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Evaluating students' learning achievement based on the eigenvector method

机译:基于特征向量法的学生学习成绩评估

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In this paper, we present a new method for students' learning achievement evaluation based on the eigenvector method. The proposed method considers the "accuracy rate", the "time rate", the "importance" and the "complexity" for evaluating students' learning achievement. First, the proposed method transforms the attributes "accuracy rate" and "time rate" into the "effect of accuracy rate" and the "effect of time rate", respectively. Then, it generates the relative importance degrees of the attributes "effect of accuracy rate", "effect of time rate", "importance" and "complexity" based on the eigenvector method. Then, it uses the correlation coefficients between the attribute vectors and the standard deviations of the elements in the attribute vectors to calculate the fitness degrees of the attributes, where the attribute vectors represent the relationships between the attributes and the questions. Then, it generates the weights of the attributes based on the relative importance degrees of the attributes and the fitness degrees of the attributes. Then, it generates the importance degrees of the questions according to the weights of the attributes and the relation matrix representing the relationships between the questions and the attributes. Finally, based on the importance degrees vector of the questions, the grade matrix, the accuracy rate matrix, it calculates the learning achievement index of each student having the same original total score for students' learning achievement evaluation. The proposed method provides us with a useful way for students' learning achievement evaluation based on the eigenvector method.
机译:本文提出了一种基于特征向量法的学生学习成绩评价新方法。所提出的方法考虑了“准确率”,“时间率”,“重要性”和“复杂性”,以评估学生的学习成绩。首先,所提出的方法将属性“准确率”和“时间率”分别转换为“准确率的影响”和“时间率的影响”。然后,基于特征向量法,生成属性“准确率的影响”,“时间率的影响”,“重要性”和“复杂性”的相对重要性程度。然后,它使用属性向量与属性向量中元素的标准偏差之间的相关系数来计算属性的适应度,其中属性向量表示属性和问题之间的关系。然后,它基于属性的相对重要性程度和属性的适合度来生成属性的权重。然后,根据属性的权重和代表问题与属性之间关系的关系矩阵,生成问题的重要程度。最后,基于问题的重要度向量,等级矩阵,准确率矩阵,计算出具有相同原始总得分的每个学生的学习成绩指数,以评价学生的学习成绩。该方法为基于特征向量法的学生学习成绩评估提供了一条有用的途径。

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