K均值聚类在高校教师评价分析中的应用研究

摘要

As an important link of internal quality management and the basis of performance appraisal,the issue of college teachers' eval-uation is always the research plume. At present,about this issue,the arithmetical average method is usually adopted,but it can't deeply excavate connotative information,and therefore can't accurately reflect teachers' comprehensive situation. Using K-means to cluster the evaluation results of teachers' teaching,scientific research,and teachers' code of morality in some major for a whole year,and analyze the clustering results in detail. The results show that the clustering algorithm can obtain more effective information from the evaluation da-ta which is very helpful for the teaching management more accurately grasping the characteristics of teachers,developing a more effective strategy training,improving the overall quality of teachers.%作为高校内部质量管理的重要环节及学校绩效考核的重要依据，高校教师评价问题一直以来都是研究的热点。当前对高校教师的评价，通常采用算术平均线性划分法，对隐含的信息没有进行深入挖掘，难以全面准确地反映教师的综合情况。运用K均值聚类算法对某高校某专业教师一学年的教学、科研和师德评价结果进行聚类，并对聚类结果进行详细分析。结果表明聚类算法能从评价数据中获取更多的有效信息，为教学管理者更加准确地掌握教师的特点，制定更为有效的培养策略，全面提高教师综合素质提供了大力的帮助。