数据挖掘在学生成绩分析中的应用研究

发布时间：2018-04-17 04:41

本文选题：数据仓库 + 数据挖掘　；参考：《兰州大学》2017年硕士论文

【摘要】：伴随着高校办学规模的不断扩大和在校生数量的增多,各个高校都相继建立了学籍管理系统、成绩管理系统等教学管理系统。这些系统都具有各自专门的数据库,但目前对它们的处理方式大都是对指定的数据进行简单的备份、查询以及简单统计,并未对这些数据所包含的潜在信息进行提取和分析,这样浪费了大量的信息资源。数据挖掘技术正是解决这类问题可行且有效的方法。将数据仓库与数据挖掘技术应用于学生成绩相关数据分析中,发掘其内部潜在的信息,这些信息对学院课程建设、专业建设、教学质量提高等方面的工作都具有重要的现实意义。本论文将数据挖掘技术应用到我院学生成绩相关数据分析中,发掘出有用的信息,并使用分析得出的结果来进行决策指导,本文的主要工作内容分为以下几个方面:一、对学生各门课程的成绩和学习情况进行调查研究,获取相关初始数据;二、提取学院教学管理信息系统中的数据,并对原始数据进行清理、集成、转换及加载,使用MS SQL Server 2008 R2 EE设计并建立数据仓库;三、采用关联规则挖掘、聚类和分类方法,对教学数据进行深入分析,挖掘出其中的有趣规则,找出课程成绩之间的相互影响关系以及学习成绩与自身学习行为之间的关系;四、对不同的数据挖掘方法进行分析和比较,并对挖掘结果做出评估,为学院教学管理的相关决策方案提供科学参考依据。论文详细阐述了数据挖掘的相关概念以及关联规则挖掘、聚类规则挖掘和分类规则挖掘方法的理论基础与分析过程。重点介绍了数据挖掘技术在学生成绩分析中的应用,并采用这三种挖掘方法进行一组学生考试成绩样本数据的分析:通过对不同课程成绩的相关性的分析,为课程设置的先后顺序提供了一些可行性的建议;通过对课程成绩的聚类分析,弥补了传统成绩等级划分方法的不足;通过对影响课程成绩高低因素的分析,为如何提高课程成绩,进而提高教学质量提供了有益参考。
[Abstract]:With the continuous expansion of the scale of running a university and the increase of the number of students, each university has set up the teaching management system such as student status management system, achievement management system and so on.These systems all have their own special databases, but at present, most of them are processed by simple backup, query and simple statistics of the specified data, without extracting and analyzing the potential information contained in these data.This wasted a lot of information resources.Data mining technology is a feasible and effective method to solve this kind of problems.Applying data warehouse and data mining technology to the data analysis of students' achievement, to discover the potential information inside, which is helpful to the course construction and specialty construction of the college.The improvement of teaching quality has important practical significance.This paper applies the data mining technology to the data analysis of the students' achievement in our college, finds out the useful information, and uses the results of the analysis to guide the decision. The main work of this paper is divided into the following aspects: 1.To investigate and study the students' achievement and study situation of each course, to obtain the related initial data; second, to extract the data from the teaching management information system of the college, and to clean, integrate, convert and load the original data.Using MS SQL Server 2008 R2EE to design and build data warehouse. Thirdly, using association rules mining, clustering and classification methods, the teaching data are deeply analyzed, and the interesting rules are mined out.To find out the interaction between curriculum achievement and learning achievement and their own learning behavior; fourth, to analyze and compare different data mining methods, and to evaluate the results of mining.It provides the scientific reference for the decision-making scheme of the teaching management in the college.The related concepts of data mining and the theoretical basis and analysis process of association rule mining, clustering rule mining and classification rule mining are described in detail in this paper.This paper mainly introduces the application of data mining technology in the analysis of students' scores, and adopts these three mining methods to analyze the sample data of students' examination results.It provides some feasible suggestions for the sequence of curriculum setup; through the clustering analysis of the course results, it makes up for the shortcomings of the traditional grading method; through the analysis of the factors affecting the curriculum achievement,It provides a useful reference for how to improve the course achievement and improve the teaching quality.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G647.3;TP311.13

【参考文献】