基于大数据关联分析的学生考试成绩分析

Analysis of Student Exam Scores Based on Big Data Association Analysis

考试成绩不仅是院校教育者了解教学实施情况的重要参考,更是学生了解自身知识掌握情况、寻找短板弱项、科学制定个人学习目标的重要参考。开展基于大数据的考试成绩分析与应用,寻找学生考试成绩背后各科目之间的相互关联,对于各高校提升管理质量和管理效益,学生开展更有针对性的学习具有十分重要的意义。采用Apriori算法的数据挖掘技术,对我校已毕业的2018级学生高考、在校期间的考试成绩数据进行了分析,寻找制约学生成绩的关键课程和影响因素,为改进人才培养提供数据支撑。

Test scores are not only an important reference for college educators to understand the implementation of teaching,but also an important reference for students to understand their knowledge mastery,find weaknesses,and scientifically establish personal learning goals.Carrying out analysis and application of test scores based on big data and finding the interrelationships between various subjects behind student test scores is of great significance for universities to improve management quality and efficiency,and for students to implement more targeted learning.Using the data mining technology of Apriori algorithm,this paper analyzes the data on the college entrance examination and exam scores of students of 2018,examines key courses and influencing factors that restrict student performance,which provides data support for improving talent cultivation.