时，显着提高了算法效率。通过实验研究可以看出，该制度的构建不仅从宏观上明确了管理的方向，而且从微观上揭示了具体的管理方法，在一定程度上有效地解决了管理中存在的问题。高校思想政治理论课.