【摘要】 该文以某高校思政类必修课程的学生评教结果为研究样本，从评教分数（封闭式问题）和意见建议（开放式问题）两部分出发，分析课程成绩与评教结果的关系，识别评教结果的有效性，探索高校学生评教结果应用路径。研究发现，学生课程成绩与评教分数整体数据呈现不相关，个别课程出现负相关；在大多数情况下，课程成绩为“中”（70分≤中<80分）的学生评教分数有效性最高；大一年级课程成绩中等以上（≥70分）的学生评教分数有效性高于其他年级。运用K-means聚类算法对评教数据进行聚类分析，将学生评教样本分为高满意高收获型、高满意低收获型、低满意高收获型和低满意低收获型四个类别。在课程成绩分析基础上，提出高校学生评教结果合理应用的建议。更多还原

【Abstract】 Using the students’ teaching evaluation results of ideological and political compulsory courses in a university as a research sample, the article analyzes the relationship between course scores and evaluation results, identifies the effectiveness of evaluation results, and explores its application path from two parts-closed question and open questions. The study found that the overall data of student course scores and evaluation scores are not correlated, and individual courses are negatively correlated; in most cases, students whose course scores are "medium"(70 points ≤medium<80 points) have the highest effectiveness in evaluation scores;the effectiveness of evaluation scores for students with average grades(≥70 points) in the freshman year is higher than other grades.The article uses K-means clustering algorithm to cluster the teaching evaluation data, and the students’ evaluation samples are divided into four categories: high satisfaction-high yield, high satisfaction-low yield, low satisfaction-high yield, and low satisfaction-low yield.Finally, the article puts forward some suggestions on the reasonable application of university students’ teaching evaluation results.更多还原