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学生各科学习成绩指标的模糊识别

2016-10-31王辉

科教导刊·电子版 2016年23期
关键词:相关关系均衡基础课

王辉

摘 要 本文主要采用了模糊识别的方法对不同课程的成绩之间的相互影响程度进行了计算,为同学们如何以正确地态度面对学习提供了建议。

关键词 专业课 基础课 均衡 知识系统 相关关系

中图分类号:G642.4 文献标识码:A

在高校学生学习过程中,有时会存在着这种情况:有的同学只关注专业课,不重视基础课程,认为及格就行;同时又有一些同学由于在中学阶段成绩比较好,所以保留了偏爱一些基础课程的习惯,专业课成绩相对较差。作为教师,我们主张同学们在学习时间和精力允许的条件下尽可能的均衡发展自己,做到一专多能。事实上,很多课程之间都存在着相辅相成的关系,过于偏科对于学生整个知识系统的建立是不利的。下面将以本校某班学生学习成绩为指标利用相关关系进行评价。

说明:(1)事实上,在这一个学期里考察班级所开课程还有英语、体育和政治,本文主要讨论数学课程与专业课程以及专业课程之间的相关关系,所以在上表中略去了这三门的成绩。(2)由于本班学生较多,所以按学号选取了前15名同学的数据作为研究对象。

两个模糊集、之间的接近程度可以用贴近度函数来描述,

距离贴近度:。

下面通过计算选取的15位同学对应的5门课程成绩指标之间的贴近程度来分析各门课程评价指标之间的相关程度的大小。首先,15位同学对应的5个课程评价指标的相对隶属度值经过归一化处理后得到:

(数学成绩)=(0.067,0.062,0.070,0.066,0.073,0.071,0.076,0.060,0.069,0.062,0.066,0.068,0.074,0.052,0.064)

(CAD成绩)=(0.070,0.071,0.060,0.067,0.074,0.073,0.074,0.036,0.032,0.070,0.075,0.070,0.080,0.072,0.076)

(电工成绩)=(0.061,0.067,0.067,0.065,0.069,0.071,0.072,0.060,0.070,0.070,0.065,0.065,0.072,0.065,0.058)

(计算机文化基础成绩)=(0.076,0.056,0.056,0.057,0.070,0.073,0.082,0.055,0.055,0.074,0.073,0.073,0.077,0.058,0.064)

(机械制图成绩)=(0.062,0.064,0.064,0.064,0.070,0.069,0.089,0.053,0.051,0.065,0.070,0.062,0.089,0.067,0.063)

计算结果见表2。

由择近原则可知,模糊集与模糊集,模糊集与模糊集,模糊集与模糊集,模糊集与模糊集,模糊集与模糊集都很贴近,其中以模糊集与模糊集最为贴近。可以认为贴近的两个模糊集具有紧密的相关关系。从数据可以看出:数学课作为基础课与多门课程都有密切的相关关系,学好数学课程与学好其他课程有直接的联系。特别是电工课,虽然看似与数学关系不大,但从数据分析结果来看两者却非常紧密,从中可以看出学好数学明显的提高了同学的分析、理解和逻辑能力,从而间接的帮助了专业课的学习;另一方面,在专业课的学习过程中也会用到基础课的知识,这种实践会促进基础课程知识的吸收和升华。另外电工和机械制图评价指标贴近度也较高,可以看出这两门专业课的学习有着相辅相成的关系。

参考文献

[1] 刘合香.模糊数学理论及其应用[M].北京:科学出版社,2012.

[2] 罗承忠.模糊集引论(上下册)[M].北京:北京师范大学出版社,1989.

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