考试成绩是评估教学质量的一项重要依据,相比于k-means算法需要确定合适聚类数目的缺点,利用自组织神经网络(SOM)对学生成绩自动聚类。根据聚类结果分析学生的学习差异和学习特点,以提高和完善教师的教学方法。 Test scores are an important basis for assessing teaching quality. Compared with k-means algorithm, it is necessary to determine the appropriate number of clusters. Self-organizing neural network (SOM) is used to automatically classify student’s grades. According to the clustering results, students’ learning differences and learning characteristics are analyzed to improve and perfect the teaching methods of teachers.