基于变异性和聚类分析的高校班级学困群体识别

为了准确把握高校学生学习状况,提高人才培养质量,结合变异性分析方法和系统聚类算法,提出一种精准识别高校班级学习困难群体的新方法。首先,利用变异性分析得到学生课程成绩变异程度,得到变异程度较大的课程列表,并分析变异原因;其次,从学习质量的角度出发,利用系统聚类算法对学生群体进行分类;最后,将建立的新方法与传统分析方法进行比较。分析结果表明,建立的新方法能够科学分析学生的学习状况,对学生群体进行合理分类,并准确识别学习存在困难的学生群体。

In order to accurately grasp the learning status of college students and improve the quality of talent cultivation,a new method for accurately identifying groups with learning difficulties in one class of universities is proposed combining variability analysis methods and systematic clustering algorithms.First,the degree of variation of the students’course grades is be obtained by using the variability analysis and the list of courses with a large degree of variation,and the reasons for the variation can be analyzed.Secondly,from the perspective of learning quality,a systematic clustering algorithm is used to classify the student population.Finally,the established new method is compared with the traditional analysis method.The analysis results show that the established new method can scientifically analyze the learning situation of students and classify the student groups reasonably and accurately identify the student groups with learning difficulties.