用数据挖掘技术评价大学生友谊状况对学业成绩的影响

T. Bardak, S. Bardak
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摘要

影响学生学习动机的因素有很多。朋友的数量,友谊的满意度和沟通技巧是一些重要的因素。在科学研究中,友谊和同伴排斥对学业成绩有独特的影响。此外,它还强调,如果友谊关系是积极的,它对情感发展是有效的。然而,通过使用数据挖掘技术来检验大学生友谊关系的研究数量非常有限。如今,数据挖掘被广泛应用于许多不同的学科。在其最基本的定义中,数据挖掘是从数据集中提取有意义的信息。随着计算机容量和性能的不断提高,数据科学领域的研究变得越来越容易。本研究采用数据挖掘中常用的关联算法,分析了友谊、年龄、性别、院系与学业成绩之间的关联关系。采用调查法收集数据。数据分析使用了全球流行的Rapidminer软件。作为研究的结果,人们认为友谊关系应该被考虑到学业上的成功。可见,沟通质量对学校的成功和社会生活都是有效的。同时,数据挖掘方法可以有效地用于学生的学业成绩。
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Evaluation of the University Students Friendship Status Effect on Their Academic Achievement with Data Mining Techniques
There are many factors that affect students' motivation to learn. Number of friends, friendship satisfaction and communication skills are some of the important factors. In scientific studies, friendship and peer rejection have unique effects on academic achievement. Besides, it was emphasized that if friendship relations were positive, it was effective on emotional development. However, there are very limited number of studies examining the friendship relationships of university students by using data mining techniques. Data mining is widely used in many different disciplines today. In its most basic definition, data mining is the extraction of meaningful information from a data set. With the increase of computer the capacity and power, studies in the field of data science have become easier. In this study, the association between friendship, age, gender, department and academic achievement was analyzed with the frequently used association algorithm in data mining. Survey method was used to collect data. Rapidminer software, which is popular in the world, was used for data analysis. As a result of the study, it was determined that friendship relations should be taken into consideration in academic success. It is seen that communication quality is effective in school success as well as in social life. Meanwhile, it has been determined that data mining methods can be used effectively in academic achievement of students.
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